Undergraduate Student Motivation in Modularized Developmental Mathematics Courses

ERIC Educational Resources Information Center

Pachlhofer, Keith A.

2017-01-01

This study used the Motivated Strategies for Learning Questionnaire in modularized courses at three institutions across the nation (N = 189), and multiple regression was completed to investigate five categories of student motivation that predicted academic success and course completion. The overall multiple regression analysis was significant and…

Predicting Scientific Understanding of Prospective Elementary Teachers: Role of Gender, Education Level, Courses in Science, and Attitudes Toward Science and Mathematics

NASA Astrophysics Data System (ADS)

Kumar, David D.; Morris, John D.

2005-12-01

A multiple regression analysis of the relationship between prospective teachers' scientific understanding and Gender, Education Level (High School, College), Courses in Science (Biology, Chemistry, Physics, Earth Science, Astronomy, and Agriculture), Attitude Towards Science, and Attitude Towards Mathematics is reported. Undergraduate elementary science students ( N = 176) in an urban doctoral-level university in the United States participated in this study. The results of this study showed Gender, completion of courses in High School Chemistry and Physics, College Chemistry and Physics, and Attitudes Toward Mathematics and Science significantly correlated with scientific understanding. Based on a regression model, Gender, and College Chemistry and Physics experiences added significant predictive accuracy to scientific understanding among prospective elementary teachers compared to the other variables.

Do Developmental Mathematics Programs Have a Causal Impact on Student Retention? An Application of Discrete-Time Survival and Regression-Discontinuity Analysis

ERIC Educational Resources Information Center

Lesik, Sally A.

2007-01-01

The impact of academic programs--such as developmental mathematics programs--on student retention, has been a controversial topic for administrators, policy makers, and faculty in higher education. Despite deep interest in the effectiveness of these programs in retaining students, scholars have been unable to determine whether such programs have a…

Implications of Interactions among Society, Education and Technology: A Comparison of Multiple Linear Regression and Multilevel Modeling in Mathematics Achievement Analyses

ERIC Educational Resources Information Center

Deering, Pamela Rose

2014-01-01

This research compares and contrasts two approaches to predictive analysis of three years' of school district data to investigate relationships between student and teacher characteristics and math achievement as measured by the state-mandated Maryland School Assessment mathematics exam. The sample for the study consisted of 3,514 students taught…

Factors influencing undergraduates' self-evaluation of numerical competence

NASA Astrophysics Data System (ADS)

Tariq, Vicki N.; Durrani, Naureen

2012-04-01

This empirical study explores factors influencing undergraduates' self-evaluation of their numerical competence, using data from an online survey completed by 566 undergraduates from a diversity of academic disciplines, across all four faculties at a post-1992 UK university. Analysis of the data, which included correlation and multiple regression analyses, revealed that undergraduates exhibiting greater confidence in their mathematical and numeracy skills, as evidenced by their higher self-evaluation scores and their higher scores on the confidence sub-scale contributing to the measurement of attitude, possess more cohesive, rather than fragmented, conceptions of mathematics, and display more positive attitudes towards mathematics/numeracy. They also exhibit lower levels of mathematics anxiety. Students exhibiting greater confidence also tended to be those who were relatively young (i.e. 18-29 years), whose degree programmes provided them with opportunities to practise and further develop their numeracy skills, and who possessed higher pre-university mathematics qualifications. The multiple regression analysis revealed two positive predictors (overall attitude towards mathematics/numeracy and possession of a higher pre-university mathematics qualification) and five negative predictors (mathematics anxiety, lack of opportunity to practise/develop numeracy skills, being a more mature student, being enrolled in Health and Social Care compared with Science and Technology, and possessing no formal mathematics/numeracy qualification compared with a General Certificate of Secondary Education or equivalent qualification) accounted for approximately 64% of the variation in students' perceptions of their numerical competence. Although the results initially suggested that male students were significantly more confident than females, one compounding variable was almost certainly the students' highest pre-university mathematics or numeracy qualification, since a higher percentage of males (24%) compared to females (15%) possessed an Advanced Subsidiary or A2 qualification (or equivalent) in mathematics. Of particular concern is the fact that undergraduates based in Health and Social Care expressed significantly less confidence in their numeracy skills than students from any of the other three faculties.

Establishing a Mathematical Equations and Improving the Production of L-tert-Leucine by Uniform Design and Regression Analysis.

PubMed

Jiang, Wei; Xu, Chao-Zhen; Jiang, Si-Zhi; Zhang, Tang-Duo; Wang, Shi-Zhen; Fang, Bai-Shan

2017-04-01

L-tert-Leucine (L-Tle) and its derivatives are extensively used as crucial building blocks for chiral auxiliaries, pharmaceutically active ingredients, and ligands. Combining with formate dehydrogenase (FDH) for regenerating the expensive coenzyme NADH, leucine dehydrogenase (LeuDH) is continually used for synthesizing L-Tle from α-keto acid. A multilevel factorial experimental design was executed for research of this system. In this work, an efficient optimization method for improving the productivity of L-Tle was developed. And the mathematical model between different fermentation conditions and L-Tle yield was also determined in the form of the equation by using uniform design and regression analysis. The multivariate regression equation was conveniently implemented in water, with a space time yield of 505.9 g L -1  day -1 and an enantiomeric excess value of >99 %. These results demonstrated that this method might become an ideal protocol for industrial production of chiral compounds and unnatural amino acids such as chiral drug intermediates.

Determinants of Academic Attainment in the United States: A Quantile Regression Analysis of Test Scores

ERIC Educational Resources Information Center

Haile, Getinet Astatike; Nguyen, Anh Ngoc

2008-01-01

We investigate the determinants of high school students' academic attainment in mathematics, reading and science in the United States; focusing particularly on possible differential impacts of ethnicity and family background across the distribution of test scores. Using data from the NELS2000 and employing quantile regression, we find two…

Radiomorphometric analysis of frontal sinus for sex determination.

PubMed

Verma, Saumya; Mahima, V G; Patil, Karthikeya

2014-09-01

Sex determination of unknown individuals carries crucial significance in forensic research, in cases where fragments of skull persist with no likelihood of identification based on dental arch. In these instances sex determination becomes important to rule out certain number of possibilities instantly and helps in establishing a biological profile of human remains. The aim of the study is to evaluate a mathematical method based on logistic regression analysis capable of ascertaining the sex of individuals in the South Indian population. The study was conducted in the department of Oral Medicine and Radiology. The right and left areas, maximum height, width of frontal sinus were determined in 100 Caldwell views of 50 women and 50 men aged 20 years and above, with the help of Vernier callipers and a square grid with 1 square measuring 1mm(2) in area. Student's t-test, logistic regression analysis. The mean values of variables were greater in men, based on Student's t-test at 5% level of significance. The mathematical model based on logistic regression analysis gave percentage agreement of total area to correctly predict the female gender as 55.2%, of right area as 60.9% and of left area as 55.2%. The areas of the frontal sinus and the logistic regression proved to be unreliable in sex determination. (Logit = 0.924 - 0.00217 × right area).

Are learning strategies linked to academic performance among adolescents in two States in India? A tobit regression analysis.

PubMed

Areepattamannil, Shaljan

2014-01-01

The results of the fourth cycle of the Program for International Student Assessment (PISA) revealed that an unacceptably large number of adolescent students in two states in India-Himachal Pradesh and Tamil Nadu-have failed to acquire basic skills in reading, mathematics, and science (Walker, 2011). Drawing on data from the PISA 2009 database and employing multivariate left-censored to bit regression as a data analytic strategy, the present study, therefore, examined whether or not the learning strategies-memorization, elaboration, and control strategies-of adolescent students in Himachal Pradesh (N = 1,616; Mean age = 15.81 years) and Tamil Nadu (N = 3,210; Mean age = 15.64 years) were linked to their performance on the PISA 2009 reading, mathematics, and science assessments. Tobit regression analyses, after accounting for student demographic characteristics, revealed that the self-reported use of control strategies was significantly positively associated with reading, mathematical, and scientific literacy of adolescents in Himachal Pradesh and Tamil Nadu. While the self-reported use of elaboration strategies was not significantly associated with reading literacy among adolescents in Himachal Pradesh and Tamil Nadu, it was significantly positively associated with mathematical literacy among adolescents in Himachal Pradesh and Tamil Nadu. Moreover, the self-reported use of elaboration strategies was significantly and positively linked to scientific literacy among adolescents in Himachal Pradesh alone. The self-reported use of memorization strategies was significantly negatively associated with reading, mathematical, and scientific literacy in Tamil Nadu, while it was significantly negatively associated with mathematical and scientific literacy alone in Himachal Pradesh. Implications of these findings are discussed.

Regression modeling and prediction of road sweeping brush load characteristics from finite element analysis and experimental results.

PubMed

Wang, Chong; Sun, Qun; Wahab, Magd Abdel; Zhang, Xingyu; Xu, Limin

2015-09-01

Rotary cup brushes mounted on each side of a road sweeper undertake heavy debris removal tasks but the characteristics have not been well known until recently. A Finite Element (FE) model that can analyze brush deformation and predict brush characteristics have been developed to investigate the sweeping efficiency and to assist the controller design. However, the FE model requires large amount of CPU time to simulate each brush design and operating scenario, which may affect its applications in a real-time system. This study develops a mathematical regression model to summarize the FE modeled results. The complex brush load characteristic curves were statistically analyzed to quantify the effects of cross-section, length, mounting angle, displacement and rotational speed etc. The data were then fitted by a multiple variable regression model using the maximum likelihood method. The fitted results showed good agreement with the FE analysis results and experimental results, suggesting that the mathematical regression model may be directly used in a real-time system to predict characteristics of different brushes under varying operating conditions. The methodology may also be used in the design and optimization of rotary brush tools. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Student and School Level Variables Related to Mathematics Self-Efficacy Level Based on PISA 2012 Results for China-Shanghai, Turkey, and Greece

ERIC Educational Resources Information Center

Usta, H. Gonca

2016-01-01

This study aims to analyze the student and school level variables that affect students' self-efficacy levels in mathematics in China-Shanghai, Turkey, and Greece based on PISA 2012 results. In line with this purpose, the hierarchical linear regression model (HLM) was employed. The interschool variability is estimated at approximately 17% in…

Biodiversity patterns along ecological gradients: unifying β-diversity indices.

PubMed

Szava-Kovats, Robert C; Pärtel, Meelis

2014-01-01

Ecologists have developed an abundance of conceptions and mathematical expressions to define β-diversity, the link between local (α) and regional-scale (γ) richness, in order to characterize patterns of biodiversity along ecological (i.e., spatial and environmental) gradients. These patterns are often realized by regression of β-diversity indices against one or more ecological gradients. This practice, however, is subject to two shortcomings that can undermine the validity of the biodiversity patterns. First, many β-diversity indices are constrained to range between fixed lower and upper limits. As such, regression analysis of β-diversity indices against ecological gradients can result in regression curves that extend beyond these mathematical constraints, thus creating an interpretational dilemma. Second, despite being a function of the same measured α- and γ-diversity, the resultant biodiversity pattern depends on the choice of β-diversity index. We propose a simple logistic transformation that rids beta-diversity indices of their mathematical constraints, thus eliminating the possibility of an uninterpretable regression curve. Moreover, this transformation results in identical biodiversity patterns for three commonly used classical beta-diversity indices. As a result, this transformation eliminates the difficulties of both shortcomings, while allowing the researcher to use whichever beta-diversity index deemed most appropriate. We believe this method can help unify the study of biodiversity patterns along ecological gradients.

Biodiversity Patterns along Ecological Gradients: Unifying β-Diversity Indices

PubMed Central

Szava-Kovats, Robert C.; Pärtel, Meelis

2014-01-01

Ecologists have developed an abundance of conceptions and mathematical expressions to define β-diversity, the link between local (α) and regional-scale (γ) richness, in order to characterize patterns of biodiversity along ecological (i.e., spatial and environmental) gradients. These patterns are often realized by regression of β-diversity indices against one or more ecological gradients. This practice, however, is subject to two shortcomings that can undermine the validity of the biodiversity patterns. First, many β-diversity indices are constrained to range between fixed lower and upper limits. As such, regression analysis of β-diversity indices against ecological gradients can result in regression curves that extend beyond these mathematical constraints, thus creating an interpretational dilemma. Second, despite being a function of the same measured α- and γ-diversity, the resultant biodiversity pattern depends on the choice of β-diversity index. We propose a simple logistic transformation that rids beta-diversity indices of their mathematical constraints, thus eliminating the possibility of an uninterpretable regression curve. Moreover, this transformation results in identical biodiversity patterns for three commonly used classical beta-diversity indices. As a result, this transformation eliminates the difficulties of both shortcomings, while allowing the researcher to use whichever beta-diversity index deemed most appropriate. We believe this method can help unify the study of biodiversity patterns along ecological gradients. PMID:25330181

USE OF WEIBULL FUNCTION FOR NON-LINEAR ANALYSIS OF EFFECTS OF LOW LEVELS OF SIMULATED HERBICIDE DRIFT ON PLANTS

EPA Science Inventory

We compared two regression models, which are based on the Weibull and probit functions, for the analysis of pesticide toxicity data from laboratory studies on Illinois crop and native plant species. Both mathematical models are continuous, differentiable, strictly positive, and...

Effects of intracerebroventricular administration of beta-amyloid on the dynamics of learning in purebred and mongrel rats.

PubMed

Stepanov, I I; Kuznetsova, N N; Klement'ev, B I; Sapronov, N S

2007-07-01

The effects of intracerebroventricular administration of the beta-amyloid peptide fragment Abeta(25-35) on the dynamics of the acquisition of a conditioned reflex in a Y maze were studied in Wistar and mongrel rats. The dynamics of decreases in the number of errors were assessed using an exponential mathematical model describing the transfer function of a first-order system in response to stepped inputs using non-linear regression analysis. This mathematical model provided a good approximation to the learning dynamics in inbred and mongrel mice. In Wistar rats, beta-amyloid impaired learning, with reduced memory between the first and second training sessions, but without complete blockade of learning. As a result, learning dynamics were no longer approximated by the mathematical model. At the same time, comparison of the number of errors in each training sessions between the control group of Wistar rats and the group given beta-amyloid showed no significant differences (Student's t test). This result demonstrates the advantage of regression analysis based on a mathematical model over the traditionally used statistical methods. In mongrel rats, the effect of beta-amyloid was limited to an a slowing of the process of learning as compared with control mongrel rats, with retention of the approximation by the mathematical model. It is suggested that mongrel animals have some kind of innate, genetically determined protective mechanism against the harmful effects of beta-amyloid.

The role of attention in the academic attainment of children with autism spectrum disorder.

PubMed

May, Tamara; Rinehart, Nicole; Wilding, John; Cornish, Kim

2013-09-01

Academic attainment in children with Autism Spectrum Disorder (ASD) is under-studied, with associated factors largely undetermined. Parent-reported attention symptoms, attentional-switching and sustained-attention tasks were examined to determine relationships with mathematics and reading attainment in 124 children aged 7-12 years; sixty-four with high-functioning ASD, half girls, and sixty age- and gender-matched typical children (TYP). With full-scale IQ controlled there were no differences in mathematics, reading, attentional switching or sustained attention. In regression analysis, attentional switching was related to mathematics achievement in ASD but not TYP children. Findings highlight attentional switching difficulties are linked with poorer mathematics outcomes in ASD.

Mathematical analysis of the normal anatomy of the aging fovea.

PubMed

Nesmith, Brooke; Gupta, Akash; Strange, Taylor; Schaal, Yuval; Schaal, Shlomit

2014-08-28

To mathematically analyze anatomical changes that occur in the normal fovea during aging. A total of 2912 spectral-domain optical coherence tomography (SD-OCT) normal foveal scans were analyzed. Subjects were healthy individuals, aged 13 to 97 years, with visual acuity ≥20/40 and without evidence of foveal pathology. Using automated symbolic regression software Eureqa (version 0.98), foveal thickness maps of 390 eyes were analyzed using several measurements: parafoveal retinal thickness at 50 μm consecutive intervals, parafoveal maximum retinal thickness at two points lateral to central foveal depression, distance between two points of maximum retinal thickness, maximal foveal slope at two intervals lateral to central foveal depression, and central length of foveal depression. A unique mathematical equation representing the mathematical analog of foveal anatomy was derived for every decade, between 10 and 100 years. The mathematical regression function for normal fovea followed first order sine curve of level 10 complexity for the second decade of life. The mathematical regression function became more complex with normal aging, up to level 43 complexity (0.085 fit; P < 0.05). Young foveas had higher symmetry (0.92 ± 0.10) along midline, whereas aged foveas had significantly less symmetry (0.76 ± 0.27, P < 0.01) along midline and steeper maximal slopes (29 ± 32°, P < 0.01). Normal foveal anatomical configuration changes with age. Normal aged foveas are less symmetric along midline with steeper slopes. Differentiating between normal aging and pathologic changes using SD-OCT scans may allow early diagnosis, follow-up, and better management of the aging population. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

The nonlinear relations of the approximate number system and mathematical language to early mathematics development.

PubMed

Purpura, David J; Logan, Jessica A R

2015-12-01

Both mathematical language and the approximate number system (ANS) have been identified as strong predictors of early mathematics performance. Yet, these relations may be different depending on a child's developmental level. The purpose of this study was to evaluate the relations between these domains across different levels of ability. Participants included 114 children who were assessed in the fall and spring of preschool on a battery of academic and cognitive tasks. Children were 3.12 to 5.26 years old (M = 4.18, SD = .58) and 53.6% were girls. Both mixed-effect and quantile regressions were conducted. The mixed-effect regressions indicated that mathematical language, but not the ANS, nor other cognitive domains, predicted mathematics performance. However, the quantile regression analyses revealed a more nuanced relation among domains. Specifically, it was found that mathematical language and the ANS predicted mathematical performance at different points on the ability continuum. These dual nonlinear relations indicate that different mechanisms may enhance mathematical acquisition dependent on children's developmental abilities. (c) 2015 APA, all rights reserved).

Advanced statistics: linear regression, part I: simple linear regression.

PubMed

Marill, Keith A

2004-01-01

Simple linear regression is a mathematical technique used to model the relationship between a single independent predictor variable and a single dependent outcome variable. In this, the first of a two-part series exploring concepts in linear regression analysis, the four fundamental assumptions and the mechanics of simple linear regression are reviewed. The most common technique used to derive the regression line, the method of least squares, is described. The reader will be acquainted with other important concepts in simple linear regression, including: variable transformations, dummy variables, relationship to inference testing, and leverage. Simplified clinical examples with small datasets and graphic models are used to illustrate the points. This will provide a foundation for the second article in this series: a discussion of multiple linear regression, in which there are multiple predictor variables.

Regarding to the Variance Analysis of Regression Equation of the Surface Roughness obtained by End Milling process of 7136 Aluminium Alloy

NASA Astrophysics Data System (ADS)

POP, A. B.; ȚÎȚU, M. A.

2016-11-01

In the metal cutting process, surface quality is intrinsically related to the cutting parameters and to the cutting tool geometry. At the same time, metal cutting processes are closely related to the machining costs. The purpose of this paper is to reduce manufacturing costs and processing time. A study was made, based on the mathematical modelling of the average of the absolute value deviation (Ra) resulting from the end milling process on 7136 aluminium alloy, depending on cutting process parameters. The novel element brought by this paper is the 7136 aluminium alloy type, chosen to conduct the experiments, which is a material developed and patented by Universal Alloy Corporation. This aluminium alloy is used in the aircraft industry to make parts from extruded profiles, and it has not been studied for the proposed research direction. Based on this research, a mathematical model of surface roughness Ra was established according to the cutting parameters studied in a set experimental field. A regression analysis was performed, which identified the quantitative relationships between cutting parameters and the surface roughness. Using the variance analysis ANOVA, the degree of confidence for the achieved results by the regression equation was determined, and the suitability of this equation at every point of the experimental field.

Which Instructional Practices Most Help First Grade Students with and without Mathematics Difficulties?

PubMed

Morgan, Paul L; Farkas, George; Maczuga, Steve

2015-06-01

We used population-based, longitudinal data to investigate the relation between mathematics instructional practices used by 1 st grade teachers in the U.S. and the mathematics achievement of their students. Factor analysis identified four types of instructional activities (i.e., teacher-directed, student-centered, manipulatives/calculators, movement/music) and eight types of specific skills taught (e.g., adding two-digit numbers). First-grade students were then classified into five groups on the basis of their fall and/or spring of kindergarten mathematics achievement-three groups with mathematics difficulties (MD) and two without MD. Regression analysis indicated that a higher percentage of MD students in 1 st grade classrooms was associated with greater use by teachers of manipulatives/calculators and movement/music to teach mathematics. Yet follow-up analysis for each of the MD and non-MD groups indicated that only teacher-directed instruction was significantly associated with the achievement of students with MD (covariate-adjusted ES s = .05-.07). The largest predicted effect for a specific instructional practice was for routine practice and drill. In contrast, for both groups of non-MD students, teacher-directed and student-centered instruction had approximately equal, statistically significant positive predicted effects (covariate-adjusted ES s = .03-.04). First-grade teachers in the U.S. may need to increase their use of teacher-directed instruction if they are to raise the mathematics achievement of students with MD.

Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: Evidence from Quantile Regression Analyses

ERIC Educational Resources Information Center

Shafiq, M. Najeeb

2011-01-01

Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15 year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

Gender Gaps in Mathematics, Science and Reading Achievements in Muslim Countries: A Quantile Regression Approach

ERIC Educational Resources Information Center

Shafiq, M. Najeeb

2013-01-01

Using quantile regression analyses, this study examines gender gaps in mathematics, science, and reading in Azerbaijan, Indonesia, Jordan, the Kyrgyz Republic, Qatar, Tunisia, and Turkey among 15-year-old students. The analyses show that girls in Azerbaijan achieve as well as boys in mathematics and science and overachieve in reading. In Jordan,…

[Stature estimation for Sichuan Han nationality female based on X-ray technology with measurement of lumbar vertebrae].

PubMed

Qing, Si-han; Chang, Yun-feng; Dong, Xiao-ai; Li, Yuan; Chen, Xiao-gang; Shu, Yong-kang; Deng, Zhen-hua

2013-10-01

To establish the mathematical models of stature estimation for Sichuan Han female with measurement of lumbar vertebrae by X-ray to provide essential data for forensic anthropology research. The samples, 206 Sichuan Han females, were divided into three groups including group A, B and C according to the ages. Group A (206 samples) consisted of all ages, group B (116 samples) were 20-45 years old and 90 samples over 45 years old were group C. All the samples were examined lumbar vertebrae through CR technology, including the parameters of five centrums (L1-L5) as anterior border, posterior border and central heights (x1-x15), total central height of lumbar spine (x16), and the real height of every sample. The linear regression analysis was produced using the parameters to establish the mathematical models of stature estimation. Sixty-two trained subjects were tested to verify the accuracy of the mathematical models. The established mathematical models by hypothesis test of linear regression equation model were statistically significant (P<0.05). The standard errors of the equation were 2.982-5.004 cm, while correlation coefficients were 0.370-0.779 and multiple correlation coefficients were 0.533-0.834. The return tests of the highest correlation coefficient and multiple correlation coefficient of each group showed that the highest accuracy of the multiple regression equation, y = 100.33 + 1.489 x3 - 0.548 x6 + 0.772 x9 + 0.058 x12 + 0.645 x15, in group A were 80.6% (+/- lSE) and 100% (+/- 2SE). The established mathematical models in this study could be applied for the stature estimation for Sichuan Han females.

Atmospheric mold spore counts in relation to meteorological parameters

NASA Astrophysics Data System (ADS)

Katial, R. K.; Zhang, Yiming; Jones, Richard H.; Dyer, Philip D.

Fungal spore counts of Cladosporium, Alternaria, and Epicoccum were studied during 8 years in Denver, Colorado. Fungal spore counts were obtained daily during the pollinating season by a Rotorod sampler. Weather data were obtained from the National Climatic Data Center. Daily averages of temperature, relative humidity, daily precipitation, barometric pressure, and wind speed were studied. A time series analysis was performed on the data to mathematically model the spore counts in relation to weather parameters. Using SAS PROC ARIMA software, a regression analysis was performed, regressing the spore counts on the weather variables assuming an autoregressive moving average (ARMA) error structure. Cladosporium was found to be positively correlated (P<0.02) with average daily temperature, relative humidity, and negatively correlated with precipitation. Alternaria and Epicoccum did not show increased predictability with weather variables. A mathematical model was derived for Cladosporium spore counts using the annual seasonal cycle and significant weather variables. The model for Alternaria and Epicoccum incorporated the annual seasonal cycle. Fungal spore counts can be modeled by time series analysis and related to meteorological parameters controlling for seasonallity; this modeling can provide estimates of exposure to fungal aeroallergens.

Regression analysis for solving diagnosis problem of children's health

NASA Astrophysics Data System (ADS)

Cherkashina, Yu A.; Gerget, O. M.

2016-04-01

The paper includes results of scientific researches. These researches are devoted to the application of statistical techniques, namely, regression analysis, to assess the health status of children in the neonatal period based on medical data (hemostatic parameters, parameters of blood tests, the gestational age, vascular-endothelial growth factor) measured at 3-5 days of children's life. In this paper a detailed description of the studied medical data is given. A binary logistic regression procedure is discussed in the paper. Basic results of the research are presented. A classification table of predicted values and factual observed values is shown, the overall percentage of correct recognition is determined. Regression equation coefficients are calculated, the general regression equation is written based on them. Based on the results of logistic regression, ROC analysis was performed, sensitivity and specificity of the model are calculated and ROC curves are constructed. These mathematical techniques allow carrying out diagnostics of health of children providing a high quality of recognition. The results make a significant contribution to the development of evidence-based medicine and have a high practical importance in the professional activity of the author.

[Influence of sample surface roughness on mathematical model of NIR quantitative analysis of wood density].

PubMed

Huang, An-Min; Fei, Ben-Hua; Jiang, Ze-Hui; Hse, Chung-Yun

2007-09-01

Near infrared spectroscopy is widely used as a quantitative method, and the main multivariate techniques consist of regression methods used to build prediction models, however, the accuracy of analysis results will be affected by many factors. In the present paper, the influence of different sample roughness on the mathematical model of NIR quantitative analysis of wood density was studied. The result of experiments showed that if the roughness of predicted samples was consistent with that of calibrated samples, the result was good, otherwise the error would be much higher. The roughness-mixed model was more flexible and adaptable to different sample roughness. The prediction ability of the roughness-mixed model was much better than that of the single-roughness model.

Which Instructional Practices Most Help First Grade Students with and without Mathematics Difficulties?

PubMed Central

Morgan, Paul L.; Farkas, George; Maczuga, Steve

2015-01-01

We used population-based, longitudinal data to investigate the relation between mathematics instructional practices used by 1st grade teachers in the U.S. and the mathematics achievement of their students. Factor analysis identified four types of instructional activities (i.e., teacher-directed, student-centered, manipulatives/calculators, movement/music) and eight types of specific skills taught (e.g., adding two-digit numbers). First-grade students were then classified into five groups on the basis of their fall and/or spring of kindergarten mathematics achievement—three groups with mathematics difficulties (MD) and two without MD. Regression analysis indicated that a higher percentage of MD students in 1st grade classrooms was associated with greater use by teachers of manipulatives/calculators and movement/music to teach mathematics. Yet follow-up analysis for each of the MD and non-MD groups indicated that only teacher-directed instruction was significantly associated with the achievement of students with MD (covariate-adjusted ESs = .05–.07). The largest predicted effect for a specific instructional practice was for routine practice and drill. In contrast, for both groups of non-MD students, teacher-directed and student-centered instruction had approximately equal, statistically significant positive predicted effects (covariate-adjusted ESs = .03–.04). First-grade teachers in the U.S. may need to increase their use of teacher-directed instruction if they are to raise the mathematics achievement of students with MD. PMID:26180268

Deaf college students' mathematical skills relative to morphological knowledge, reading level, and language proficiency.

PubMed

Kelly, Ronald R; Gaustad, Martha G

2007-01-01

This study of deaf college students examined specific relationships between their mathematics performance and their assessed skills in reading, language, and English morphology. Simple regression analyses showed that deaf college students' language proficiency scores, reading grade level, and morphological knowledge regarding word segmentation and meaning were all significantly correlated with both the ACT Mathematics Subtest and National Technical Institute for the Deaf (NTID) Mathematics Placement Test scores. Multiple regression analyses identified the best combination from among these potential independent predictors of students' performance on both the ACT and NTID mathematics tests. Additionally, the participating deaf students' grades in their college mathematics courses were significantly and positively associated with their reading grade level and their knowledge of morphological components of words.

Influences of Self-Perceived Competence in Mathematics and Positive Affect toward Mathematics on Mathematics Achievement of Adolescents in Singapore

ERIC Educational Resources Information Center

Areepattamannil, Shaljan; Kaur, Berinderjeet

2012-01-01

This study, drawing on data from the Trends in International Mathematics and Science Study (TIMSS) 2007, examined the influences of self-perceived competence in mathematics and positive affect toward mathematics on mathematics achievement of adolescents in Singapore. Ordinary least squares (OLS) regression analyses revealed the positive influences…

Teacher Salaries and Teacher Aptitude: An Analysis Using Quantile Regressions

ERIC Educational Resources Information Center

Gilpin, Gregory A.

2012-01-01

This study investigates the relationship between salaries and scholastic aptitude for full-time public high school humanities and mathematics/sciences teachers. For identification, we rely on variation in salaries between adjacent school districts within the same state. The results indicate that teacher aptitude is positively correlated with…

Multiple regression technique for Pth degree polynominals with and without linear cross products

NASA Technical Reports Server (NTRS)

Davis, J. W.

1973-01-01

A multiple regression technique was developed by which the nonlinear behavior of specified independent variables can be related to a given dependent variable. The polynomial expression can be of Pth degree and can incorporate N independent variables. Two cases are treated such that mathematical models can be studied both with and without linear cross products. The resulting surface fits can be used to summarize trends for a given phenomenon and provide a mathematical relationship for subsequent analysis. To implement this technique, separate computer programs were developed for the case without linear cross products and for the case incorporating such cross products which evaluate the various constants in the model regression equation. In addition, the significance of the estimated regression equation is considered and the standard deviation, the F statistic, the maximum absolute percent error, and the average of the absolute values of the percent of error evaluated. The computer programs and their manner of utilization are described. Sample problems are included to illustrate the use and capability of the technique which show the output formats and typical plots comparing computer results to each set of input data.

Assessment of heart rate variability based on mobile device for planning physical activity

NASA Astrophysics Data System (ADS)

Svirin, I. S.; Epishina, E. V.; Voronin, V. V.; Semenishchev, E. A.; Solodova, E. N.; Nabilskaya, N. V.

2015-05-01

In this paper we present a method for the functional analysis of human heart based on electrocardiography (ECG) signals. The approach using the apparatus of analytical and differential geometry and correlation and regression analysis. ECG contains information on the current condition of the cardiovascular system as well as on the pathological changes in the heart. Mathematical processing of the heart rate variability allows to obtain a great set of mathematical and statistical characteristics. These characteristics of the heart rate are used when solving research problems to study physiological changes that determine functional changes of an individual. The proposed method implemented for up-to-date mobile Android and iOS based devices.

Propensity score estimation: machine learning and classification methods as alternatives to logistic regression

PubMed Central

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-01-01

Summary Objective Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this Review was to assess machine learning alternatives to logistic regression which may accomplish the same goals but with fewer assumptions or greater accuracy. Study Design and Setting We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. Results We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (CART), and meta-classifiers (in particular, boosting). Conclusion While the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and to a lesser extent decision trees (particularly CART) appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. PMID:20630332

New Evidence on Causal Relationship between Approximate Number System (ANS) Acuity and Arithmetic Ability in Elementary-School Students: A Longitudinal Cross-Lagged Analysis.

PubMed

He, Yunfeng; Zhou, Xinlin; Shi, Dexin; Song, Hairong; Zhang, Hui; Shi, Jiannong

2016-01-01

Approximate number system (ANS) acuity and mathematical ability have been found to be closely associated in recent studies. However, whether and how these two measures are causally related still remain less addressed. There are two hypotheses about the possible causal relationship: ANS acuity influences mathematical performances, or access to math education sharpens ANS acuity. Evidences in support of both hypotheses have been reported, but these two hypotheses have never been tested simultaneously. Therefore, questions still remain whether only one-direction or reciprocal causal relationships existed in the association. In this work, we provided a new evidence on the causal relationship between ANS acuity and arithmetic ability. ANS acuity and mathematical ability of elementary-school students were measured sequentially at three time points within one year, and all possible causal directions were evaluated simultaneously using cross-lagged regression analysis. The results show that ANS acuity influences later arithmetic ability while the reverse causal direction was not supported. Our finding adds a strong evidence to the causal association between ANS acuity and mathematical ability, and also has important implications for educational intervention designed to train ANS acuity and thereby promote mathematical ability.

New Evidence on Causal Relationship between Approximate Number System (ANS) Acuity and Arithmetic Ability in Elementary-School Students: A Longitudinal Cross-Lagged Analysis

PubMed Central

He, Yunfeng; Zhou, Xinlin; Shi, Dexin; Song, Hairong; Zhang, Hui; Shi, Jiannong

2016-01-01

Approximate number system (ANS) acuity and mathematical ability have been found to be closely associated in recent studies. However, whether and how these two measures are causally related still remain less addressed. There are two hypotheses about the possible causal relationship: ANS acuity influences mathematical performances, or access to math education sharpens ANS acuity. Evidences in support of both hypotheses have been reported, but these two hypotheses have never been tested simultaneously. Therefore, questions still remain whether only one-direction or reciprocal causal relationships existed in the association. In this work, we provided a new evidence on the causal relationship between ANS acuity and arithmetic ability. ANS acuity and mathematical ability of elementary-school students were measured sequentially at three time points within one year, and all possible causal directions were evaluated simultaneously using cross-lagged regression analysis. The results show that ANS acuity influences later arithmetic ability while the reverse causal direction was not supported. Our finding adds a strong evidence to the causal association between ANS acuity and mathematical ability, and also has important implications for educational intervention designed to train ANS acuity and thereby promote mathematical ability. PMID:27462291

An investigation of correlation between pilot scanning behavior and workload using stepwise regression analysis

NASA Technical Reports Server (NTRS)

Waller, M. C.

1976-01-01

An electro-optical device called an oculometer which tracks a subject's lookpoint as a time function has been used to collect data in a real-time simulation study of instrument landing system (ILS) approaches. The data describing the scanning behavior of a pilot during the instrument approaches have been analyzed by use of a stepwise regression analysis technique. A statistically significant correlation between pilot workload, as indicated by pilot ratings, and scanning behavior has been established. In addition, it was demonstrated that parameters derived from the scanning behavior data can be combined in a mathematical equation to provide a good representation of pilot workload.

STEM development: A study of 6th--12th grade girls' interest and confidence in mathematics and science

NASA Astrophysics Data System (ADS)

Heaverlo, Carol Ann

Researchers, policymakers, business, and industry have indicated that the United States will experience a shortage of professionals in the Science, Technology, Engineering, and Mathematics (STEM) fields. Several strategies have been suggested to address this shortage, one of which includes increasing the representation of girls and women in the STEM fields. In order to increase the representation of women in the STEM fields, it is important to understand the developmental factors that impact girls' interest and confidence in STEM academics and extracurricular programs. Research indicates that greater confidence leads to greater interest and vice versa (Denissen et al., 2007). This study identifies factors that impact girls' interest and confidence in mathematics and science, defined as girls' STEM development. Using Bronfenbrenner's (2005) bioecological model of human development, several factors were hypothesized as having an impact on girls' STEM development; specifically, the macrosystems of region of residence and race/ethnicity, and the microsystems of extracurricular STEM activities, family STEM influence, and math/science teacher influence. Hierarchical regression analysis results indicated that extracurricular STEM involvement and math teacher influence were statistically significant predictors for 6--12th grade girls' interest and confidence in mathematics. Furthermore, hierarchical regression analysis results indicated that the only significant predictor for 6--12th grade girls' interest and confidence in science was science teacher influence. This study provides new knowledge about the factors that impact girls' STEM development. Results can be used to inform and guide educators, administrators, and policy makers in developing programs and policy that support and encourage the STEM development of 6--12th grade girls.

Mathematical Ecology Analysis of Geographical Distribution of Soybean-Nodulating Bradyrhizobia in Japan

PubMed Central

Saeki, Yuichi; Shiro, Sokichi; Tajima, Toshiyuki; Yamamoto, Akihiro; Sameshima-Saito, Reiko; Sato, Takashi; Yamakawa, Takeo

2013-01-01

We characterized the relationship between the genetic diversity of indigenous soybean-nodulating bradyrhizobia from weakly acidic soils in Japan and their geographical distribution in an ecological study of indigenous soybean rhizobia. We isolated bradyrhizobia from three kinds of Rj-genotype soybeans. Their genetic diversity and community structure were analyzed by PCR-RFLP analysis of the 16S–23S rRNA gene internal transcribed spacer (ITS) region with 11 Bradyrhizobium USDA strains as references. We used data from the present study and previous studies to carry out mathematical ecological analyses, multidimensional scaling analysis with the Bray-Curtis index, polar ordination analysis, and multiple regression analyses to characterize the relationship between soybean-nodulating bradyrhizobial community structures and their geographical distribution. The mathematical ecological approaches used in this study demonstrated the presence of ecological niches and suggested the geographical distribution of soybean-nodulating bradyrhizobia to be a function of latitude and the related climate, with clusters in the order Bj123, Bj110, Bj6, and Be76 from north to south in Japan. PMID:24240318

Analysis of the Influence of Quantile Regression Model on Mainland Tourists' Service Satisfaction Performance

PubMed Central

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models. PMID:24574916

Analysis of the influence of quantile regression model on mainland tourists' service satisfaction performance.

PubMed

Wang, Wen-Cheng; Cho, Wen-Chien; Chen, Yin-Jen

2014-01-01

It is estimated that mainland Chinese tourists travelling to Taiwan can bring annual revenues of 400 billion NTD to the Taiwan economy. Thus, how the Taiwanese Government formulates relevant measures to satisfy both sides is the focus of most concern. Taiwan must improve the facilities and service quality of its tourism industry so as to attract more mainland tourists. This paper conducted a questionnaire survey of mainland tourists and used grey relational analysis in grey mathematics to analyze the satisfaction performance of all satisfaction question items. The first eight satisfaction items were used as independent variables, and the overall satisfaction performance was used as a dependent variable for quantile regression model analysis to discuss the relationship between the dependent variable under different quantiles and independent variables. Finally, this study further discussed the predictive accuracy of the least mean regression model and each quantile regression model, as a reference for research personnel. The analysis results showed that other variables could also affect the overall satisfaction performance of mainland tourists, in addition to occupation and age. The overall predictive accuracy of quantile regression model Q0.25 was higher than that of the other three models.

Some environmental and attitudinal characteristics as predictors of mathematical creativity

NASA Astrophysics Data System (ADS)

Kanhai, Abhishek; Singh, Bhoodev

2017-04-01

There are many things which can be made more useful and interesting through the application of creativity. Self-concept in mathematics and some school environmental factors such as resource adequacy, teachers' support to the students, teachers' classroom control, creative stimulation by the teachers, etc. were selected in the study. The sample of the study comprised 770 seventh grade students. Pearson correlation, multiple correlation, regression equation and multiple discriminant function analyses of variance were used to analyse the data. The result of the study showed that the relationship between mathematical creativity and each attitudinal and environmental characteristic was found to be positive and significant. Index of forecasting efficiency reveals that mathematical creativity may be best predicted by self-concept in mathematics. Environmental factors, resource adequacy and creative stimulation by the teachers' are found to be the most important factors for predicting mathematical creativity, while social-intellectual involvement among students and educational administration of the schools are to be suppressive factors. The multiple correlation between mathematical creativity and attitudinal and school environmental characteristic suggests that the combined contribution of these variables plays a significant role in the development of mathematical creativity. Mahalanobis analysis indicates that self-concept in mathematics and total school environment were found to be contributing significantly to the development of mathematical creativity.

Separate but correlated: The latent structure of space and mathematics across development.

PubMed

Mix, Kelly S; Levine, Susan C; Cheng, Yi-Ling; Young, Chris; Hambrick, D Zachary; Ping, Raedy; Konstantopoulos, Spyros

2016-09-01

The relations among various spatial and mathematics skills were assessed in a cross-sectional study of 854 children from kindergarten, third, and sixth grades (i.e., 5 to 13 years of age). Children completed a battery of spatial mathematics tests and their scores were submitted to exploratory factor analyses both within and across domains. In the within domain analyses, all of the measures formed single factors at each age, suggesting consistent, unitary structures across this age range. Yet, as in previous work, the 2 domains were highly correlated, both in terms of overall composite score and pairwise comparisons of individual tasks. When both spatial and mathematics scores were submitted to the same factor analysis, the 2 domain specific factors again emerged, but there also were significant cross-domain factor loadings that varied with age. Multivariate regressions replicated the factor analysis and further revealed that mental rotation was the best predictor of mathematical performance in kindergarten, and visual-spatial working memory was the best predictor of mathematical performance in sixth grade. The mathematical tasks that predicted the most variance in spatial skill were place value (K, 3rd, 6th), word problems (3rd, 6th), calculation (K), fraction concepts (3rd), and algebra (6th). Thus, although spatial skill and mathematics each have strong internal structures, they also share significant overlap, and have particularly strong cross-domain relations for certain tasks. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Prediction of the Main Engine Power of a New Container Ship at the Preliminary Design Stage

NASA Astrophysics Data System (ADS)

Cepowski, Tomasz

2017-06-01

The paper presents mathematical relationships that allow us to forecast the estimated main engine power of new container ships, based on data concerning vessels built in 2005-2015. The presented approximations allow us to estimate the engine power based on the length between perpendiculars and the number of containers the ship will carry. The approximations were developed using simple linear regression and multivariate linear regression analysis. The presented relations have practical application for estimation of container ship engine power needed in preliminary parametric design of the ship. It follows from the above that the use of multiple linear regression to predict the main engine power of a container ship brings more accurate solutions than simple linear regression.

An Introduction to Graphical and Mathematical Methods for Detecting Heteroscedasticity in Linear Regression.

ERIC Educational Resources Information Center

Thompson, Russel L.

Homoscedasticity is an important assumption of linear regression. This paper explains what it is and why it is important to the researcher. Graphical and mathematical methods for testing the homoscedasticity assumption are demonstrated. Sources of homoscedasticity and types of homoscedasticity are discussed, and methods for correction are…

A mathematical programming method for formulating a fuzzy regression model based on distance criterion.

PubMed

Chen, Liang-Hsuan; Hsueh, Chan-Ching

2007-06-01

Fuzzy regression models are useful to investigate the relationship between explanatory and response variables with fuzzy observations. Different from previous studies, this correspondence proposes a mathematical programming method to construct a fuzzy regression model based on a distance criterion. The objective of the mathematical programming is to minimize the sum of distances between the estimated and observed responses on the X axis, such that the fuzzy regression model constructed has the minimal total estimation error in distance. Only several alpha-cuts of fuzzy observations are needed as inputs to the mathematical programming model; therefore, the applications are not restricted to triangular fuzzy numbers. Three examples, adopted in the previous studies, and a larger example, modified from the crisp case, are used to illustrate the performance of the proposed approach. The results indicate that the proposed model has better performance than those in the previous studies based on either distance criterion or Kim and Bishu's criterion. In addition, the efficiency and effectiveness for solving the larger example by the proposed model are also satisfactory.

The Relationship between Language Literacy and ELL Student Academic Performance in Mathematics

ERIC Educational Resources Information Center

Lawon, Molly A.

2017-01-01

This quantitative study used regression analysis to investigate the correlation of limited language proficiency and the performance of English Language Learner (ELL) students on two commonly used math assessments, namely the Smarter Balanced Assessment Consortium (SBAC) and the Measures of Academic Progress (MAP). Scores were analyzed for eighth…

Factors Affecting University Entrants' Performance in High-Stakes Tests: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Uy, Chin; Manalo, Ronaldo A.; Cabauatan, Ronaldo R.

2015-01-01

In the Philippines, students seeking admission to a university are usually required to meet certain entrance requirements, including passing the entrance examinations with questions on IQ and English, mathematics, and science. This paper aims to determine the factors that affect the performance of entrants into business programmes in high-stakes…

Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression.

PubMed

Westreich, Daniel; Lessler, Justin; Funk, Michele Jonsson

2010-08-01

Propensity scores for the analysis of observational data are typically estimated using logistic regression. Our objective in this review was to assess machine learning alternatives to logistic regression, which may accomplish the same goals but with fewer assumptions or greater accuracy. We identified alternative methods for propensity score estimation and/or classification from the public health, biostatistics, discrete mathematics, and computer science literature, and evaluated these algorithms for applicability to the problem of propensity score estimation, potential advantages over logistic regression, and ease of use. We identified four techniques as alternatives to logistic regression: neural networks, support vector machines, decision trees (classification and regression trees [CART]), and meta-classifiers (in particular, boosting). Although the assumptions of logistic regression are well understood, those assumptions are frequently ignored. All four alternatives have advantages and disadvantages compared with logistic regression. Boosting (meta-classifiers) and, to a lesser extent, decision trees (particularly CART), appear to be most promising for use in the context of propensity score analysis, but extensive simulation studies are needed to establish their utility in practice. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Anticipating Mathematics Performance: A Cross-Validation Comparison of AID3 and Regression. AIR 1988 Annual Forum Paper.

ERIC Educational Resources Information Center

Bloom, Allan M.; And Others

In response to the increasing importance of student performance in required classes, research was conducted to compare two prediction procedures, linear modeling using multiple regression and nonlinear modeling using AID3. Performance in the first college math course (College Mathematics, Calculus, or Business Calculus Matrices) was the dependent…

The effects of home computer access and social capital on mathematics and science achievement among Asian-American high school students in the NELS:88 data set

NASA Astrophysics Data System (ADS)

Quigley, Mark Declan

The purpose of this researcher was to examine specific environmental, educational, and demographic factors and their influence on mathematics and science achievement. In particular, the researcher ascertained the interconnections of home computer access and social capital, with Asian American students and the effect on mathematics and science achievement. Coleman's theory on social capital and parental influence was used as a basis for the analysis of data. Subjects for this study were the base year students from the National Education Longitudinal Study of 1988 (NELS:88) and the subsequent follow-up survey data in 1990, 1992, and 1994. The approximate sample size for this study is 640 ethnic Asians from the NELS:88 database. The analysis was a longitudinal study based on the Student and Parent Base Year responses and the Second Follow-up survey of 1992, when the subjects were in 12th grade. Achievement test results from the NELS:88 data were used to measure achievement in mathematics and science. The NELS:88 test battery was developed to measure both individual status and a student's growth in a number of achievement areas. The subject's responses were analyzed by principal components factor analysis, weights, effect sizes, hierarchial regression analysis, and PLSPath Analysis. The results of this study were that prior ability in mathematics and science is a major influence in the student's educational achievement. Findings from the study support the view that home computer access has a negative direct effect on mathematics and science achievement for both Asian American males and females. None of the social capital factors in the study had either a negative or positive direct effect on mathematics and science achievement although some indirect effects were found. Suggestions were made toward increasing parental involvement in their children's academic endeavors. Computer access in the home should be considered related to television viewing and should be closely monitored by the parents to promote educational uses.

Noise in restaurants: levels and mathematical model.

PubMed

To, Wai Ming; Chung, Andy

2014-01-01

Noise affects the dining atmosphere and is an occupational hazard to restaurant service employees worldwide. This paper examines the levels of noise in dining areas during peak hours in different types of restaurants in Hong Kong SAR, China. A mathematical model that describes the noise level in a restaurant is presented. The 1-h equivalent continuous noise level (L(eq,1-h)) was measured using a Type-1 precision integral sound level meter while the occupancy density, the floor area of the dining area, and the ceiling height of each of the surveyed restaurants were recorded. It was found that the measured noise levels using Leq,1-h ranged from 67.6 to 79.3 dBA in Chinese restaurants, from 69.1 to 79.1 dBA in fast food restaurants, and from 66.7 to 82.6 dBA in Western restaurants. Results of the analysis of variance show that there were no significant differences between means of the measured noise levels among different types of restaurants. A stepwise multiple regression analysis was employed to determine the relationships between geometrical and operational parameters and the measured noise levels. Results of the regression analysis show that the measured noise levels depended on the levels of occupancy density only. By reconciling the measured noise levels and the mathematical model, it was found that people in restaurants increased their voice levels when the occupancy density increased. Nevertheless, the maximum measured hourly noise level indicated that the noise exposure experienced by restaurant service employees was below the regulated daily noise exposure value level of 85 dBA.

Multiple Linear Regression Analysis of Factors Affecting Real Property Price Index From Case Study Research In Istanbul/Turkey

NASA Astrophysics Data System (ADS)

Denli, H. H.; Koc, Z.

2015-12-01

Estimation of real properties depending on standards is difficult to apply in time and location. Regression analysis construct mathematical models which describe or explain relationships that may exist between variables. The problem of identifying price differences of properties to obtain a price index can be converted into a regression problem, and standard techniques of regression analysis can be used to estimate the index. Considering regression analysis for real estate valuation, which are presented in real marketing process with its current characteristics and quantifiers, the method will help us to find the effective factors or variables in the formation of the value. In this study, prices of housing for sale in Zeytinburnu, a district in Istanbul, are associated with its characteristics to find a price index, based on information received from a real estate web page. The associated variables used for the analysis are age, size in m2, number of floors having the house, floor number of the estate and number of rooms. The price of the estate represents the dependent variable, whereas the rest are independent variables. Prices from 60 real estates have been used for the analysis. Same price valued locations have been found and plotted on the map and equivalence curves have been drawn identifying the same valued zones as lines.

Performance in grade 12 mathematics and science predicts student nurses' performance in first year science modules at a university in the Western Cape.

PubMed

Mthimunye, Katlego D T; Daniels, Felicity M

2017-10-26

The demand for highly qualified and skilled nurses is increasing in South Africa as well as around the world. Having a background in science can create a significant advantage for students wishing to enrol for an undergraduate nursing qualification because nursing as profession is grounded in scientific evidence. The aim of this study was to investigate the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. A quantitative research method using a cross-sectional predictive design was employed in this study. The participants included first year Bachelor of Nursing students enrolled at a university in the Western Cape, South Africa. Descriptive and inferential statistics were performed to analyse the data by using the IBM Statistical Package for Social Sciences versions 24. Descriptive analysis of all variables was performed as well as the Spearman's rank correlation test to describe the relationship among the study variables. Standard multiple linear regressions analysis was performed to determine the predictive validity of grade 12 mathematics and science on the academic performance of first year student nurses in science modules. The results of this study showed that grade 12 physical science is not a significant predictor (p > 0.062) of performance in first year science modules. The multiple linear regression revealed that grade 12 mathematics and life science grades explained 37.1% to 38.1% (R2 = 0.381 and adj R2 = 0.371) of the variation in the first year science grade distributions. Based on the results of the study it is evident that performance in grade 12 mathematics (β = 2.997) and life science (β = 3.175) subjects is a significant predictor (p < 0.001) of the performance in first year science modules for student nurses at the university identified for this study.

Analysis of cost regression and post-accident absence

NASA Astrophysics Data System (ADS)

Wojciech, Drozd

2017-07-01

The article presents issues related with costs of work safety. It proves the thesis that economic aspects cannot be overlooked in effective management of occupational health and safety and that adequate expenditures on safety can bring tangible benefits to the company. Reliable analysis of this problem is essential for the description the problem of safety the work. In the article attempts to carry it out using the procedures of mathematical statistics [1, 2, 3].

Evaluating the Effectiveness of Developmental Mathematics by Embedding a Randomized Experiment within a Regression Discontinuity Design

ERIC Educational Resources Information Center

Moss, Brian G.; Yeaton, William H.; Lloyd, Jane E.

2014-01-01

Using a novel design approach, a randomized experiment (RE) was embedded within a regression discontinuity (RD) design (R-RE-D) to evaluate the impact of developmental mathematics at a large midwestern college ("n" = 2,122). Within a region of uncertainty near the cut-score, estimates of benefit from a prospective RE were closely…

Addressing the identification problem in age-period-cohort analysis: a tutorial on the use of partial least squares and principal components analysis.

PubMed

Tu, Yu-Kang; Krämer, Nicole; Lee, Wen-Chung

2012-07-01

In the analysis of trends in health outcomes, an ongoing issue is how to separate and estimate the effects of age, period, and cohort. As these 3 variables are perfectly collinear by definition, regression coefficients in a general linear model are not unique. In this tutorial, we review why identification is a problem, and how this problem may be tackled using partial least squares and principal components regression analyses. Both methods produce regression coefficients that fulfill the same collinearity constraint as the variables age, period, and cohort. We show that, because the constraint imposed by partial least squares and principal components regression is inherent in the mathematical relation among the 3 variables, this leads to more interpretable results. We use one dataset from a Taiwanese health-screening program to illustrate how to use partial least squares regression to analyze the trends in body heights with 3 continuous variables for age, period, and cohort. We then use another dataset of hepatocellular carcinoma mortality rates for Taiwanese men to illustrate how to use partial least squares regression to analyze tables with aggregated data. We use the second dataset to show the relation between the intrinsic estimator, a recently proposed method for the age-period-cohort analysis, and partial least squares regression. We also show that the inclusion of all indicator variables provides a more consistent approach. R code for our analyses is provided in the eAppendix.

Attitudes toward and approaches to learning first-year university mathematics.

PubMed

Alkhateeb, Haitham M; Hammoudi, Lakhdar

2006-08-01

This study examined the relationship for 180 undergraduate students enrolled in a first-year university calculus course between attitudes toward mathematics and approaches to learning mathematics using the Mathematics Attitude Scale and the Approaches to Learning Mathematics Questionnaire, respectively. Regression analyses indicated that scores for the Mathematics Attitude Scale were negatively related to scores for the Surface Approach and accounted for 10.4% of the variance and scores for the Mathematics Attitude Scale were positively related to scores for the Deep Approach to learning mathematics and accounted for 31.7% of the variance.

Intrafirm planning and mathematical modeling of owner's equity in industrial enterprises

NASA Astrophysics Data System (ADS)

Ponomareva, S. V.; Zheleznova, I. V.

2018-05-01

The article aims to review the different approaches to intrafirm planning of owner's equity in industrial enterprises. Since charter capital, additional capital and reserve capital do not change in the process of enterprise activity, the main interest lies on the field of share repurchases from shareholders and retained earnings within the owner's equity of the enterprise. In order to study the effect of share repurchases on the activities of the enterprise, let us use such mathematical methods as event study and econometric modeling. This article describes the step-by-step algorithm of carrying out event study and justifies the choice of Logit model in econometric analysis. The article represents basic results of conducted regression analysis on the effect of share repurchases on the key financial indicators in industrial enterprises.

[Benefits of Measures to Promote Development in Language, Mathematics and Singing in Kindergardeners: Analysis of Data Collected at School Entrance Examination in the County of Biberach].

PubMed

Hart, Ulrike; Wildner, Manfred; Krämer, Daniela; Crispin, Alexander

2018-02-01

To evaluate the benefits of implementing measures to promote skills in the areas of language, mathematics and singing in kindergardeners by statistical analysis of data collected during the school entrance examination (ESU) of 4-5-year-old children from the county of Biberach. Study 1 employs multivariate regression analysis to analyse - in chronological order - the ESU data on 4 cohorts (2011-2014; n=7 148) of children of the Biberach county. Study 2 qualitatively compares identical data representative of the entire state of Baden-Württemberg (N=3×80 000) with the Biberach results. Study 3 focuses on the cohort 2014 in Biberach county (n=1 783) and employs logistical regression techniques to correlate curriculum content and child development. There are significant performance improvements in the Biberach population (2011-2014) in the development of language and early mathematics, as well as in visual comprehension and visuomotor skills, but not in the area of gross motor skills. Similar improvements are much more difficult to demonstrate for the entire state of Baden-Württemberg. The detailed analysis of the 2014 Biberach County data reveal that kindergardeners with increased exposure to mathematics will have a decreased risk of failure in early mathematics (OR 0.72) and grammar skills (OR 0.53-0.75). Children with speech impairment or children not fluent in German that had extra language tutorials, typically in small groups and 4 times a week for 30 min, still have a higher risk of failure in all developmental aspects, save gross motor skills (e. g. OR 3.32 in grammar skills, OR 3.08 for hyperactivity). Programs with emphasis on singing have little effect on the above data. The risk of failure in German language is high (OR 2.78) for those of non-German backgrounds, but less in visuomotor skills (OR 0.52) and hyperactivity (OR 0.51). Statistical analyses show positive correlation of curriculum content and early child development for the kindergardens in Biberach county. The gains in performance are consistent with those reported from kindergardens known for pedagogical excellence. © Georg Thieme Verlag KG Stuttgart · New York.

Exploring the Associations Among Nutrition, Science, and Mathematics Knowledge for an Integrative, Food-Based Curriculum.

PubMed

Stage, Virginia C; Kolasa, Kathryn M; Díaz, Sebastián R; Duffrin, Melani W

2018-01-01

Explore associations between nutrition, science, and mathematics knowledge to provide evidence that integrating food/nutrition education in the fourth-grade curriculum may support gains in academic knowledge. Secondary analysis of a quasi-experimental study. Sample included 438 students in 34 fourth-grade classrooms across North Carolina and Ohio; mean age 10 years old; gender (I = 53.2% female; C = 51.6% female). Dependent variable = post-test-nutrition knowledge; independent variables = baseline-nutrition knowledge, and post-test science and mathematics knowledge. Analyses included descriptive statistics and multiple linear regression. The hypothesized model predicted post-nutrition knowledge (F(437) = 149.4, p < .001; Adjusted R = .51). All independent variables were significant predictors with positive association. Science and mathematics knowledge were predictive of nutrition knowledge indicating use of an integrative science and mathematics curriculum to improve academic knowledge may also simultaneously improve nutrition knowledge among fourth-grade students. Teachers can benefit from integration by meeting multiple academic standards, efficiently using limited classroom time, and increasing nutrition education provided in the classroom. © 2018, American School Health Association.

Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

NASA Astrophysics Data System (ADS)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

Using Neural Network and Logistic Regression Analysis to Predict Prospective Mathematics Teachers' Academic Success upon Entering Graduate Education

ERIC Educational Resources Information Center

Bahadir, Elif

2016-01-01

The ability to predict the success of students when they enter a graduate program is critical for educational institutions because it allows them to develop strategic programs that will help improve students' performances during their stay at an institution. In this study, we present the results of an experimental comparison study of Logistic…

Investigation of noise in gear transmissions by the method of mathematical smoothing of experiments

NASA Technical Reports Server (NTRS)

Sheftel, B. T.; Lipskiy, G. K.; Ananov, P. P.; Chernenko, I. K.

1973-01-01

A rotatable central component smoothing method is used to analyze rotating gear noise spectra. A matrix is formulated in which the randomized rows correspond to various tests and the columns to factor values. Canonical analysis of the obtained regression equation permits the calculation of optimal speed and load at a previous assigned noise level.

Determination of suitable drying curve model for bread moisture loss during baking

NASA Astrophysics Data System (ADS)

Soleimani Pour-Damanab, A. R.; Jafary, A.; Rafiee, S.

2013-03-01

This study presents mathematical modelling of bread moisture loss or drying during baking in a conventional bread baking process. In order to estimate and select the appropriate moisture loss curve equation, 11 different models, semi-theoretical and empirical, were applied to the experimental data and compared according to their correlation coefficients, chi-squared test and root mean square error which were predicted by nonlinear regression analysis. Consequently, of all the drying models, a Page model was selected as the best one, according to the correlation coefficients, chi-squared test, and root mean square error values and its simplicity. Mean absolute estimation error of the proposed model by linear regression analysis for natural and forced convection modes was 2.43, 4.74%, respectively.

Measuring and factors influencing mathematics teachers' technological pedagogical and content knowledge (TPACK) in three southernmost provinces, Thailand

NASA Astrophysics Data System (ADS)

Adulyasas, Lilla

2017-08-01

Technology becomes an important role in teaching and learning mathematics nowadays. Integrating technology in the classroom helps students have better understanding in many of mathematics concepts. One of the major framework for assessing the knowledge of integrating technology with the pedagogy and content in the classroom is Technological Pedagogical and Content Knowledge (TPACK) framework. This study aimed to measure mathematics teachers' TPACK in three southernmost provinces, Thailand and to study on factors influencing their TPACK. A quantitative study was carried out with 210 secondary level mathematics teachers in the three southernmost provinces, Thailand which were random by two stage sampling technique. Data were collected by using a questionnaire to identify the level of mathematics teachers' TPACK and the factors influencing their TPACK. Descriptive statistics, Pearson product moment correlation and multiple regression analysis were used for analysing data. Findings reveal that the mean score of mathematics teachers' TPACK is 3.33 which is in the medium level and the three factors which have positive correlation at .05 level of significant with the level of TPACK are teaching experience factor, individual specialization factor and personal & organization factor. However, there are only two factors influencing mathematics teachers' TPACK. The two factors are individual specialization factor and personal & organization factors. These give better understanding on mathematics teachers' knowledge in integrating technology with the pedagogy and content which will be the important information for improving mathematics teachers' TPACK.

Stretch-dependent changes in surface profiles of the human crystalline lens during accommodation: a finite element study.

PubMed

Pour, Hooman Mohammad; Kanapathipillai, Sangarapillai; Zarrabi, Khosrow; Manns, Fabrice; Ho, Arthur

2015-03-01

A non-linear isotropic finite element (FE) model of a 29-year-old human crystalline lens was constructed to study the effects of various geometrical parameters on lens accommodation. The model simulates dis-accommodation by stretching of the lens and predicts the change in surface profiles of the lens capsule, cortex and nucleus at select states of stretching/accommodation. Multiple regression analysis (MRA) is used to develop a stretch-dependent mathematical model relating the lens sagittal height to the radial position of the lens surface as a function of dis-accommodative stretch. A load analysis is performed to compare the finite element results to empirical results from lens stretcher studies. Using the predicted geometrical changes, the optical response of the whole eye during accommodation was analysed by ray-tracing. Aspects of lens shape change relative to stretch were evaluated, including change in diameter, central thickness and accommodation. Maximum accommodation achieved was 10.29 D. From the multiple regression analysis, the stretch-dependent mathematical model of the lens shape related lens curvatures as a function of lens ciliary stretch well (maximum mean-square residual error 2.5 × 10(-3 ) μm, p < 0.001). The results are compared with those from in vitro studies. The finite element and ray-tracing predictions are consistent with Ex Vivo Accommodation Simulator (EVAS) studies in terms of load and power change versus change in thickness. The mathematical stretch-dependent model of accommodation presented may have utility in investigating lens behaviour at states other than the relaxed or fully accommodated states. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

Cognitive and attitudinal predictors related to graphing achievement among pre-service elementary teachers

NASA Astrophysics Data System (ADS)

Szyjka, Sebastian P.

The purpose of this study was to determine the extent to which six cognitive and attitudinal variables predicted pre-service elementary teachers' performance on line graphing. Predictors included Illinois teacher education basic skills sub-component scores in reading comprehension and mathematics, logical thinking performance scores, as well as measures of attitudes toward science, mathematics and graphing. This study also determined the strength of the relationship between each prospective predictor variable and the line graphing performance variable, as well as the extent to which measures of attitude towards science, mathematics and graphing mediated relationships between scores on mathematics, reading, logical thinking and line graphing. Ninety-four pre-service elementary education teachers enrolled in two different elementary science methods courses during the spring 2009 semester at Southern Illinois University Carbondale participated in this study. Each subject completed five different instruments designed to assess science, mathematics and graphing attitudes as well as logical thinking and graphing ability. Sixty subjects provided copies of primary basic skills score reports that listed subset scores for both reading comprehension and mathematics. The remaining scores were supplied by a faculty member who had access to a database from which the scores were drawn. Seven subjects, whose scores could not be found, were eliminated from final data analysis. Confirmatory factor analysis (CFA) was conducted in order to establish validity and reliability of the Questionnaire of Attitude Toward Line Graphs in Science (QALGS) instrument. CFA tested the statistical hypothesis that the five main factor structures within the Questionnaire of Attitude Toward Statistical Graphs (QASG) would be maintained in the revised QALGS. Stepwise Regression Analysis with backward elimination was conducted in order to generate a parsimonious and precise predictive model. This procedure allowed the researcher to explore the relationships among the affective and cognitive variables that were included in the regression analysis. The results for CFA indicated that the revised QALGS measure was sound in its psychometric properties when tested against the QASG. Reliability statistics indicated that the overall reliability for the 32 items in the QALGS was .90. The learning preferences construct had the lowest reliability (.67), while enjoyment (.89), confidence (.86) and usefulness (.77) constructs had moderate to high reliabilities. The first four measurement models fit the data well as indicated by the appropriate descriptive and statistical indices. However, the fifth measurement model did not fit the data well statistically, and only fit well with two descriptive indices. The results addressing the research question indicated that mathematical and logical thinking ability were significant predictors of line graph performance among the remaining group of variables. These predictors accounted for 41% of the total variability on the line graph performance variable. Partial correlation coefficients indicated that mathematics ability accounted for 20.5% of the variance on the line graphing performance variable when removing the effect of logical thinking. The logical thinking variable accounted for 4.7% of the variance on the line graphing performance variable when removing the effect of mathematics ability.

Profiling Student Use of Calculators in the Learning of High School Mathematics

ERIC Educational Resources Information Center

Crowe, Cheryll E.; Ma, Xin

2010-01-01

Using data from the 2005 National Assessment of Educational Progress, students' use of calculators in the learning of high school mathematics was profiled based on their family background, curriculum background, and advanced mathematics coursework. A statistical method new to educational research--classification and regression trees--was applied…

Replica analysis of overfitting in regression models for time-to-event data

NASA Astrophysics Data System (ADS)

Coolen, A. C. C.; Barrett, J. E.; Paga, P.; Perez-Vicente, C. J.

2017-09-01

Overfitting, which happens when the number of parameters in a model is too large compared to the number of data points available for determining these parameters, is a serious and growing problem in survival analysis. While modern medicine presents us with data of unprecedented dimensionality, these data cannot yet be used effectively for clinical outcome prediction. Standard error measures in maximum likelihood regression, such as p-values and z-scores, are blind to overfitting, and even for Cox’s proportional hazards model (the main tool of medical statisticians), one finds in literature only rules of thumb on the number of samples required to avoid overfitting. In this paper we present a mathematical theory of overfitting in regression models for time-to-event data, which aims to increase our quantitative understanding of the problem and provide practical tools with which to correct regression outcomes for the impact of overfitting. It is based on the replica method, a statistical mechanical technique for the analysis of heterogeneous many-variable systems that has been used successfully for several decades in physics, biology, and computer science, but not yet in medical statistics. We develop the theory initially for arbitrary regression models for time-to-event data, and verify its predictions in detail for the popular Cox model.

Public and Private School Distinction, Regional Development Differences, and Other Factors Influencing the Success of Primary School Students in Turkey

ERIC Educational Resources Information Center

Sulku, Seher Nur; Abdioglu, Zehra

2015-01-01

This study investigates the factors influencing the success of students in primary schools in Turkey. TIMSS 2011 data for Turkey, measuring the success of eighth-grade students in the field of mathematics, were used in an econometric analysis, performed using classical linear regression models. Two hundred thirty-nine schools participated in the…

A Regression Analysis of Elementary Students' ICT Usage vis-à-vis Access to Technology in Singapore

ERIC Educational Resources Information Center

Tay, Lee Yong; Nair, Shanthi Suraj; Lim, Cher Ping

2017-01-01

This paper explores the relationship among ICT infrastructure (i.e., computing devices and Internet), one-to-one computing program and student ICT activities in school. It also looks into the differences of how ICT is being used in the teaching of English, mathematics and science at the elementary school level in relation to the availability of…

Chickpea seeds germination rational parameters optimization

NASA Astrophysics Data System (ADS)

Safonova, Yu A.; Ivliev, M. N.; Lemeshkin, A. V.

2018-05-01

The paper presents the influence of chickpea seeds bioactivation parameters on their enzymatic activity experimental results. Optimal bioactivation process modes were obtained by regression-factor analysis: process temperature - 13.6 °C, process duration - 71.5 h. It was found that in the germination process, the proteolytic, amylolytic and lipolytic enzymes activity increased, and the urease enzyme activity is reduced. The dependences of enzyme activity on chickpea seeds germination conditions were obtained by mathematical processing of experimental data. The calculated data are in good agreement with the experimental ones. This confirms the optimization efficiency based on experiments mathematical planning in order to determine the enzymatic activity of chickpea seeds germination optimal parameters of bioactivated seeds.

Latent transition analysis of pre-service teachers' efficacy in mathematics and science

NASA Astrophysics Data System (ADS)

Ward, Elizabeth Kennedy

This study modeled changes in pre-service teacher efficacy in mathematics and science over the course of the final year of teacher preparation using latent transition analysis (LTA), a longitudinal form of analysis that builds on two modeling traditions (latent class analysis (LCA) and auto-regressive modeling). Data were collected using the STEBI-B, MTEBI-r, and the ABNTMS instruments. The findings suggest that LTA is a viable technique for use in teacher efficacy research. Teacher efficacy is modeled as a construct with two dimensions: personal teaching efficacy (PTE) and outcome expectancy (OE). Findings suggest that the mathematics and science teaching efficacy (PTE) of pre-service teachers is a multi-class phenomena. The analyses revealed a four-class model of PTE at the beginning and end of the final year of teacher training. Results indicate that when pre-service teachers transition between classes, they tend to move from a lower efficacy class into a higher efficacy class. In addition, the findings suggest that time-varying variables (attitudes and beliefs) and time-invariant variables (previous coursework, previous experiences, and teacher perceptions) are statistically significant predictors of efficacy class membership. Further, analyses suggest that the measures used to assess outcome expectancy are not suitable for LCA and LTA procedures.

Modeling and Analysis of Process Parameters for Evaluating Shrinkage Problems During Plastic Injection Molding of a DVD-ROM Cover

NASA Astrophysics Data System (ADS)

Öktem, H.

2012-01-01

Plastic injection molding plays a key role in the production of high-quality plastic parts. Shrinkage is one of the most significant problems of a plastic part in terms of quality in the plastic injection molding. This article focuses on the study of the modeling and analysis of the effects of process parameters on the shrinkage by evaluating the quality of the plastic part of a DVD-ROM cover made with Acrylonitrile Butadiene Styrene (ABS) polymer material. An effective regression model was developed to determine the mathematical relationship between the process parameters (mold temperature, melt temperature, injection pressure, injection time, and cooling time) and the volumetric shrinkage by utilizing the analysis data. Finite element (FE) analyses designed by Taguchi (L27) orthogonal arrays were run in the Moldflow simulation program. Analysis of variance (ANOVA) was then performed to check the adequacy of the regression model and to determine the effect of the process parameters on the shrinkage. Experiments were conducted to control the accuracy of the regression model with the FE analyses obtained from Moldflow. The results show that the regression model agrees very well with the FE analyses and the experiments. From this, it can be concluded that this study succeeded in modeling the shrinkage problem in our application.

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

NASA Technical Reports Server (NTRS)

Feiveson, Alan; Glenn, Nancy L.

2013-01-01

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

Predictors of Success in Accelerated and Enrichment Summer Mathematics Courses for Academically Talented Adolescents

ERIC Educational Resources Information Center

Young, Adena E.; Worrell, Frank C.; Gabelko, Nina H.

2011-01-01

In this study, we used logistic regression to examine how well student background and prior achievement variables predicted success among students attending accelerated and enrichment mathematics courses at a summer program (N = 459). Socioeconomic status, grade point average (GPA), and mathematics diagnostic test scores significantly predicted…

Cognitive components of a mathematical processing network in 9-year-old children.

PubMed

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-07-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular 'number sense'. We suggest an 'executive memory function centric' model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors.

Cognitive components of a mathematical processing network in 9-year-old children

PubMed Central

Szűcs, Dénes; Devine, Amy; Soltesz, Fruzsina; Nobes, Alison; Gabriel, Florence

2014-01-01

We determined how various cognitive abilities, including several measures of a proposed domain-specific number sense, relate to mathematical competence in nearly 100 9-year-old children with normal reading skill. Results are consistent with an extended number processing network and suggest that important processing nodes of this network are phonological processing, verbal knowledge, visuo-spatial short-term and working memory, spatial ability and general executive functioning. The model was highly specific to predicting arithmetic performance. There were no strong relations between mathematical achievement and verbal short-term and working memory, sustained attention, response inhibition, finger knowledge and symbolic number comparison performance. Non-verbal intelligence measures were also non-significant predictors when added to our model. Number sense variables were non-significant predictors in the model and they were also non-significant predictors when entered into regression analysis with only a single visuo-spatial WM measure. Number sense variables were predicted by sustained attention. Results support a network theory of mathematical competence in primary school children and falsify the importance of a proposed modular ‘number sense’. We suggest an ‘executive memory function centric’ model of mathematical processing. Mapping a complex processing network requires that studies consider the complex predictor space of mathematics rather than just focusing on a single or a few explanatory factors. PMID:25089322

Fast and simultaneously determination of light and heavy rare earth elements in monazite using combination of ultraviolet-visible spectrophotometry and multivariate analysis

NASA Astrophysics Data System (ADS)

Anggraeni, Anni; Arianto, Fernando; Mutalib, Abdul; Pratomo, Uji; Bahti, Husein H.

2017-05-01

Rare Earth Elements (REE) are elements that a lot of function for life, such as metallurgy, optical devices, and manufacture of electronic devices. Sources of REE is present in the mineral, in which each element has similar properties. Currently, to determining the content of REE is used instruments such as ICP-OES, ICP-MS, XRF, and HPLC. But in each instruments, there are still have some weaknesses. Therefore we need an alternative analytical method for the determination of rare earth metal content, one of them is by a combination of UV-Visible spectrophotometry and multivariate analysis, including Principal Component Analysis (PCA), Principal Component Regression (PCR), and Partial Least Square Regression (PLS). The purpose of this experiment is to determine the content of light and medium rare earth elements in the mineral monazite without chemical separation by using a combination of multivariate analysis and UV-Visible spectrophotometric methods. Training set created 22 variations of concentration and absorbance was measured using a UV-Vis spectrophotometer, then the data is processed by PCA, PCR, and PLSR. The results were compared and validated to obtain the mathematical equation with the smallest percent error. From this experiment, mathematical equation used PLS methods was better than PCR after validated, which has RMSE value for La, Ce, Pr, Nd, Gd, Sm, Eu, and Tb respectively 0.095; 0.573; 0.538; 0.440; 3.387; 1.240; 1.870; and 0.639.

Child development at 5 years of age predicted mathematics ability and schooling outcomes in Malawian adolescents.

PubMed

Gandhi, Mihir; Teivaanmaki, Tiina; Maleta, Kenneth; Duan, Xiaolian; Ashorn, Per; Cheung, Yin Bun

2013-01-01

This study aimed to examine the association between child development at 5 years of age and mathematics ability and schooling outcomes at 12 years of age in Malawian children. A prospective cohort study looking at 609 rural Malawian children. Outcome measures were percentage of correctly answered mathematics questions, highest school grade completed and number of times repeating school grades at 12 years of age. A child development summary score obtained at 5 years of age was the main exposure variable. Regression analyses were used to estimate the association and adjust for confounders. Sensitivity analysis was performed by handling losses to follow-up with multiple imputation (MI) method. The summary score was positively associated with percentage of correctly answered mathematics questions (p = 0.057; p = 0.031 MI) and with highest school grade completed (p = 0.096; p = 0.070 MI), and negatively associated with number of times repeating school grades (p = 0.834; p = 0.339 MI). Fine motor score at 5 years was independently associated with the mathematic score (p = 0.032; p = 0.011 MI). The association between child development and mathematics ability did not depend on school attendance. Child development at 5 years of age showed signs of positive association with mathematics ability and possibly with highest school grade completed at 12 years of age. © 2012 The Author(s)/Acta Paediatrica © 2012 Foundation Acta Paediatrica.

General Mathematical Ability Predicts PASAT Performance in MS Patients: Implications for Clinical Interpretation and Cognitive Reserve.

PubMed

Sandry, Joshua; Paxton, Jessica; Sumowski, James F

2016-03-01

The Paced Auditory Serial Addition Test (PASAT) is used to assess cognitive status in multiple sclerosis (MS). Although the mathematical demands of the PASAT seem minor (single-digit arithmetic), cognitive psychology research links greater mathematical ability (e.g., algebra, calculus) to more rapid retrieval of single-digit math facts (e.g., 5+6=11). The present study evaluated the hypotheses that (a) mathematical ability is related to PASAT performance and (b) both the relationship between intelligence and PASAT performance as well as the relationship between education and PASAT performance are both mediated by mathematical ability. Forty-five MS patients were assessed using the Wechsler Test of Adult Reading, PASAT and Calculation Subtest of the Woodcock-Johnson-III. Regression based path analysis and bootstrapping were used to compute 95% confidence intervals and test for mediation. Mathematical ability (a) was related to PASAT (β=.61; p<.001) and (b) fully mediated the relationship between Intelligence and PASAT (β=.76; 95% confidence interval (CI95)=.28, 1.45; direct effect of Intelligence, β=.42; CI95=-.39, 1.23) as well as the relationship between Education and PASAT (β=2.43, CI95=.81, 5.16, direct effect of Education, β=.83, CI95=-1.95, 3.61). Mathematical ability represents a source of error in the clinical interpretation of cognitive decline using the PASAT. Domain-specific cognitive reserve is discussed.

Orthogonal Projection in Teaching Regression and Financial Mathematics

ERIC Educational Resources Information Center

Kachapova, Farida; Kachapov, Ilias

2010-01-01

Two improvements in teaching linear regression are suggested. The first is to include the population regression model at the beginning of the topic. The second is to use a geometric approach: to interpret the regression estimate as an orthogonal projection and the estimation error as the distance (which is minimized by the projection). Linear…

Categorical regression dose-response modeling

EPA Science Inventory

The goal of this training is to provide participants with training on the use of the U.S. EPA’s Categorical Regression soft¬ware (CatReg) and its application to risk assessment. Categorical regression fits mathematical models to toxicity data that have been assigned ord...

A Model Comparison for Count Data with a Positively Skewed Distribution with an Application to the Number of University Mathematics Courses Completed

ERIC Educational Resources Information Center

Liou, Pey-Yan

2009-01-01

The current study examines three regression models: OLS (ordinary least square) linear regression, Poisson regression, and negative binomial regression for analyzing count data. Simulation results show that the OLS regression model performed better than the others, since it did not produce more false statistically significant relationships than…

[From clinical judgment to linear regression model.

PubMed

Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

2013-01-01

When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

Exploring Crossing Differential Item Functioning by Gender in Mathematics Assessment

ERIC Educational Resources Information Center

Ong, Yoke Mooi; Williams, Julian; Lamprianou, Iasonas

2015-01-01

The purpose of this article is to explore crossing differential item functioning (DIF) in a test drawn from a national examination of mathematics for 11-year-old pupils in England. An empirical dataset was analyzed to explore DIF by gender in a mathematics assessment. A two-step process involving the logistic regression (LR) procedure for…

Incorporating Learning Motivation and Self-Concept in Mathematical Communicative Ability

ERIC Educational Resources Information Center

Rajagukguk, Waminton

2016-01-01

This research is trying to determine of the mathematical concepts, instead by integrating the learning motivation (X[subscript 1]) and self-concept (X[subscript 2]) can contribute to the mathematical communicative ability (Y). The test instruments showed the following results: (1) simple regressive equation Y on X[subscript 1] was Y = 32.891 +…

Predicting Student Success in a Major's Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores

ERIC Educational Resources Information Center

Thompson, E. David; Bowling, Bethany V.; Markle, Ross E.

2018-01-01

Studies over the last 30 years have considered various factors related to student success in introductory biology courses. While much of the available literature suggests that the best predictors of success in a college course are prior college grade point average (GPA) and class attendance, faculty often require a valuable predictor of success in…

Distributed collaborative probabilistic design for turbine blade-tip radial running clearance using support vector machine of regression

NASA Astrophysics Data System (ADS)

Fei, Cheng-Wei; Bai, Guang-Chen

2014-12-01

To improve the computational precision and efficiency of probabilistic design for mechanical dynamic assembly like the blade-tip radial running clearance (BTRRC) of gas turbine, a distribution collaborative probabilistic design method-based support vector machine of regression (SR)(called as DCSRM) is proposed by integrating distribution collaborative response surface method and support vector machine regression model. The mathematical model of DCSRM is established and the probabilistic design idea of DCSRM is introduced. The dynamic assembly probabilistic design of aeroengine high-pressure turbine (HPT) BTRRC is accomplished to verify the proposed DCSRM. The analysis results reveal that the optimal static blade-tip clearance of HPT is gained for designing BTRRC, and improving the performance and reliability of aeroengine. The comparison of methods shows that the DCSRM has high computational accuracy and high computational efficiency in BTRRC probabilistic analysis. The present research offers an effective way for the reliability design of mechanical dynamic assembly and enriches mechanical reliability theory and method.

Development of multiple regression analysis instruments to predict success in advanced placement chemistry

NASA Astrophysics Data System (ADS)

Wagner, Kurt Collins

2001-10-01

This research asks the fundamental question: "What is the profile of the successful AP chemistry student?" Two populations of students are studied. The first population is comprised of students who attend or attended the South Carolina Governor's School for Science and Mathematics, a specialized high school for high ability students, and who have taken the Advanced Placement (AP) chemistry examination in the past five years. The second population is comprised of the 581 South Carolina public school students at 46 high schools who took the AP chemistry examination in 2000. The first part of the study is intended to be useful in recruitment and placement decisions for schools in the National Consortium for Specialized Secondary Schools of Mathematics, Science and Technology. The second part of the study is intended to facilitate AP chemistry recruitment in South Carolina public schools. The first part of the study was conducted by ex post facto searches of teacher and school records at the South Carolina Governor's School for Science and Mathematics. The second part of the study was conducted by obtaining school participation information from the SC Department of Education and soliciting data from the public schools. Data were collected from 440 of 581 (75.7%) of students in 35 of 46 (76.1%) of schools. Intercorrelational and Multiple Regression Analyses (MRA) have yielded different results for these two populations. For the specialized school population, the significant predictors for success in AP chemistry are PSAT Math, placement test, and PSAT Writing. For the population of SC students, significant predictors for success are PSAT Math, count of prior science courses, and PSAT Writing. Multiple Regressions have been successfully developed for the two populations studied. Recommendations for their application are made.

Mathematical literacy in undergraduates: role of gender, emotional intelligence and emotional self-efficacy

NASA Astrophysics Data System (ADS)

Tariq, Vicki N.; Qualter, Pamela; Roberts, Sian; Appleby, Yvon; Barnes, Lynne

2013-12-01

This empirical study explores the roles that Emotional Intelligence (EI) and Emotional Self-Efficacy (ESE) play in undergraduates' mathematical literacy, and the influence of EI and ESE on students' attitudes towards and beliefs about mathematics. A convenience sample of 93 female and 82 male first-year undergraduates completed a test of mathematical literacy, followed by an online survey designed to measure the students' EI, ESE and factors associated with mathematical literacy. Analysis of the data revealed significant gender differences. Males attained a higher mean test score than females and out-performed the females on most of the individual questions and the associated mathematical tasks. Overall, males expressed greater confidence in their mathematical skills, although both males' and females' confidence outweighed their actual mathematical proficiency. Correlation analyses revealed that males and females attaining higher mathematical literacy test scores were more confident and persistent, exhibited lower levels of mathematics anxiety and possessed higher mathematics qualifications. Correlation analyses also revealed that in male students, aspects of ESE were associated with beliefs concerning the learning of mathematics (i.e. that intelligence is malleable and that persistence can facilitate success), but not with confidence or actual performance. Both EI and ESE play a greater role with regard to test performance and attitudes/beliefs regarding mathematics amongst female undergraduates; higher EI and ESE scores were associated with higher test scores, while females exhibiting higher levels of ESE were also more confident and less anxious about mathematics, believed intelligence to be malleable, were more persistent and were learning goal oriented. Moderated regression analyses confirmed mathematics anxiety as a negative predictor of test performance in males and females, but also revealed that in females EI and ESE moderate the effects of anxiety on test performance, with the relationship between anxiety and test performance linked more to emotional management (EI) than to ESE.

Multivariate analysis of fMRI time series: classification and regression of brain responses using machine learning.

PubMed

Formisano, Elia; De Martino, Federico; Valente, Giancarlo

2008-09-01

Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the full spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In typical fMRI applications, pattern recognition algorithms "learn" a functional relationship between brain response patterns and a perceptual, cognitive or behavioral state of a subject expressed in terms of a label, which may assume discrete (classification) or continuous (regression) values. This learned functional relationship is then used to predict the unseen labels from a new data set ("brain reading"). In this article, we describe the mathematical foundations of machine learning applications in fMRI. We focus on two methods, support vector machines and relevance vector machines, which are respectively suited for the classification and regression of fMRI patterns. Furthermore, by means of several examples and applications, we illustrate and discuss the methodological challenges of using machine learning algorithms in the context of fMRI data analysis.

The Association between Working Memory and Educational Attainment as Measured in Different Mathematical Subtopics in the Swedish National Assessment: Primary Education

ERIC Educational Resources Information Center

Nyroos, Mikaela; Wiklund-Hornqvist, Carola

2012-01-01

The aim of this study was to examine the relationship between working memory capacity and mathematical performance measured by the national curriculum assessment in third-grade children (n = 40). The national tests concerned six subareas within mathematics. One-way ANOVA, two-tailed Pearson correlation and multiple regression analyses were…

Examining spectral properties of Landsat 8 OLI for predicting above-ground carbon of Labanan Forest, Berau

NASA Astrophysics Data System (ADS)

Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.

2018-04-01

Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression.

PubMed

Beckstead, Jason W

2012-03-30

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic strategy to isolate, examine, and remove suppression effects has been offered. In this article such an approach, rooted in confirmatory factor analysis theory and employing matrix algebra, is developed. Suppression is viewed as the result of criterion-irrelevant variance operating among predictors. Decomposition of predictor variables into criterion-relevant and criterion-irrelevant components using structural equation modeling permits derivation of regression weights with the effects of criterion-irrelevant variance omitted. Three examples with data from applied research are used to illustrate the approach: the first assesses child and parent characteristics to explain why some parents of children with obsessive-compulsive disorder accommodate their child's compulsions more so than do others, the second examines various dimensions of personal health to explain individual differences in global quality of life among patients following heart surgery, and the third deals with quantifying the relative importance of various aptitudes for explaining academic performance in a sample of nursing students. The approach is offered as an analytic tool for investigators interested in understanding predictor-criterion relationships when complex patterns of intercorrelation among predictors are present and is shown to augment dominance analysis.

A structural equation modeling of executive functions, IQ and mathematical skills in primary students: Differential effects on number production, mental calculus and arithmetical problems.

PubMed

Arán Filippetti, Vanessa; Richaud, María Cristina

2017-10-01

Though the relationship between executive functions (EFs) and mathematical skills has been well documented, little is known about how both EFs and IQ differentially support diverse math domains in primary students. Inconsistency of results may be due to the statistical techniques employed, specifically, if the analysis is conducted with observed variables, i.e., regression analysis, or at the latent level, i.e., structural equation modeling (SEM). The current study explores the contribution of both EFs and IQ in mathematics through an SEM approach. A total of 118 8- to 12-year-olds were administered measures of EFs, crystallized (Gc) and fluid (Gf) intelligence, and math abilities (i.e., number production, mental calculus and arithmetical problem-solving). Confirmatory factor analysis (CFA) offered support for the three-factor solution of EFs: (1) working memory (WM), (2) shifting, and (3) inhibition. Regarding the relationship among EFs, IQ and math abilities, the results of the SEM analysis showed that (i) WM and age predict number production and mental calculus, and (ii) shifting and sex predict arithmetical problem-solving. In all of the SEM models, EFs partially or totally mediated the relationship between IQ, age and math achievement. These results suggest that EFs differentially supports math abilities in primary-school children and is a more significant predictor of math achievement than IQ level.

Regression Analysis as a Cost Estimation Model for Unexploded Ordnance Cleanup at Former Military Installations

DTIC Science & Technology

2002-06-01

fits our actual data . To determine the goodness of fit, statisticians typically use the following four measures: R2 Statistic. The R2 statistic...reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of...mathematical model is developed to better estimate cleanup costs using historical cost data that could be used by the Defense Department prior to placing

The relationship between mathematical problem-solving skills and self-regulated learning through homework behaviours, motivation, and metacognition

NASA Astrophysics Data System (ADS)

Çiğdem Özcan, Zeynep

2016-04-01

Studies highlight that using appropriate strategies during problem solving is important to improve problem-solving skills and draw attention to the fact that using these skills is an important part of students' self-regulated learning ability. Studies on this matter view the self-regulated learning ability as key to improving problem-solving skills. The aim of this study is to investigate the relationship between mathematical problem-solving skills and the three dimensions of self-regulated learning (motivation, metacognition, and behaviour), and whether this relationship is of a predictive nature. The sample of this study consists of 323 students from two public secondary schools in Istanbul. In this study, the mathematics homework behaviour scale was administered to measure students' homework behaviours. For metacognition measurements, the mathematics metacognition skills test for students was administered to measure offline mathematical metacognitive skills, and the metacognitive experience scale was used to measure the online mathematical metacognitive experience. The internal and external motivational scales used in the Programme for International Student Assessment (PISA) test were administered to measure motivation. A hierarchic regression analysis was conducted to determine the relationship between the dependent and independent variables in the study. Based on the findings, a model was formed in which 24% of the total variance in students' mathematical problem-solving skills is explained by the three sub-dimensions of the self-regulated learning model: internal motivation (13%), willingness to do homework (7%), and post-problem retrospective metacognitive experience (4%).

An Empirical Investigation of Differences between Mathematics Specialists and Non-Specialists at the High School Level in Cyprus: A Logistic Regression Approach

ERIC Educational Resources Information Center

Papanastasiou, Elena C.; Zembylas, Michalinos

2006-01-01

The data obtained from high-school seniors for the Third International Mathematics and Science Study (TIMSS) for the country of Cyprus appear to be contradictory. Although Cypriot students did not perform well in mathematics in elementary school, middle school, and in the non-advanced sectors of high school, students in advanced mathematics…

Mathematics Readiness of First-Year University Students

ERIC Educational Resources Information Center

Atuahene, Francis; Russell, Tammy A.

2016-01-01

The majority of high school students, particularly underrepresented minorities (URMs) from low socioeconomic backgrounds are graduating from high school less prepared academically for advanced-level college mathematics. Using 2009 and 2010 course enrollment data, several statistical analyses (multiple linear regression, Cochran Mantel Haenszel…

A survey on the measure of combat readiness

NASA Astrophysics Data System (ADS)

Wen, Kwong Fook; Nor, Norazman Mohamad; Soon, Lee Lai

2014-09-01

Measuring the combat readiness in military forces involves the measures of tangible and intangible elements of combat power. Though these measures are applicable, the mathematical models and formulae used focus mainly on either the tangible or the intangible elements. In this paper, a review is done to highlight the research gap in the formulation of a mathematical model that incorporates tangible elements with intangible elements to measure the combat readiness of a military force. It highlights the missing link between the tangible and intangible elements of combat power. To bridge the gap and missing link, a mathematical model could be formulated that measures both the tangible and intangible aspects of combat readiness by establishing the relationship between the causal (tangible and intangible) elements and its effects on the measure of combat readiness. The model uses multiple regression analysis as well as mathematical modeling and simulation which digest the capability component reflecting its assets and resources, the morale component reflecting human needs, and the quality of life component reflecting soldiers' state of satisfaction in life. The results of the review provide a mean to bridge the research gap through the formulation of a mathematical model that shows the total measure of a military force's combat readiness. The results also significantly identify parameters for each of the variables and factors in the model.

Mathematics beliefs and instructional strategies in achievement of elementary-school students in Japan: results from the TIMSS 2003 assessment.

PubMed

House, J Daniel

2007-04-01

Recent findings concerning mathematics assessment indicate that students in Japan consistently score above international averages. Researchers have examined specific mathematics beliefs and instructional strategies associated with mathematics achievement for students in Japan. This study examined relationships among self-beliefs, classroom instructional strategies, and mathematics achievement for a large national sample of students (N=4,207) from the TIMSS 2003 international sample of fourth graders in Japan. Several significant relationships between mathematics beliefs and test scores were found; a number of classroom teaching strategies were also significantly associated with test scores. However, multiple regression using the complete set of five mathematics beliefs and five instructional strategies explained only 25.1% of the variance in mathematics achievement test scores.

Building Your Own Regression Model

ERIC Educational Resources Information Center

Horton, Robert, M.; Phillips, Vicki; Kenelly, John

2004-01-01

Spreadsheets to explore regression with an algebra 2 class in a medium-sized rural high school are presented. The use of spreadsheets can help students develop sophisticated understanding of mathematical models and use them to describe real-world phenomena.

Identification and agreement of first turn point by mathematical analysis applied to heart rate, carbon dioxide output and electromyography

PubMed Central

Zamunér, Antonio R.; Catai, Aparecida M.; Martins, Luiz E. B.; Sakabe, Daniel I.; Silva, Ester Da

2013-01-01

Background The second heart rate (HR) turn point has been extensively studied, however there are few studies determining the first HR turn point. Also, the use of mathematical and statistical models for determining changes in dynamic characteristics of physiological variables during an incremental cardiopulmonary test has been suggested. Objectives To determine the first turn point by analysis of HR, surface electromyography (sEMG), and carbon dioxide output () using two mathematical models and to compare the results to those of the visual method. Method Ten sedentary middle-aged men (53.9±3.2 years old) were submitted to cardiopulmonary exercise testing on an electromagnetic cycle ergometer until exhaustion. Ventilatory variables, HR, and sEMG of the vastus lateralis were obtained in real time. Three methods were used to determine the first turn point: 1) visual analysis based on loss of parallelism between and oxygen uptake (); 2) the linear-linear model, based on fitting the curves to the set of data (Lin-Lin ); 3) a bi-segmental linear regression of Hinkley' s algorithm applied to HR (HMM-HR), (HMM- ), and sEMG data (HMM-RMS). Results There were no differences between workload, HR, and ventilatory variable values at the first ventilatory turn point as determined by the five studied parameters (p>0.05). The Bland-Altman plot showed an even distribution of the visual analysis method with Lin-Lin , HMM-HR, HMM-CO2, and HMM-RMS. Conclusion The proposed mathematical models were effective in determining the first turn point since they detected the linear pattern change and the deflection point of , HR responses, and sEMG. PMID:24346296

Identification and agreement of first turn point by mathematical analysis applied to heart rate, carbon dioxide output and electromyography.

PubMed

Zamunér, Antonio R; Catai, Aparecida M; Martins, Luiz E B; Sakabe, Daniel I; Da Silva, Ester

2013-01-01

The second heart rate (HR) turn point has been extensively studied, however there are few studies determining the first HR turn point. Also, the use of mathematical and statistical models for determining changes in dynamic characteristics of physiological variables during an incremental cardiopulmonary test has been suggested. To determine the first turn point by analysis of HR, surface electromyography (sEMG), and carbon dioxide output (VCO2) using two mathematical models and to compare the results to those of the visual method. Ten sedentary middle-aged men (53.9 ± 3.2 years old) were submitted to cardiopulmonary exercise testing on an electromagnetic cycle ergometer until exhaustion. Ventilatory variables, HR, and sEMG of the vastus lateralis were obtained in real time. Three methods were used to determine the first turn point: 1) visual analysis based on loss of parallelism between VCO2 and oxygen uptake (VO2); 2) the linear-linear model, based on fitting the curves to the set of VCO2 data (Lin-LinVCO2); 3) a bi-segmental linear regression of Hinkley's algorithm applied to HR (HMM-HR), VCO2 (HMM-VCO2), and sEMG data (HMM-RMS). There were no differences between workload, HR, and ventilatory variable values at the first ventilatory turn point as determined by the five studied parameters (p>0.05). The Bland-Altman plot showed an even distribution of the visual analysis method with Lin-LinVCO2, HMM-HR, HMM-VCO2, and HMM-RMS. The proposed mathematical models were effective in determining the first turn point since they detected the linear pattern change and the deflection point of VCO2, HR responses, and sEMG.

Spatial analysis of relative humidity during ungauged periods in a mountainous region

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Kim, Yeonjoo

2017-08-01

Although atmospheric humidity influences environmental and agricultural conditions, thereby influencing plant growth, human health, and air pollution, efforts to develop spatial maps of atmospheric humidity using statistical approaches have thus far been limited. This study therefore aims to develop statistical approaches for inferring the spatial distribution of relative humidity (RH) for a mountainous island, for which data are not uniformly available across the region. A multiple regression analysis based on various mathematical models was used to identify the optimal model for estimating monthly RH by incorporating not only temperature but also location and elevation. Based on the regression analysis, we extended the monthly RH data from weather stations to cover the ungauged periods when no RH observations were available. Then, two different types of station-based data, the observational data and the data extended via the regression model, were used to form grid-based data with a resolution of 100 m. The grid-based data that used the extended station-based data captured the increasing RH trend along an elevation gradient. Furthermore, annual RH values averaged over the regions were examined. Decreasing temporal trends were found in most cases, with magnitudes varying based on the season and region.

Mathematics Intervention for First- and Second-Grade Students with Mathematics Difficulties: The Effects of Tier 2 Intervention Delivered as Booster Lessons

ERIC Educational Resources Information Center

Bryant, Diane Pedrotty; Bryant, Brian R.; Gersten, Russell; Scammacca, Nancy; Chavez, Melissa M.

2008-01-01

This study sought to examine the effects of Tier 2 intervention in a multitiered model on the performance of first- and second-grade students who were identified as having mathematics difficulties. A regression discontinuity design was utilized. Participants included 126 (Tier 2, n = 26) first graders and 140 (Tier 2, n = 25) second graders. Tier…

Risk stratification personalised model for prediction of life-threatening ventricular tachyarrhythmias in patients with chronic heart failure.

PubMed

Frolov, Alexander Vladimirovich; Vaikhanskaya, Tatjana Gennadjevna; Melnikova, Olga Petrovna; Vorobiev, Anatoly Pavlovich; Guel, Ludmila Michajlovna

2017-01-01

The development of prognostic factors of life-threatening ventricular tachyarrhythmias (VTA) and sudden cardiac death (SCD) continues to maintain its priority and relevance in cardiology. The development of a method of personalised prognosis based on multifactorial analysis of the risk factors associated with life-threatening heart rhythm disturbances is considered a key research and clinical task. To design a prognostic and mathematical model to define personalised risk for life-threatening VTA in patients with chronic heart failure (CHF). The study included 240 patients with CHF (mean-age of 50.5 ± 12.1 years; left ventricular ejection fraction 32.8 ± 10.9%; follow-up period 36.8 ± 5.7 months). The participants received basic therapy for heart failure. The elec-trocardiogram (ECG) markers of myocardial electrical instability were assessed including microvolt T-wave alternans, heart rate turbulence, heart rate deceleration, and QT dispersion. Additionally, echocardiography and Holter monitoring (HM) were performed. The cardiovascular events were considered as primary endpoints, including SCD, paroxysmal ventricular tachycardia/ventricular fibrillation (VT/VF) based on HM-ECG data, and data obtained from implantable device interrogation (CRT-D, ICD) as well as appropriated shocks. During the follow-up period, 66 (27.5%) subjects with CHF showed adverse arrhythmic events, including nine SCD events and 57 VTAs. Data from a stepwise discriminant analysis of cumulative ECG-markers of myocardial electrical instability were used to make a mathematical model of preliminary VTA risk stratification. Uni- and multivariate Cox logistic regression analysis were performed to define an individualised risk stratification model of SCD/VTA. A binary logistic regression model demonstrated a high prognostic significance of discriminant function with a classification sensitivity of 80.8% and specificity of 99.1% (F = 31.2; c2 = 143.2; p < 0.0001). The method of personalised risk stratification using Cox logistic regression allows correct classification of more than 93.9% of CHF cases. A robust body of evidence concerning logistic regression prognostic significance to define VTA risk allows inclusion of this method into the algorithm of subsequent control and selection of the optimal treatment modality to treat patients with CHF.

Comparison of methods for the analysis of relatively simple mediation models.

PubMed

Rijnhart, Judith J M; Twisk, Jos W R; Chinapaw, Mai J M; de Boer, Michiel R; Heymans, Martijn W

2017-09-01

Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural equation modeling (SEM), and the potential outcomes framework. Most applied researchers do not know that these methods are mathematically equivalent when applied to mediation models with a continuous mediator and outcome variable. Therefore, the aim of this paper was to demonstrate the similarities between OLS regression, SEM, and the potential outcomes framework in three mediation models: 1) a crude model, 2) a confounder-adjusted model, and 3) a model with an interaction term for exposure-mediator interaction. Secondary data analysis of a randomized controlled trial that included 546 schoolchildren. In our data example, the mediator and outcome variable were both continuous. We compared the estimates of the total, direct and indirect effects, proportion mediated, and 95% confidence intervals (CIs) for the indirect effect across OLS regression, SEM, and the potential outcomes framework. OLS regression, SEM, and the potential outcomes framework yielded the same effect estimates in the crude mediation model, the confounder-adjusted mediation model, and the mediation model with an interaction term for exposure-mediator interaction. Since OLS regression, SEM, and the potential outcomes framework yield the same results in three mediation models with a continuous mediator and outcome variable, researchers can continue using the method that is most convenient to them.

Independent contrasts and PGLS regression estimators are equivalent.

PubMed

Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

2012-05-01

We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

Trend Estimation and Regression Analysis in Climatological Time Series: An Application of Structural Time Series Models and the Kalman Filter.

NASA Astrophysics Data System (ADS)

Visser, H.; Molenaar, J.

1995-05-01

The detection of trends in climatological data has become central to the discussion on climate change due to the enhanced greenhouse effect. To prove detection, a method is needed (i) to make inferences on significant rises or declines in trends, (ii) to take into account natural variability in climate series, and (iii) to compare output from GCMs with the trends in observed climate data. To meet these requirements, flexible mathematical tools are needed. A structural time series model is proposed with which a stochastic trend, a deterministic trend, and regression coefficients can be estimated simultaneously. The stochastic trend component is described using the class of ARIMA models. The regression component is assumed to be linear. However, the regression coefficients corresponding with the explanatory variables may be time dependent to validate this assumption. The mathematical technique used to estimate this trend-regression model is the Kaiman filter. The main features of the filter are discussed.Examples of trend estimation are given using annual mean temperatures at a single station in the Netherlands (1706-1990) and annual mean temperatures at Northern Hemisphere land stations (1851-1990). The inclusion of explanatory variables is shown by regressing the latter temperature series on four variables: Southern Oscillation index (SOI), volcanic dust index (VDI), sunspot numbers (SSN), and a simulated temperature signal, induced by increasing greenhouse gases (GHG). In all analyses, the influence of SSN on global temperatures is found to be negligible. The correlations between temperatures and SOI and VDI appear to be negative. For SOI, this correlation is significant, but for VDI it is not, probably because of a lack of volcanic eruptions during the sample period. The relation between temperatures and GHG is positive, which is in agreement with the hypothesis of a warming climate because of increasing levels of greenhouse gases. The prediction performance of the model is rather poor, and possible explanations are discussed.

Improving reliability of aggregation, numerical simulation and analysis of complex systems by empirical data

NASA Astrophysics Data System (ADS)

Dobronets, Boris S.; Popova, Olga A.

2018-05-01

The paper considers a new approach of regression modeling that uses aggregated data presented in the form of density functions. Approaches to Improving the reliability of aggregation of empirical data are considered: improving accuracy and estimating errors. We discuss the procedures of data aggregation as a preprocessing stage for subsequent to regression modeling. An important feature of study is demonstration of the way how represent the aggregated data. It is proposed to use piecewise polynomial models, including spline aggregate functions. We show that the proposed approach to data aggregation can be interpreted as the frequency distribution. To study its properties density function concept is used. Various types of mathematical models of data aggregation are discussed. For the construction of regression models, it is proposed to use data representation procedures based on piecewise polynomial models. New approaches to modeling functional dependencies based on spline aggregations are proposed.

Harmony search optimization in dimensional accuracy of die sinking EDM process using SS316L stainless steel

NASA Astrophysics Data System (ADS)

Deris, A. M.; Zain, A. M.; Sallehuddin, R.; Sharif, S.

2017-09-01

Electric discharge machine (EDM) is one of the widely used nonconventional machining processes for hard and difficult to machine materials. Due to the large number of machining parameters in EDM and its complicated structural, the selection of the optimal solution of machining parameters for obtaining minimum machining performance is remain as a challenging task to the researchers. This paper proposed experimental investigation and optimization of machining parameters for EDM process on stainless steel 316L work piece using Harmony Search (HS) algorithm. The mathematical model was developed based on regression approach with four input parameters which are pulse on time, peak current, servo voltage and servo speed to the output response which is dimensional accuracy (DA). The optimal result of HS approach was compared with regression analysis and it was found HS gave better result y giving the most minimum DA value compared with regression approach.

Optimization to the Culture Conditions for Phellinus Production with Regression Analysis and Gene-Set Based Genetic Algorithm

PubMed Central

Li, Zhongwei; Xin, Yuezhen; Wang, Xun; Sun, Beibei; Xia, Shengyu; Li, Hui

2016-01-01

Phellinus is a kind of fungus and is known as one of the elemental components in drugs to avoid cancers. With the purpose of finding optimized culture conditions for Phellinus production in the laboratory, plenty of experiments focusing on single factor were operated and large scale of experimental data were generated. In this work, we use the data collected from experiments for regression analysis, and then a mathematical model of predicting Phellinus production is achieved. Subsequently, a gene-set based genetic algorithm is developed to optimize the values of parameters involved in culture conditions, including inoculum size, PH value, initial liquid volume, temperature, seed age, fermentation time, and rotation speed. These optimized values of the parameters have accordance with biological experimental results, which indicate that our method has a good predictability for culture conditions optimization. PMID:27610365

Predicting performance in a first engineering calculus course: implications for interventions

NASA Astrophysics Data System (ADS)

Hieb, Jeffrey L.; Lyle, Keith B.; Ralston, Patricia A. S.; Chariker, Julia

2015-01-01

At the University of Louisville, a large, urban institution in the south-east United States, undergraduate engineering students take their mathematics courses from the school of engineering. In the fall of their freshman year, engineering students take Engineering Analysis I, a calculus-based engineering analysis course. After the first two weeks of the semester, many students end up leaving Engineering Analysis I and moving to a mathematics intervention course. In an effort to retain more students in Engineering Analysis I, the department collaborated with university academic support services to create a summer intervention programme. Students were targeted for the summer programme based on their score on an algebra readiness exam (ARE). In a previous study, the ARE scores were found to be a significant predictor of retention and performance in Engineering Analysis I. This study continues that work, analysing data from students who entered the engineering school in the fall of 2012. The predictive validity of the ARE was verified, and a hierarchical linear regression model was created using math American College Testing (ACT) scores, ARE scores, summer intervention participation, and several metacognitive and motivational factors as measured by subscales of the Motivated Strategies for Learning Questionnaire. In the regression model, ARE score explained an additional 5.1% of the variation in exam performance in Engineering Analysis I beyond math ACT score. Students took the ARE before and after the summer interventions and scores were significantly higher following the intervention. However, intervention participants nonetheless had lower exam scores in Engineering Analysis I. The following factors related to motivation and learning strategies were found to significantly predict exam scores in Engineering Analysis I: time and study environment management, internal goal orientation, and test anxiety. The adjusted R2 for the full model was 0.42, meaning that the model could explain 42% of the variation in Engineering Analysis I exam scores.

Deriving the Regression Equation without Using Calculus

ERIC Educational Resources Information Center

Gordon, Sheldon P.; Gordon, Florence S.

2004-01-01

Probably the one "new" mathematical topic that is most responsible for modernizing courses in college algebra and precalculus over the last few years is the idea of fitting a function to a set of data in the sense of a least squares fit. Whether it be simple linear regression or nonlinear regression, this topic opens the door to applying the…

Preterm birth and dyscalculia.

PubMed

Jaekel, Julia; Wolke, Dieter

2014-06-01

To evaluate whether the risk for dyscalculia in preterm children increases the lower the gestational age (GA) and whether small-for-gestational age birth is associated with dyscalculia. A total of 922 children ranging from 23 to 41 weeks' GA were studied as part of a prospective geographically defined longitudinal investigation of neonatal at-risk children in South Germany. At 8 years of age, children's cognitive and mathematic abilities were measured with the Kaufman Assessment Battery for Children and with a standardized mathematics test. Dyscalculia diagnoses were evaluated with discrepancy-based residuals of a linear regression predicting children's math scores by IQ and with fixed cut-off scores. We investigated each GA group's ORs for general cognitive impairment, general mathematic impairment, and dyscalculia by using binary logistic regressions. The risk for general cognitive and mathematic impairment increased with lower GA. In contrast, preterm children were not at increased risk of dyscalculia after statistically adjusting for child sex, family socioeconomic status, and small-for-gestational age birth. The risk of general cognitive and mathematic impairments increases with lower GA but preterm children are not at increased risk of dyscalculia. Copyright © 2014 Elsevier Inc. All rights reserved.

Predicting Student Success in a Major's Introductory Biology Course via Logistic Regression Analysis of Scientific Reasoning Ability and Mathematics Scores

NASA Astrophysics Data System (ADS)

Thompson, E. David; Bowling, Bethany V.; Markle, Ross E.

2018-02-01

Studies over the last 30 years have considered various factors related to student success in introductory biology courses. While much of the available literature suggests that the best predictors of success in a college course are prior college grade point average (GPA) and class attendance, faculty often require a valuable predictor of success in those courses wherein the majority of students are in the first semester and have no previous record of college GPA or attendance. In this study, we evaluated the efficacy of the ACT Mathematics subject exam and Lawson's Classroom Test of Scientific Reasoning in predicting success in a major's introductory biology course. A logistic regression was utilized to determine the effectiveness of a combination of scientific reasoning (SR) scores and ACT math (ACT-M) scores to predict student success. In summary, we found that the model—with both SR and ACT-M as significant predictors—could be an effective predictor of student success and thus could potentially be useful in practical decision making for the course, such as directing students to support services at an early point in the semester.

Mathematics beliefs and achievement of a national sample of Native American students: results from the Trends in International Mathematics and Science Study (TIMSS) 2003 United States assessment.

PubMed

House, J Daniel

2009-04-01

Recent mathematics assessment findings indicate that Native American students tend to score below students of the ethnic majority. Findings suggest that students' beliefs about mathematics are significantly related to achievement outcomes. This study examined relations between self-beliefs and mathematics achievement for a national sample of 130 Grade 8 Native American students from the Trends in International Mathematics and Science Study (TIMSS) 2003 United States sample of (M age = 14.2 yr., SD = 0.5). Multiple regression indicated several significant relations of mathematics beliefs with achievement and accounted for 26.7% of the variance in test scores. Students who earned high test scores tended to hold more positive beliefs about their ability to learn mathematics quickly, while students who earned low scores expressed negative beliefs about their ability to learn new mathematics topics.

Numerical simulations for tumor and cellular immune system interactions in lung cancer treatment

NASA Astrophysics Data System (ADS)

Kolev, M.; Nawrocki, S.; Zubik-Kowal, B.

2013-06-01

We investigate a new mathematical model that describes lung cancer regression in patients treated by chemotherapy and radiotherapy. The model is composed of nonlinear integro-differential equations derived from the so-called kinetic theory for active particles and a new sink function is investigated according to clinical data from carcinoma planoepitheliale. The model equations are solved numerically and the data are utilized in order to find their unknown parameters. The results of the numerical experiments show a good correlation between the predicted and clinical data and illustrate that the mathematical model has potential to describe lung cancer regression.

Deaf College Students' Mathematical Skills Relative to Morphological Knowledge, Reading Level, and Language Proficiency

ERIC Educational Resources Information Center

Kelly, Ronald R.; Gaustad, Martha G.

2007-01-01

This study of deaf college students examined specific relationships between their mathematics performance and their assessed skills in reading, language, and English morphology. Simple regression analyses showed that deaf college students' language proficiency scores, reading grade level, and morphological knowledge regarding word segmentation and…

The Value of 18F-FDG PET/CT Mathematical Prediction Model in Diagnosis of Solitary Pulmonary Nodules

PubMed Central

Chen, Yao; Tang, Kun; Lin, Jie

2018-01-01

Purpose To establish an 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) mathematical prediction model to improve the diagnosis of solitary pulmonary nodules (SPNs). Materials and Methods We retrospectively reviewed 177 consecutive patients who underwent 18F-FDG PET/CT for evaluation of SPNs. The mathematical model was established by logistic regression analysis. The diagnostic capabilities of the model were calculated, and the areas under the receiver operating characteristic curve (AUC) were compared with Mayo and VA model. Results The mathematical model was y = exp⁡(x)/[1 + exp⁡(x)], x = −7.363 + 0.079 × age + 1.900 × lobulation + 1.024 × vascular convergence + 1.530 × pleural retraction + 0.359 × the maximum of standardized uptake value (SUVmax). When the cut-off value was set at 0.56, the sensitivity, specificity, and accuracy of our model were 86.55%, 74.14%, and 81.4%, respectively. The area under the receiver operating characteristic curve (AUC) of our model was 0.903 (95% confidence interval (CI): 0.860 to 0.946). The AUC of our model was greater than that of the Mayo model, the VA model, and PET (P < 0.05) and has no difference with that of PET/CT (P > 0.05). Conclusion The mathematical predictive model has high accuracy in estimating the malignant probability of patients with SPNs. PMID:29789808

Statistical experiments using the multiple regression research for prediction of proper hardness in areas of phosphorus cast-iron brake shoes manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Ratiu, S. A.; Rackov, M.; Penčić, M.

2018-01-01

Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. This article focuses on expressing the multiple linear regression model related to the hardness assurance by the chemical composition of the phosphorous cast irons destined to the brake shoes, having in view that the regression coefficients will illustrate the unrelated contributions of each independent variable towards predicting the dependent variable. In order to settle the multiple correlations between the hardness of the cast-iron brake shoes, and their chemical compositions several regression equations has been proposed. Is searched a mathematical solution which can determine the optimum chemical composition for the hardness desirable values. Starting from the above-mentioned affirmations two new statistical experiments are effectuated related to the values of Phosphorus [P], Manganese [Mn] and Silicon [Si]. Therefore, the regression equations, which describe the mathematical dependency between the above-mentioned elements and the hardness, are determined. As result, several correlation charts will be revealed.

Stiffness analysis of glued connection of the timber-concrete structure

NASA Astrophysics Data System (ADS)

Daňková, Jana; Mec, Pavel; Majstríková, Tereza

2016-01-01

This paper presents results of experimental and mathematical analysis of stiffness characteristics of a composite timber-concrete structure. The composite timberconcrete structure presented herein is non-typical compared to similar types of building structures. The interaction between the timber and concrete part of the composite cross-section is not based on metal connecting elements, but it is ensured by a glued-in perforated mesh made of plywood. The paper presents results of experimental and mathematical analysis for material alternatives of the solution of the glued joint. The slip modulus values were determined experimentally. Data obtained from the experiment evaluated by means of regression analysis. Test results were also used as input data for the compilation of a 3D model of a composite structure by means of the 3D finite element model. On the basis of result evaluation, it can be stated that the stress-deformation behaviour at shear loading of this specific timber-concrete composite structure can be affected by the type of glue used. Parameters of the 3D model of both alternative of the structure represent well the behaviour of the composite structure and the model can be used for predicting design parameters of a building structure.

Mathematic simulation of soil-vegetation condition and land use structure applying basin approach

NASA Astrophysics Data System (ADS)

Mishchenko, Natalia; Shirkin, Leonid; Krasnoshchekov, Alexey

2016-04-01

Ecosystems anthropogenic transformation is basically connected to the changes of land use structure and human impact on soil fertility. The Research objective is to simulate the stationary state of river basins ecosystems. Materials and Methods. Basin approach has been applied in the research. Small rivers basins of the Klyazma river have been chosen as our research objects. They are situated in the central part of the Russian plain. The analysis is carried out applying integrated characteristics of ecosystems functioning and mathematic simulation methods. To design mathematic simulator functional simulation methods and principles on the basis of regression, correlation and factor analysis have been applied in the research. Results. Mathematic simulation resulted in defining possible permanent conditions of "phytocenosis-soil" system in coordinates of phytomass, phytoproductivity, humus percentage in soil. Ecosystem productivity is determined not only by vegetation photosynthesis activity but also by the area ratio of forest and meadow phytocenosis. Local maximums attached to certain phytomass areas and humus content in soil have been defined on the basin phytoproductivity distribution diagram. We explain the local maximum by synergetic effect. It appears with the definite ratio of forest and meadow phytocenosis. In this case, utmost values of phytomass for the whole area are higher than just a sum of utmost values of phytomass for the forest and meadow phytocenosis. Efficient correlation of natural forest and meadow phytocenosis has been defined for the Klyazma river. Conclusion. Mathematic simulation methods assist in forecasting the ecosystem conditions under various changes of land use structure. Nowadays overgrowing of the abandoned agricultural lands is very actual for the Russian Federation. Simulation results demonstrate that natural ratio of forest and meadow phytocenosis for the area will restore during agricultural overgrowing.

Which Preschool Mathematics Competencies Are Most Predictive of Fifth Grade Achievement?

PubMed

Nguyen, Tutrang; Watts, Tyler W; Duncan, Greg J; Clements, Douglas H; Sarama, Julie S; Wolfe, Christopher; Spitler, Mary Elaine

In an effort to promote best practices regarding mathematics teaching and learning at the preschool level, national advisory panels and organizations have emphasized the importance of children's emergent counting and related competencies, such as the ability to verbally count, maintain one-to-one correspondence, count with cardinality, subitize, and count forward or backward from a given number. However, little research has investigated whether the kind of mathematical knowledge promoted by the various standards documents actually predict later mathematics achievement. The present study uses longitudinal data from a primarily low-income and minority sample of children to examine the extent to which preschool mathematical competencies, specifically basic and advanced counting, predict fifth grade mathematics achievement. Using regression analyses, we find early numeracy abilities to be the strongest predictors of later mathematics achievement, with advanced counting competencies more predictive than basic counting competencies. Our results highlight the significance of preschool mathematics knowledge for future academic achievement.

Among friends: the role of academic-preparedness diversity in individual performance within a small-group STEM learning environment

NASA Astrophysics Data System (ADS)

Micari, Marina; Van Winkle, Zachary; Pazos, Pilar

2016-08-01

In this study, we investigate the relationship between academic-preparedness diversity within small learning groups and individual academic performance in science, technology, engineering, and mathematics (STEM) university courses. We further examine whether academic-preparedness diversity impacts academically more- and less-prepared students differently. We use data from 5367 university students nested within 1141 science, engineering, and mathematics learning groups and use a regression analysis to estimate the effect of group diversity, measured in two ways, on course performance. Our results indicate that academic-preparedness diversity is generally associated with positive learning outcomes, that academically less-prepared students derive greater benefit, and that less-prepared students fare best when they are not alone in a group of highly prepared students. Implications for teaching and small-group facilitation are addressed.

Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

ERIC Educational Resources Information Center

Lee, Young-Jin

2017-01-01

Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

Relationship between academic motivation and mathematics achievement among Indian adolescents in Canada and India.

PubMed

Areepattamannil, Shaljan

2014-01-01

This study examined the relationships between academic motivation-intrinsic motivation, extrinsic motivation, amotivation-and mathematics achievement among 363 Indian adolescents in India and 355 Indian immigrant adolescents in Canada. Results of hierarchical multiple regression analyses showed that intrinsic motivation, extrinsic motivation, and amotivation were not statistically significantly related to mathematics achievement among Indian adolescents in India. In contrast, both intrinsic motivation and extrinsic motivation were statistically significantly related to mathematics achievement among Indian immigrant adolescents in Canada. While intrinsic motivation was a statistically significant positive predictor of mathematics achievement among Indian immigrant adolescents in Canada, extrinsic motivation was a statistically significant negative predictor of mathematics achievement among Indian immigrant adolescents in Canada. Amotivation was not statistically significantly related to mathematics achievement among Indian immigrant adolescents in Canada. Implications of the findings for pedagogy and practice are discussed.

Modeling energy expenditure in children and adolescents using quantile regression

USDA-ARS?s Scientific Manuscript database

Advanced mathematical models have the potential to capture the complex metabolic and physiological processes that result in energy expenditure (EE). Study objective is to apply quantile regression (QR) to predict EE and determine quantile-dependent variation in covariate effects in nonobese and obes...

A FORTRAN technique for correlating a circular environmental variable with a linear physiological variable in the sugar maple.

PubMed

Pease, J M; Morselli, M F

1987-01-01

This paper deals with a computer program adapted to a statistical method for analyzing an unlimited quantity of binary recorded data of an independent circular variable (e.g. wind direction), and a linear variable (e.g. maple sap flow volume). Circular variables cannot be statistically analyzed with linear methods, unless they have been transformed. The program calculates a critical quantity, the acrophase angle (PHI, phi o). The technique is adapted from original mathematics [1] and is written in Fortran 77 for easier conversion between computer networks. Correlation analysis can be performed following the program or regression which, because of the circular nature of the independent variable, becomes periodic regression. The technique was tested on a file of approximately 4050 data pairs.

Influences of Metacognitive and Self-Regulated Learning Strategies for Reading on Mathematical Literacy of Adolescents in Australia and Singapore

ERIC Educational Resources Information Center

Kaur, Berinderjeet; Areepattamannil, Shaljan

2012-01-01

This study, drawing on data from the Programme for International Student Assessment (PISA) 2009, explored the influences of metacognitive and self-regulated learning strategies for reading on mathematical literacy of adolescents in Australia and Singapore. Ordinary least squares (OLS) regression analyses revealed the positive influences of…

Structural, Linguistic and Topic Variables in Verbal and Computational Problems in Elementary Mathematics.

ERIC Educational Resources Information Center

Beardslee, Edward C.; Jerman, Max E.

Five structural, four linguistic and twelve topic variables are used in regression analyses on results of a 50-item achievement test. The test items are related to 12 topics from the third-grade mathematics curriculum. The items reflect one of two cases of the structural variable, cognitive level; the two levels are characterized, inductive…

Relations between Measures of Cattell-Horn-Carroll (CHC) Cognitive Abilities and Mathematics Achievement across the School-Age Years

ERIC Educational Resources Information Center

Floyd, Randy G.; Evans, Jeffrey J.; McGrew, Kevin S.

2003-01-01

Cognitive clusters from the Woodcock-Johnson III (WJ III) Tests of Cognitive Abilities that measure select Cattell-Horn-Carroll broad and narrow cognitive abilities were shown to be significantly related to mathematics achievement in a large, nationally representative sample of children and adolescents. Multiple regression analyses were used to…

A Regression Model with a New Tool: IDB Analyzer for Identifying Factors Predicting Mathematics Performance Using PISA 2012 Indices

ERIC Educational Resources Information Center

Arikan, Serkan

2014-01-01

There are many studies that focus on factors affecting achievement. However, there is limited research that used student characteristics indices reported by the Programme for International Student Assessment (PISA). Therefore, this study investigated the predictive effects of student characteristics on mathematics performance of Turkish students.…

Statistical research using the multiple regression analysis in areas of the cast hipereutectoid steel rolls manufacturing

NASA Astrophysics Data System (ADS)

Kiss, I.; Alexa, V.; Serban, S.; Rackov, M.; Čavić, M.

2018-01-01

The cast hipereutectoid steel (usually named Adamite) is a roll manufacturing destined material, having mechanical, chemical properties and Carbon [C] content of which stands between steelandiron, along-withitsalloyelements such as Nickel [Ni], Chrome [Cr], Molybdenum [Mo] and/or other alloy elements. Adamite Rolls are basically alloy steel rolls (a kind of high carbon steel) having hardness ranging from 40 to 55 degrees Shore C, with Carbon [C] percentage ranging from 1.35% until to 2% (usually between 1.2˜2.3%), the extra Carbon [C] and the special alloying element giving an extra wear resistance and strength. First of all the Adamite roll’s prominent feature is the small variation in hardness of the working surface, and has a good abrasion resistance and bite performance. This paper reviews key aspects of roll material properties and presents an analysis of the influences of chemical composition upon the mechanical properties (hardness) of the cast hipereutectoid steel rolls (Adamite). Using the multiple regression analysis (the double and triple regression equations), some mathematical correlations between the cast hipereutectoid steel rolls’ chemical composition and the obtained hardness are presented. In this work several results and evidence obtained by actual experiments are presented. Thus, several variation boundaries for the chemical composition of cast hipereutectoid steel rolls, in view the obtaining the proper values of the hardness, are revealed. For the multiple regression equations, correlation coefficients and graphical representations the software Matlab was used.

An Integrated Analysis of the Physiological Effects of Space Flight: Executive Summary

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1985-01-01

A large array of models were applied in a unified manner to solve problems in space flight physiology. Mathematical simulation was used as an alternative way of looking at physiological systems and maximizing the yield from previous space flight experiments. A medical data analysis system was created which consist of an automated data base, a computerized biostatistical and data analysis system, and a set of simulation models of physiological systems. Five basic models were employed: (1) a pulsatile cardiovascular model; (2) a respiratory model; (3) a thermoregulatory model; (4) a circulatory, fluid, and electrolyte balance model; and (5) an erythropoiesis regulatory model. Algorithms were provided to perform routine statistical tests, multivariate analysis, nonlinear regression analysis, and autocorrelation analysis. Special purpose programs were prepared for rank correlation, factor analysis, and the integration of the metabolic balance data.

Distributed collaborative probabilistic design of multi-failure structure with fluid-structure interaction using fuzzy neural network of regression

NASA Astrophysics Data System (ADS)

Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen

2018-05-01

To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.

[Risk factor analysis of the patients with solitary pulmonary nodules and establishment of a prediction model for the probability of malignancy].

PubMed

Wang, X; Xu, Y H; Du, Z Y; Qian, Y J; Xu, Z H; Chen, R; Shi, M H

2018-02-23

Objective: This study aims to analyze the relationship among the clinical features, radiologic characteristics and pathological diagnosis in patients with solitary pulmonary nodules, and establish a prediction model for the probability of malignancy. Methods: Clinical data of 372 patients with solitary pulmonary nodules who underwent surgical resection with definite postoperative pathological diagnosis were retrospectively analyzed. In these cases, we collected clinical and radiologic features including gender, age, smoking history, history of tumor, family history of cancer, the location of lesion, ground-glass opacity, maximum diameter, calcification, vessel convergence sign, vacuole sign, pleural indentation, speculation and lobulation. The cases were divided to modeling group (268 cases) and validation group (104 cases). A new prediction model was established by logistic regression analying the data from modeling group. Then the data of validation group was planned to validate the efficiency of the new model, and was compared with three classical models(Mayo model, VA model and LiYun model). With the calculated probability values for each model from validation group, SPSS 22.0 was used to draw the receiver operating characteristic curve, to assess the predictive value of this new model. Results: 112 benign SPNs and 156 malignant SPNs were included in modeling group. Multivariable logistic regression analysis showed that gender, age, history of tumor, ground -glass opacity, maximum diameter, and speculation were independent predictors of malignancy in patients with SPN( P <0.05). We calculated a prediction model for the probability of malignancy as follow: p =e(x)/(1+ e(x)), x=-4.8029-0.743×gender+ 0.057×age+ 1.306×history of tumor+ 1.305×ground-glass opacity+ 0.051×maximum diameter+ 1.043×speculation. When the data of validation group was added to the four-mathematical prediction model, The area under the curve of our mathematical prediction model was 0.742, which is greater than other models (Mayo 0.696, VA 0.634, LiYun 0.681), while the differences between any two of the four models were not significant ( P >0.05). Conclusions: Age of patient, gender, history of tumor, ground-glass opacity, maximum diameter and speculation are independent predictors of malignancy in patients with solitary pulmonary nodule. This logistic regression prediction mathematic model is not inferior to those classical models in estimating the prognosis of SPNs.

Mathematics beliefs and achievement of adolescent students in Japan: results from the TIMSS 1999 assessment.

PubMed

House, J Daniel

2005-12-01

A recent study (1) of undergraduate students in a precalculus course indicated that they expressed slightly positive attitudes toward mathematics. It is important, however, to examine relationships between students' initial attitudes and achievement outcomes. The present purpose was to assess the relationship between self-beliefs and mathematics achievement for a large national sample of students from the TIMSS 1999 international sample (eighth graders) from Japan. Several significant relationships between mathematics beliefs and test scores were noted. In addition, the overall multiple regression equation that assessed the joint significance of the complete set of self-belief variables was significant (F7.65 = 159.48, p < .001) and explained 20.6% of the variance in mathematics achievement test scores.

A cumulative risk factor model for early identification of academic difficulties in premature and low birth weight infants.

PubMed

Roberts, G; Bellinger, D; McCormick, M C

2007-03-01

Premature and low birth weight children have a high prevalence of academic difficulties. This study examines a model comprised of cumulative risk factors that allows early identification of these difficulties. This is a secondary analysis of data from a large cohort of premature (<37 weeks gestation) and LBW (<2500 g) children. The study subjects were 8 years of age and 494 had data available for reading achievement and 469 for mathematics. Potential predictor variables were categorized into 4 domains: sociodemographic, neonatal, maternal mental health and early childhood (ages 3 and 5). Regression analysis was used to create a model to predict reading and mathematics scores. Variables from all domains were significant in the model, predicting low achievement scores in reading (R (2) of 0.49, model p-value < .0001) and mathematics (R (2) of 0.44, model p-value < .0001). Significant risk factors for lower reading scores, were: lower maternal education and income, and Black or Hispanic race (sociodemographic); lower birth weight and male gender (neonatal); lower maternal responsivity (maternal mental health); lower intelligence, visual-motor skill and higher behavioral disturbance scores (early childhood). Lower mathematics scores were predicted by lower maternal education, income and age and Black or Hispanic race (sociodemographic); lower birth weight and higher head circumference (neonatal); lower maternal responsivity (maternal mental health); lower intelligence, visual-motor skill and higher behavioral disturbance scores (early childhood). Sequential early childhood risk factors in premature and LBW children lead to a cumulative risk for academic difficulties and can be used for early identification.

Commentary on the statistical properties of noise and its implication on general linear models in functional near-infrared spectroscopy.

PubMed

Huppert, Theodore J

2016-01-01

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of light to measure changes in cerebral blood oxygenation levels. In the majority of NIRS functional brain studies, analysis of this data is based on a statistical comparison of hemodynamic levels between a baseline and task or between multiple task conditions by means of a linear regression model: the so-called general linear model. Although these methods are similar to their implementation in other fields, particularly for functional magnetic resonance imaging, the specific application of these methods in fNIRS research differs in several key ways related to the sources of noise and artifacts unique to fNIRS. In this brief communication, we discuss the application of linear regression models in fNIRS and the modifications needed to generalize these models in order to deal with structured (colored) noise due to systemic physiology and noise heteroscedasticity due to motion artifacts. The objective of this work is to present an overview of these noise properties in the context of the linear model as it applies to fNIRS data. This work is aimed at explaining these mathematical issues to the general fNIRS experimental researcher but is not intended to be a complete mathematical treatment of these concepts.

Computerized dynamic posturography: the influence of platform stability on postural control.

PubMed

Palm, Hans-Georg; Lang, Patricia; Strobel, Johannes; Riesner, Hans-Joachim; Friemert, Benedikt

2014-01-01

Postural stability can be quantified using posturography systems, which allow different foot platform stability settings to be selected. It is unclear, however, how platform stability and postural control are mathematically correlated. Twenty subjects performed tests on the Biodex Stability System at all 13 stability levels. Overall stability index, medial-lateral stability index, and anterior-posterior stability index scores were calculated, and data were analyzed using analysis of variance and linear regression analysis. A decrease in platform stability from the static level to the second least stable level was associated with a linear decrease in postural control. The overall stability index scores were 1.5 ± 0.8 degrees (static), 2.2 ± 0.9 degrees (level 8), and 3.6 ± 1.7 degrees (level 2). The slope of the regression lines was 0.17 for the men and 0.10 for the women. A linear correlation was demonstrated between platform stability and postural control. The influence of stability levels seems to be almost twice as high in men as in women.

Modelling the effect of the physical and chemical characteristics of the materials used as casing layers on the production parameters of Agaricus bisporus.

PubMed

Pardo, Arturo; Emilio Pardo, J; de Juan, J Arturo; Zied, Diego Cunha

2010-12-01

The aim of this research was to show the mathematical data obtained through the correlations found between the physical and chemical characteristics of casing layers and the final mushrooms' properties. For this purpose, 8 casing layers were used: soil, soil + peat moss, soil + black peat, soil + composted pine bark, soil + coconut fibre pith, soil + wood fibre, soil + composted vine shoots and, finally, the casing of La Rioja subjected to the ruffling practice. The conclusion that interplays in the fructification process with only the physical and chemical characteristics of casing are complicated was drawn. The mathematical data obtained in earliness could be explained in non-ruffled cultivation. The variability observed for the mushroom weight and the mushroom diameter variables could be explained in both ruffled and non-ruffled cultivations. Finally, the properties of the final quality of mushrooms were established by regression analysis.

Predicting scientific oral presentation scores in a high school photonics science, technology, engineering and mathematics (STEM) program

NASA Astrophysics Data System (ADS)

Gilchrist, Pamela O.; Carpenter, Eric D.; Gray-Battle, Asia

2014-07-01

A hybrid teacher professional development, student science technology mathematics and engineering pipeline enrichment program was operated by the reporting research group for the past 3 years. Overall, the program has reached 69 students from 13 counties in North Carolina and 57 teachers from 30 counties spread over a total of five states. Quantitative analysis of oral presentations given by participants at a program event is provided. Scores from multiple raters were averaged and used as a criterion in several regression analyses. Overall it was revealed that student grade point averages, most advanced science course taken, extra quality points earned in their most advanced science course taken, and posttest scores on a pilot research design survey were significant predictors of student oral presentation scores. Rationale for findings, opportunities for future research, and implications for the iterative development of the program are discussed.

Assessment of traffic noise levels in urban areas using different soft computing techniques.

PubMed

Tomić, J; Bogojević, N; Pljakić, M; Šumarac-Pavlović, D

2016-10-01

Available traffic noise prediction models are usually based on regression analysis of experimental data, and this paper presents the application of soft computing techniques in traffic noise prediction. Two mathematical models are proposed and their predictions are compared to data collected by traffic noise monitoring in urban areas, as well as to predictions of commonly used traffic noise models. The results show that application of evolutionary algorithms and neural networks may improve process of development, as well as accuracy of traffic noise prediction.

School league tables: a new population based predictor of dental restorative treatment need.

PubMed

Crowley, Evelyn; O'Brien, Graham; Marcenes, Wagner

2003-06-01

To test whether dental restorative treatment need was related to the school league tables and level of social deprivation of the school ward. An ecological study using clinical data aggregated at school level, collected in the school dental screening examinations (1996-97), National Census (1991) and the results of the UK school league tables--Key Stage 2 SATs (1996-97). State primary schools in the Greenwich District of SE London, UK (1996-97). 12,854 pupils (6-11 years of age) in 62 schools. The percentage of 6 to 11 year old pupils per school requiring dental restorative treatment. Deprivation as measured by the overall Jarman Under Privileged Area Index (UPA) of the school ward was not associated with dental restorative treatment need (p > 0.05). Only two components of the Jarman Index, level of unemployment and the number of lone parent families in the school ward were found to be significantly associated with dental restorative treatment need (p < 0.05). Results of stepwise multiple linear regression analysis showed that the association with the school league table results in all three subjects, English, Mathematics and Science remained statistically significant after adjusting for levels of unemployment and single parents. Results of multiple linear regression analysis showed that a high level of dental restorative treatment need was significantly associated with poor school league table results in English, Mathematics and Science (p < 0.05) after adjusting for the overall Jarman score of the school ward. A separate analysis for the 11-year-old pupils aggregated by school (n = 46 schools) gave similar results. Aggregate measures of academic achievement may be a potential indicator of dental restorative treatment need.

Which Preschool Mathematics Competencies Are Most Predictive of Fifth Grade Achievement?

PubMed Central

Nguyen, Tutrang; Watts, Tyler W.; Duncan, Greg J.; Clements, Douglas H.; Sarama, Julie S.; Wolfe, Christopher; Spitler, Mary Elaine

2016-01-01

In an effort to promote best practices regarding mathematics teaching and learning at the preschool level, national advisory panels and organizations have emphasized the importance of children’s emergent counting and related competencies, such as the ability to verbally count, maintain one-to-one correspondence, count with cardinality, subitize, and count forward or backward from a given number. However, little research has investigated whether the kind of mathematical knowledge promoted by the various standards documents actually predict later mathematics achievement. The present study uses longitudinal data from a primarily low-income and minority sample of children to examine the extent to which preschool mathematical competencies, specifically basic and advanced counting, predict fifth grade mathematics achievement. Using regression analyses, we find early numeracy abilities to be the strongest predictors of later mathematics achievement, with advanced counting competencies more predictive than basic counting competencies. Our results highlight the significance of preschool mathematics knowledge for future academic achievement. PMID:27057084

The big-fish-little-pond effect on mathematics self-concept: Evidence from the United Arab Emirates.

PubMed

Areepattamannil, Shaljan; Khine, Myint Swe; Al Nuaimi, Samira

2017-08-01

This study examined the big-fish-little-pond effect (BFLPE; Marsh, 1987) on mathematics self-concept of 7404 adolescents (female = 3767 [51%], male = 3637 [49%]; M age  = 15.85 years, SD = 0.28) from 456 schools in the United Arab Emirates, one of the Arab states of the Persian Gulf. The results of multilevel regression analyses indicated good support for the BFLPE's theoretical predictions: the effect of individual student mathematics achievement on individual student mathematics self-concept was positive and statistically significant, whereas the effect of school-average mathematics achievement on individual student mathematics self-concept was negative and statistically significant. Moreover, the interaction between school-average mathematics achievement and individual student mathematics achievement was small and non-significant. Implications of the findings for policy and practice are briefly discussed. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Missing data imputation: focusing on single imputation.

PubMed

Zhang, Zhongheng

2016-01-01

Complete case analysis is widely used for handling missing data, and it is the default method in many statistical packages. However, this method may introduce bias and some useful information will be omitted from analysis. Therefore, many imputation methods are developed to make gap end. The present article focuses on single imputation. Imputations with mean, median and mode are simple but, like complete case analysis, can introduce bias on mean and deviation. Furthermore, they ignore relationship with other variables. Regression imputation can preserve relationship between missing values and other variables. There are many sophisticated methods exist to handle missing values in longitudinal data. This article focuses primarily on how to implement R code to perform single imputation, while avoiding complex mathematical calculations.

Missing data imputation: focusing on single imputation

PubMed Central

2016-01-01

Complete case analysis is widely used for handling missing data, and it is the default method in many statistical packages. However, this method may introduce bias and some useful information will be omitted from analysis. Therefore, many imputation methods are developed to make gap end. The present article focuses on single imputation. Imputations with mean, median and mode are simple but, like complete case analysis, can introduce bias on mean and deviation. Furthermore, they ignore relationship with other variables. Regression imputation can preserve relationship between missing values and other variables. There are many sophisticated methods exist to handle missing values in longitudinal data. This article focuses primarily on how to implement R code to perform single imputation, while avoiding complex mathematical calculations. PMID:26855945

Accurate Descriptions of Hot Flow Behaviors Across β Transus of Ti-6Al-4V Alloy by Intelligence Algorithm GA-SVR

NASA Astrophysics Data System (ADS)

Wang, Li-yong; Li, Le; Zhang, Zhi-hua

2016-09-01

Hot compression tests of Ti-6Al-4V alloy in a wide temperature range of 1023-1323 K and strain rate range of 0.01-10 s-1 were conducted by a servo-hydraulic and computer-controlled Gleeble-3500 machine. In order to accurately and effectively characterize the highly nonlinear flow behaviors, support vector regression (SVR) which is a machine learning method was combined with genetic algorithm (GA) for characterizing the flow behaviors, namely, the GA-SVR. The prominent character of GA-SVR is that it with identical training parameters will keep training accuracy and prediction accuracy at a stable level in different attempts for a certain dataset. The learning abilities, generalization abilities, and modeling efficiencies of the mathematical regression model, ANN, and GA-SVR for Ti-6Al-4V alloy were detailedly compared. Comparison results show that the learning ability of the GA-SVR is stronger than the mathematical regression model. The generalization abilities and modeling efficiencies of these models were shown as follows in ascending order: the mathematical regression model < ANN < GA-SVR. The stress-strain data outside experimental conditions were predicted by the well-trained GA-SVR, which improved simulation accuracy of the load-stroke curve and can further improve the related research fields where stress-strain data play important roles, such as speculating work hardening and dynamic recovery, characterizing dynamic recrystallization evolution, and improving processing maps.

The Influence of Socioeconomic, Parental, and District Factors on the 2013 MCAS Grade 4 Language Arts and Mathematics Scores

ERIC Educational Resources Information Center

Caldwell, Dale G.

2017-01-01

This correlational, explanatory study utilized multiple linear and hierarchical regression to examine the predictive power of socioeconomic, parental and district factors on the total percentage of students who scored Proficient or Advanced Proficient on the 2013 MCAS Grade 4 language arts and mathematics test. The population for this study…

School Effects on Educational Achievement in Mathematics and Science: 1985-86. National Assessment of Educational Progress. Research and Development Report.

ERIC Educational Resources Information Center

Arnold, Carolyn L.; Kaufman, Phillip D.

This report examines the effects of both student and school characteristics on mathematics and science achievement levels in the third, seventh, and eleventh grades using data from the 1985-86 National Assessment of Educational Progress (NAEP). Analyses feature hierarchical linear models (HLM), a regression-like statistical technique that…

Exploring the Ups and Downs of Mathematics Engagement in the Middle Years of School

ERIC Educational Resources Information Center

Martin, Andrew J.; Way, Jennifer; Bobis, Janette; Anderson, Judy

2015-01-01

This study of 1,601 students in the middle years of schooling (Grades 5-8, each student measured twice, 1 year apart) from 200 classrooms in 44 schools sought to identify factors explaining gains and declines in mathematics engagement at key transition points. In multilevel regression modeling, findings showed that compared with Grade 6 students…

Socioeconomic Status, Higher-Level Mathematics Courses, Absenteeism, and Student Mobility as Indicators of Work Readiness

ERIC Educational Resources Information Center

Folds, Lea D.; Tanner, C. Kenneth

2014-01-01

The purpose of this study was to analyze the relations among socioeconomic status, highest-level mathematics course, absenteeism, student mobility and measures of work readiness of high school seniors in Georgia. Study participants were 476 high school seniors in one Georgia county. The full regression model explained 27.5% of the variance in…

Understanding the effect of compositions on electronegativity, atomic radius and thermal stability of Mg-Ni-Y amorphous alloy

NASA Astrophysics Data System (ADS)

Deshmukh, A. A.; Kuthe, S. A.; Palikundwar, U. A.

2018-05-01

In the present paper, the consequences of variation in compositions on the electronegativity (ΔX), atomic radius difference (δ) and the thermal stability (ΔTx) of Mg-Ni-Y bulk metallic glasses (BMGs) are evaluated. In order to understand the effect of variation in compositions on ΔX, δ and ΔTx, regression analysis is performed on the experimentally available data. A linear correlation between both δ and ΔX with regression coefficient 0.93 is observed. Further, compositional variation is performed with δ and then it is correlated to the ΔTx by deriving subsequent equations. It is observed that concentration of Mg, Ni and Y are directly proportional to the δ with regression coefficients 0.93, 0.93 and 0.50 respectively. The positive slope of Ni and Y stated that ΔTx will increase if it has more contribution from both Ni and Y. On the other hand negative slope stated that composition of Mg should be selected in such a way that it will have more stability with Ni and Y. The results obtained from mathematical calculations are also tested by regression analysis of ΔTx with the compositions of individual elements in the alloy. These results conclude that there is a strong dependence of ΔTx of the alloy on the compositions of the constituting elements in the alloy.

Explaining Variation in Instructional Time: An Application of Quantile Regression

ERIC Educational Resources Information Center

Corey, Douglas Lyman; Phelps, Geoffrey; Ball, Deborah Loewenberg; Demonte, Jenny; Harrison, Delena

2012-01-01

This research is conducted in the context of a large-scale study of three nationally disseminated comprehensive school reform projects (CSRs) and examines how school- and classroom-level factors contribute to variation in instructional time in English language arts and mathematics. When using mean-based OLS regression techniques such as…

Assistive Technologies for Second-Year Statistics Students Who Are Blind

ERIC Educational Resources Information Center

Erhardt, Robert J.; Shuman, Michael P.

2015-01-01

At Wake Forest University, a student who is blind enrolled in a second course in statistics. The course covered simple and multiple regression, model diagnostics, model selection, data visualization, and elementary logistic regression. These topics required that the student both interpret and produce three sets of materials: mathematical writing,…

IPMP Global Fit - A one-step direct data analysis tool for predictive microbiology.

PubMed

Huang, Lihan

2017-12-04

The objective of this work is to develop and validate a unified optimization algorithm for performing one-step global regression analysis of isothermal growth and survival curves for determination of kinetic parameters in predictive microbiology. The algorithm is incorporated with user-friendly graphical interfaces (GUIs) to develop a data analysis tool, the USDA IPMP-Global Fit. The GUIs are designed to guide the users to easily navigate through the data analysis process and properly select the initial parameters for different combinations of mathematical models. The software is developed for one-step kinetic analysis to directly construct tertiary models by minimizing the global error between the experimental observations and mathematical models. The current version of the software is specifically designed for constructing tertiary models with time and temperature as the independent model parameters in the package. The software is tested with a total of 9 different combinations of primary and secondary models for growth and survival of various microorganisms. The results of data analysis show that this software provides accurate estimates of kinetic parameters. In addition, it can be used to improve the experimental design and data collection for more accurate estimation of kinetic parameters. IPMP-Global Fit can be used in combination with the regular USDA-IPMP for solving the inverse problems and developing tertiary models in predictive microbiology. Published by Elsevier B.V.

Study relationship between inorganic and organic coal analysis with gross calorific value by multiple regression and ANFIS

USGS Publications Warehouse

Chelgani, S.C.; Hart, B.; Grady, W.C.; Hower, J.C.

2011-01-01

The relationship between maceral content plus mineral matter and gross calorific value (GCV) for a wide range of West Virginia coal samples (from 6518 to 15330 BTU/lb; 15.16 to 35.66MJ/kg) has been investigated by multivariable regression and adaptive neuro-fuzzy inference system (ANFIS). The stepwise least square mathematical method comparison between liptinite, vitrinite, plus mineral matter as input data sets with measured GCV reported a nonlinear correlation coefficient (R2) of 0.83. Using the same data set the correlation between the predicted GCV from the ANFIS model and the actual GCV reported a R2 value of 0.96. It was determined that the GCV-based prediction methods, as used in this article, can provide a reasonable estimation of GCV. Copyright ?? Taylor & Francis Group, LLC.

A simple method for processing data with least square method

NASA Astrophysics Data System (ADS)

Wang, Chunyan; Qi, Liqun; Chen, Yongxiang; Pang, Guangning

2017-08-01

The least square method is widely used in data processing and error estimation. The mathematical method has become an essential technique for parameter estimation, data processing, regression analysis and experimental data fitting, and has become a criterion tool for statistical inference. In measurement data analysis, the distribution of complex rules is usually based on the least square principle, i.e., the use of matrix to solve the final estimate and to improve its accuracy. In this paper, a new method is presented for the solution of the method which is based on algebraic computation and is relatively straightforward and easy to understand. The practicability of this method is described by a concrete example.

Modeling Student Performance in Mathematics Using Binary Logistic Regression at Selected Secondary Schools a Case Study of Mtwara Municipality and Ilemela District

ERIC Educational Resources Information Center

Mabula, Salyungu

2015-01-01

This study investigated the performance of secondary school students in Mathematics at the Selected Secondary Schools in Mtwara Municipality and Ilemela District by Absenteeism, Conduct, Type of School and Gender as explanatory Factors. The data used in the study was collected from documented records of 250 form three students with 1:1 gender…

Intended and Unintended Effects of State-Mandated High School Science and Mathematics Course Graduation Requirements on Educational Attainment

ERIC Educational Resources Information Center

Plunk, Andrew D.; Tate, William F.; Bierut, Laura J.; Grucza, Richard A.

2014-01-01

Mathematics and science course graduation requirement (CGR) increases in the 1980s and 1990s might have had both intended and unintended consequences. Using logistic regression with Census and American Community Survey (ACS) data (n = 2,892,444), we modeled CGR exposure on (a) high school dropout, (b) beginning college, and (c) obtaining any…

Gender Gap in Mathematics and Physics in Chinese Middle Schools: A Case Study of A Beijing's District

ERIC Educational Resources Information Center

Li, Manli; Zhang, Yu; Wang, Yihan

2017-01-01

This study examines the gender gaps in mathematics and physics in Chinese middle schools. The data is from the Education Bureau management database which includes all middle school students who took high school entrance exam in a district of Beijing from 2006-2013. The ordinary least square model and quantile regression model are applied. This…

Predicting Student Performance in Statewide High-Stakes Tests for Middle School Mathematics Using the Results from Third Party Testing Instruments

ERIC Educational Resources Information Center

Meylani, Rusen; Bitter, Gary G.; Castaneda, Rene

2014-01-01

In this study regression and neural networks based methods are used to predict statewide high-stakes test results for middle school mathematics using the scores obtained from third party tests throughout the school year. Such prediction is of utmost significance for school districts to live up to the state's educational standards mandated by the…

Educational standardization and gender differences in mathematics achievement: A comparative study.

PubMed

Ayalon, Hanna; Livneh, Idit

2013-03-01

We argue that between-country variations in the gender gap in mathematics are related to the level of educational system standardization. In countries with standardized educational systems both genders are exposed to similar knowledge and are motivated to invest in studying mathematics, which leads to similar achievements. We hypothesize that national examinations and between-teacher uniformity in covering major mathematics topics are associated with a smaller gender gap in a country. Based on Trends of International Mathematical and Science Study (TIMSS) 2003, we use multilevel regression models to compare the link of these two factors to the gender gap in 32 countries, controlling for various country characteristics. The use of national examinations and less between-teacher instructional variation prove major factors in reducing the advantage of boys over girls in mathematics scores and in the odds of excelling. Factors representing gender stratification, often analyzed in comparative gender-gap research in mathematics, are at most marginal in respect of the gap. Copyright © 2012 Elsevier Inc. All rights reserved.

Neonatal MRI is associated with future cognition and academic achievement in preterm children

PubMed Central

Spencer-Smith, Megan; Thompson, Deanne K.; Doyle, Lex W.; Inder, Terrie E.; Anderson, Peter J.; Klingberg, Torkel

2015-01-01

School-age children born preterm are particularly at risk for low mathematical achievement, associated with reduced working memory and number skills. Early identification of preterm children at risk for future impairments using brain markers might assist in referral for early intervention. This study aimed to examine the use of neonatal magnetic resonance imaging measures derived from automated methods (Jacobian maps from deformation-based morphometry; fractional anisotropy maps from diffusion tensor images) to predict skills important for mathematical achievement (working memory, early mathematical skills) at 5 and 7 years in a cohort of preterm children using both univariable (general linear model) and multivariable models (support vector regression). Participants were preterm children born <30 weeks’ gestational age and healthy control children born ≥37 weeks’ gestational age at the Royal Women’s Hospital in Melbourne, Australia between July 2001 and December 2003 and recruited into a prospective longitudinal cohort study. At term-equivalent age ( ±2 weeks) 224 preterm and 46 control infants were recruited for magnetic resonance imaging. Working memory and early mathematics skills were assessed at 5 years (n = 195 preterm; n = 40 controls) and 7 years (n = 197 preterm; n = 43 controls). In the preterm group, results identified localized regions around the insula and putamen in the neonatal Jacobian map that were positively associated with early mathematics at 5 and 7 years (both P < 0.05), even after covarying for important perinatal clinical factors using general linear model but not support vector regression. The neonatal Jacobian map showed the same trend for association with working memory at 7 years (models ranging from P = 0.07 to P = 0.05). Neonatal fractional anisotropy was positively associated with working memory and early mathematics at 5 years (both P < 0.001) even after covarying for clinical factors using support vector regression but not general linear model. These significant relationships were not observed in the control group. In summary, we identified, in the preterm brain, regions around the insula and putamen using neonatal deformation-based morphometry, and brain microstructural organization using neonatal diffusion tensor imaging, associated with skills important for childhood mathematical achievement. Results contribute to the growing evidence for the clinical utility of neonatal magnetic resonance imaging for early identification of preterm infants at risk for childhood cognitive and academic impairment. PMID:26329284

A Comparison of Educational "Value-Added" Methodologies for Classifying Teacher Effectiveness: Value Tables vs. Covariate Regression

ERIC Educational Resources Information Center

Dwyer, Theodore J.

2016-01-01

There is a great deal of concern regarding teacher impacts on student achievement being used as a substantial portion of a teacher's performance evaluation. This study investigated the degree of concordance and discordance between mathematics teacher ranking using value tables and covariate regression, which have both been used as measures for…

Calibrated Peer Review for Interpreting Linear Regression Parameters: Results from a Graduate Course

ERIC Educational Resources Information Center

Enders, Felicity B.; Jenkins, Sarah; Hoverman, Verna

2010-01-01

Biostatistics is traditionally a difficult subject for students to learn. While the mathematical aspects are challenging, it can also be demanding for students to learn the exact language to use to correctly interpret statistical results. In particular, correctly interpreting the parameters from linear regression is both a vital tool and a…

Rounding the Regression

ERIC Educational Resources Information Center

Marland, Eric; Bossé, Michael J.; Rhoads, Gregory

2018-01-01

Rounding is a necessary step in many mathematical processes. We are taught early in our education about significant figures and how to properly round a number. So when we are given a data set and asked to find a regression line, we are inclined to offer the line with rounded coefficients to reflect our model. However, the effects are not as…

[Predicting the probability of development and progression of primary open angle glaucoma by regression modeling].

PubMed

Likhvantseva, V G; Sokolov, V A; Levanova, O N; Kovelenova, I V

2018-01-01

Prediction of the clinical course of primary open-angle glaucoma (POAG) is one of the main directions in solving the problem of vision loss prevention and stabilization of the pathological process. Simple statistical methods of correlation analysis show the extent of each risk factor's impact, but do not indicate the total impact of these factors in personalized combinations. The relationships between the risk factors is subject to correlation and regression analysis. The regression equation represents the dependence of the mathematical expectation of the resulting sign on the combination of factor signs. To develop a technique for predicting the probability of development and progression of primary open-angle glaucoma based on a personalized combination of risk factors by linear multivariate regression analysis. The study included 66 patients (23 female and 43 male; 132 eyes) with newly diagnosed primary open-angle glaucoma. The control group consisted of 14 patients (8 male and 6 female). Standard ophthalmic examination was supplemented with biochemical study of lacrimal fluid. Concentration of matrix metalloproteinase MMP-2 and MMP-9 in tear fluid in both eyes was determined using 'sandwich' enzyme-linked immunosorbent assay (ELISA) method. The study resulted in the development of regression equations and step-by-step multivariate logistic models that can help calculate the risk of development and progression of POAG. Those models are based on expert evaluation of clinical and instrumental indicators of hydrodynamic disturbances (coefficient of outflow ease - C, volume of intraocular fluid secretion - F, fluctuation of intraocular pressure), as well as personalized morphometric parameters of the retina (central retinal thickness in the macular area) and concentration of MMP-2 and MMP-9 in the tear film. The newly developed regression equations are highly informative and can be a reliable tool for studying of the influence vector and assessment of pathogenic potential of the independent risk factors in specific personalized combinations.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

What Is the Long-Run Impact of Learning Mathematics During Preschool?

PubMed

Watts, Tyler W; Duncan, Greg J; Clements, Douglas H; Sarama, Julie

2018-03-01

The current study estimated the causal links between preschool mathematics learning and late elementary school mathematics achievement using variation in treatment assignment to an early mathematics intervention as an instrument for preschool mathematics change. Estimates indicate (n = 410) that a standard deviation of intervention-produced change at age 4 is associated with a 0.24-SD gain in achievement in late elementary school. This impact is approximately half the size of the association produced by correlational models relating later achievement to preschool math change, and is approximately 35% smaller than the effect reported by highly controlled ordinary least squares (OLS) regression models (Claessens et al., 2009; Watts et al., ) using national data sets. Implications for developmental theory and practice are discussed. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Dealing with dissatisfaction in mathematical modelling to integrate QFD and Kano’s model

NASA Astrophysics Data System (ADS)

Retno Sari Dewi, Dian; Debora, Joana; Edy Sianto, Martinus

2017-12-01

The purpose of the study is to implement the integration of Quality Function Deployment (QFD) and Kano’s Model into mathematical model. Voice of customer data in QFD was collected using questionnaire and the questionnaire was developed based on Kano’s model. Then the operational research methodology was applied to build the objective function and constraints in the mathematical model. The relationship between voice of customer and engineering characteristics was modelled using linier regression model. Output of the mathematical model would be detail of engineering characteristics. The objective function of this model is to maximize satisfaction and minimize dissatisfaction as well. Result of this model is 62% .The major contribution of this research is to implement the existing mathematical model to integrate QFD and Kano’s Model in the case study of shoe cabinet.

Persistence in STEM: An investigation of the relationship between high school experiences in science and mathematics and college degree completion in STEM fields

NASA Astrophysics Data System (ADS)

Maltese, Adam V.

While the number of Bachelor's degrees awarded annually has nearly tripled over the past 40 years (NSF, 2008), the same cannot be said for degrees in the STEM (science, technology, engineering and mathematics) fields. The Bureau of Labor Statistics projects that by the year 2014 the combination of new positions and retirements will lead to 2 million job openings in STEM (BLS, 2005). Thus, the research questions I sought to answer with this study were: (1)What are the most common enrollment patterns for students who enter into and exit from the STEM pipeline during high school and college? (2) Controlling for differences in student background and early interest in STEM careers, what are the high school science and mathematics classroom experiences that characterize student completion of a college major in STEM? Using data from NELS:88 I analyzed descriptive statistics and completed logistic regressions to gain an understanding of factors related to student persistence in STEM. Approximately 4700 students with transcript records and who participated in all survey rounds were included in the analyses. The results of the descriptive analysis demonstrated that most students who went on to complete majors in STEM completed at least three or four years of STEM courses during high school, and enrolled in advanced high school mathematics and science courses at higher rates. At almost every pipeline checkpoint indicators of the level of coursework and achievement were significant in predicting student completion of a STEM degree. The results also support previous research that showed demographic variables have little effect on persistence once the sample is limited to those who have the intrinsic ability and desire to complete a college degree. The most significant finding is that measures of student interest and engagement in science and mathematics were significant in predicting completion of a STEM degree, above and beyond the effects of course enrollment and performance. A final analysis, which involved the comparison of descriptive statistics for students who switched into and out of the STEM pipeline during high school, suggested that attitudes toward mathematics and science play a major role in choices regarding pipeline persistence.

Issues and Importance of "Good" Starting Points for Nonlinear Regression for Mathematical Modeling with Maple: Basic Model Fitting to Make Predictions with Oscillating Data

ERIC Educational Resources Information Center

Fox, William

2012-01-01

The purpose of our modeling effort is to predict future outcomes. We assume the data collected are both accurate and relatively precise. For our oscillating data, we examined several mathematical modeling forms for predictions. We also examined both ignoring the oscillations as an important feature and including the oscillations as an important…

[Mathematical modeling for conditionality of cardiovascular disease by housing conditions].

PubMed

Meshkov, N A

2014-01-01

There was studied the influence of living conditions (housing area per capita, availability of housing water supply, sewerage and central heating) on the morbidity of the cardiovascular diseases in child and adult population. With the method of regression analysis the morbidity rate was established to significantly decrease with the increase in the area of housing, constructed models are statistically significant, respectively, p = 0.01 and p = 0.02. There was revealed the relationship of the morbidity rate of cardiovascular diseases in children and adults with the supply with housing central heating (p = 0.02 and p = 0.009).

Predictive Relation between Early Numerical Competencies and Mathematics Achievement in First Grade Portuguese Children.

PubMed

Marcelino, Lilia; de Sousa, Óscar; Lopes, António

2017-01-01

Early numerical competencies (ENC) (counting, number relations, and basic arithmetic operations) have a central position in the initial learning of mathematics, and their assessment is useful for predicting later mathematics achievement. Using a regression model, this study aims to analyze the correlational and predictive evidence between ENC and mathematics achievement in first grade Portuguese children ( n = 123). The children's ENC were examined at the point of school entry. Three criterion groups (low, moderate, and high ENC) were formed based on the results of the early numerical brief screener and mathematics achievement measured at the end of first grade. The following hypotheses were tested: children who started first grade with low numerical competencies remained low mathematics achievement at the end of first grade; and children who started with high numerical competencies, finished the first grade with high mathematics achievement. The results showed that ENC contributed to a significant amount of explained variance in mathematics achievement at the end of the first grade. Children with low numerical competencies performed lower than children with moderate and high numerical competencies. Findings suggest that ENC are meaningful for predicting first-grade mathematics difficulties.

Predictive Relation between Early Numerical Competencies and Mathematics Achievement in First Grade Portuguese Children

PubMed Central

Marcelino, Lilia; de Sousa, Óscar; Lopes, António

2017-01-01

Early numerical competencies (ENC) (counting, number relations, and basic arithmetic operations) have a central position in the initial learning of mathematics, and their assessment is useful for predicting later mathematics achievement. Using a regression model, this study aims to analyze the correlational and predictive evidence between ENC and mathematics achievement in first grade Portuguese children (n = 123). The children’s ENC were examined at the point of school entry. Three criterion groups (low, moderate, and high ENC) were formed based on the results of the early numerical brief screener and mathematics achievement measured at the end of first grade. The following hypotheses were tested: children who started first grade with low numerical competencies remained low mathematics achievement at the end of first grade; and children who started with high numerical competencies, finished the first grade with high mathematics achievement. The results showed that ENC contributed to a significant amount of explained variance in mathematics achievement at the end of the first grade. Children with low numerical competencies performed lower than children with moderate and high numerical competencies. Findings suggest that ENC are meaningful for predicting first-grade mathematics difficulties. PMID:28713308

Visual short term memory related brain activity predicts mathematical abilities.

PubMed

Boulet-Craig, Aubrée; Robaey, Philippe; Lacourse, Karine; Jerbi, Karim; Oswald, Victor; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Jolicoeur, Pierre; Lippé, Sarah

2017-07-01

Previous research suggests visual short-term memory (VSTM) capacity and mathematical abilities are significantly related. Moreover, both processes activate similar brain regions within the parietal cortex, in particular, the intraparietal sulcus; however, it is still unclear whether the neuronal underpinnings of VSTM directly correlate with mathematical operation and reasoning abilities. The main objective was to investigate the association between parieto-occipital brain activity during the retention period of a VSTM task and performance in mathematics. The authors measured mathematical abilities and VSTM capacity as well as brain activity during memory maintenance using magnetoencephalography (MEG) in 19 healthy adult participants. Event-related magnetic fields (ERFs) were computed on the MEG data. Linear regressions were used to estimate the strength of the relation between VSTM related brain activity and mathematical abilities. The amplitude of parieto-occipital cerebral activity during the retention of visual information was related to performance in 2 standardized mathematical tasks: mathematical reasoning and calculation fluency. The findings show that brain activity during retention period of a VSTM task is associated with mathematical abilities. Contributions of VSTM processes to numerical cognition should be considered in cognitive interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Analytical and regression models of glass rod drawing process

NASA Astrophysics Data System (ADS)

Alekseeva, L. B.

2018-03-01

The process of drawing glass rods (light guides) is being studied. The parameters of the process affecting the quality of the light guide have been determined. To solve the problem, mathematical models based on general equations of continuum mechanics are used. The conditions for the stable flow of the drawing process have been found, which are determined by the stability of the motion of the glass mass in the formation zone to small uncontrolled perturbations. The sensitivity of the formation zone to perturbations of the drawing speed and viscosity is estimated. Experimental models of the drawing process, based on the regression analysis methods, have been obtained. These models make it possible to customize a specific production process to obtain light guides of the required quality. They allow one to find the optimum combination of process parameters in the chosen area and to determine the required accuracy of maintaining them at a specified level.

Modeling the language learning strategies and English language proficiency of pre-university students in UMS: A case study

NASA Astrophysics Data System (ADS)

Kiram, J. J.; Sulaiman, J.; Swanto, S.; Din, W. A.

2015-10-01

This study aims to construct a mathematical model of the relationship between a student's Language Learning Strategy usage and English Language proficiency. Fifty-six pre-university students of University Malaysia Sabah participated in this study. A self-report questionnaire called the Strategy Inventory for Language Learning was administered to them to measure their language learning strategy preferences before they sat for the Malaysian University English Test (MUET), the results of which were utilised to measure their English language proficiency. We attempted the model assessment specific to Multiple Linear Regression Analysis subject to variable selection using Stepwise regression. We conducted various assessments to the model obtained, including the Global F-test, Root Mean Square Error and R-squared. The model obtained suggests that not all language learning strategies should be included in the model in an attempt to predict Language Proficiency.

Simultaneous spectrophotometric determination of salbutamol and bromhexine in tablets.

PubMed

Habib, I H I; Hassouna, M E M; Zaki, G A

2005-03-01

Typical anti-mucolytic drugs called salbutamol hydrochloride and bromhexine sulfate encountered in tablets were determined simultaneously either by using linear regression at zero-crossing wavelengths of the first derivation of UV-spectra or by application of multiple linear partial least squares regression method. The results obtained by the two proposed mathematical methods were compared with those obtained by the HPLC technique.

A Method for Calculating the Probability of Successfully Completing a Rocket Propulsion Ground Test

NASA Technical Reports Server (NTRS)

Messer, Bradley

2007-01-01

Propulsion ground test facilities face the daily challenge of scheduling multiple customers into limited facility space and successfully completing their propulsion test projects. Over the last decade NASA s propulsion test facilities have performed hundreds of tests, collected thousands of seconds of test data, and exceeded the capabilities of numerous test facility and test article components. A logistic regression mathematical modeling technique has been developed to predict the probability of successfully completing a rocket propulsion test. A logistic regression model is a mathematical modeling approach that can be used to describe the relationship of several independent predictor variables X(sub 1), X(sub 2),.., X(sub k) to a binary or dichotomous dependent variable Y, where Y can only be one of two possible outcomes, in this case Success or Failure of accomplishing a full duration test. The use of logistic regression modeling is not new; however, modeling propulsion ground test facilities using logistic regression is both a new and unique application of the statistical technique. Results from this type of model provide project managers with insight and confidence into the effectiveness of rocket propulsion ground testing.

Comparison of mathematic models for assessment of glomerular filtration rate with electron-beam CT in pigs.

PubMed

Daghini, Elena; Juillard, Laurent; Haas, John A; Krier, James D; Romero, Juan C; Lerman, Lilach O

2007-02-01

To prospectively compare in pigs three mathematic models for assessment of glomerular filtration rate (GFR) on electron-beam (EB) computed tomographic (CT) images, with concurrent inulin clearance serving as the reference standard. This study was approved by the institutional animal care and use committee. Inulin clearance was measured in nine pigs (18 kidneys) and compared with single-kidney GFR assessed from renal time-attenuation curves (TACs) obtained with EB CT before and after infusion of the vasodilator acetylcholine. CT-derived GFR was calculated with the original and modified Patlak methods and with previously validated extended gamma variate modeling of first-pass cortical TACs. Statistical analysis was performed to assess correlation between CT methods and inulin clearance for estimation of GFR with least-squares regression analysis and Bland-Altman graphical representation. Comparisons within groups were performed with a paired t test. GFR assessed with the original Patlak method indicated poor correlation with inulin clearance, whereas GFR assessed with the modified Patlak method (P < .001, r = 0.75) and with gamma variate modeling (P < .001, r = 0.79) correlated significantly with inulin clearance and indicated an increase in response to acetylcholine. CT-derived estimates of GFR can be significantly improved by modifications in image analysis methods (eg, use of a cortical region of interest). (c) RSNA, 2007.

Neural Network and Regression Approximations in High Speed Civil Transport Aircraft Design Optimization

NASA Technical Reports Server (NTRS)

Patniak, Surya N.; Guptill, James D.; Hopkins, Dale A.; Lavelle, Thomas M.

1998-01-01

Nonlinear mathematical-programming-based design optimization can be an elegant method. However, the calculations required to generate the merit function, constraints, and their gradients, which are frequently required, can make the process computational intensive. The computational burden can be greatly reduced by using approximating analyzers derived from an original analyzer utilizing neural networks and linear regression methods. The experience gained from using both of these approximation methods in the design optimization of a high speed civil transport aircraft is the subject of this paper. The Langley Research Center's Flight Optimization System was selected for the aircraft analysis. This software was exercised to generate a set of training data with which a neural network and a regression method were trained, thereby producing the two approximating analyzers. The derived analyzers were coupled to the Lewis Research Center's CometBoards test bed to provide the optimization capability. With the combined software, both approximation methods were examined for use in aircraft design optimization, and both performed satisfactorily. The CPU time for solution of the problem, which had been measured in hours, was reduced to minutes with the neural network approximation and to seconds with the regression method. Instability encountered in the aircraft analysis software at certain design points was also eliminated. On the other hand, there were costs and difficulties associated with training the approximating analyzers. The CPU time required to generate the input-output pairs and to train the approximating analyzers was seven times that required for solution of the problem.

Sparse Logistic Regression for Diagnosis of Liver Fibrosis in Rat by Using SCAD-Penalized Likelihood

PubMed Central

Yan, Fang-Rong; Lin, Jin-Guan; Liu, Yu

2011-01-01

The objective of the present study is to find out the quantitative relationship between progression of liver fibrosis and the levels of certain serum markers using mathematic model. We provide the sparse logistic regression by using smoothly clipped absolute deviation (SCAD) penalized function to diagnose the liver fibrosis in rats. Not only does it give a sparse solution with high accuracy, it also provides the users with the precise probabilities of classification with the class information. In the simulative case and the experiment case, the proposed method is comparable to the stepwise linear discriminant analysis (SLDA) and the sparse logistic regression with least absolute shrinkage and selection operator (LASSO) penalty, by using receiver operating characteristic (ROC) with bayesian bootstrap estimating area under the curve (AUC) diagnostic sensitivity for selected variable. Results show that the new approach provides a good correlation between the serum marker levels and the liver fibrosis induced by thioacetamide (TAA) in rats. Meanwhile, this approach might also be used in predicting the development of liver cirrhosis. PMID:21716672

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

Dough performance, quality and shelf life of flat bread supplemented with fractions of germinated date seed.

PubMed

Hejri-Zarifi, Sudiyeh; Ahmadian-Kouchaksaraei, Zahra; Pourfarzad, Amir; Khodaparast, Mohammad Hossein Haddad

2014-12-01

Germinated palm date seeds were milled into two fractions: germ and residue. Dough rheological characteristics, baking (specific volume and sensory evaluation), and textural properties (at first day and during storage for 5 days) were determined in Barbari flat bread. Germ and residue fractions were incorporated at various levels ranged in 0.5-3 g/100 g of wheat flour. Water absorption, arrival time and gelatination temperature were decreased by germ fraction but accompanied by an increasing effect on the mixing tolerance index and degree of softening in most levels. Although improvement in dough stability was monitored but specific volume of bread was not affected by both fractions. Texture analysis of bread samples during 5 days of storage indicated that both fractions of germinated date seeds were able to diminish bread staling. Avrami non-linear regression equation was chosen as useful mathematical model to properly study bread hardening kinetics. In addition, principal component analysis (PCA) allowed discriminating among dough and bread specialties. Partial least squares regression (PLSR) models were applied to determine the relationships between sensory and instrumental data.

New method for calculating a mathematical expression for streamflow recession

USGS Publications Warehouse

Rutledge, Albert T.

1991-01-01

An empirical method has been devised to calculate the master recession curve, which is a mathematical expression for streamflow recession during times of negligible direct runoff. The method is based on the assumption that the storage-delay factor, which is the time per log cycle of streamflow recession, varies linearly with the logarithm of streamflow. The resulting master recession curve can be nonlinear. The method can be executed by a computer program that reads a data file of daily mean streamflow, then allows the user to select several near-linear segments of streamflow recession. The storage-delay factor for each segment is one of the coefficients of the equation that results from linear least-squares regression. Using results for each recession segment, a mathematical expression of the storage-delay factor as a function of the log of streamflow is determined by linear least-squares regression. The master recession curve, which is a second-order polynomial expression for time as a function of log of streamflow, is then derived using the coefficients of this function.

Which statistics should tropical biologists learn?

PubMed

Loaiza Velásquez, Natalia; González Lutz, María Isabel; Monge-Nájera, Julián

2011-09-01

Tropical biologists study the richest and most endangered biodiversity in the planet, and in these times of climate change and mega-extinctions, the need for efficient, good quality research is more pressing than in the past. However, the statistical component in research published by tropical authors sometimes suffers from poor quality in data collection; mediocre or bad experimental design and a rigid and outdated view of data analysis. To suggest improvements in their statistical education, we listed all the statistical tests and other quantitative analyses used in two leading tropical journals, the Revista de Biología Tropical and Biotropica, during a year. The 12 most frequent tests in the articles were: Analysis of Variance (ANOVA), Chi-Square Test, Student's T Test, Linear Regression, Pearson's Correlation Coefficient, Mann-Whitney U Test, Kruskal-Wallis Test, Shannon's Diversity Index, Tukey's Test, Cluster Analysis, Spearman's Rank Correlation Test and Principal Component Analysis. We conclude that statistical education for tropical biologists must abandon the old syllabus based on the mathematical side of statistics and concentrate on the correct selection of these and other procedures and tests, on their biological interpretation and on the use of reliable and friendly freeware. We think that their time will be better spent understanding and protecting tropical ecosystems than trying to learn the mathematical foundations of statistics: in most cases, a well designed one-semester course should be enough for their basic requirements.

An empirical investigation of differences between mathematics specialists and non-specialists at the high school level in Cyprus: A Logistic regression Approach

NASA Astrophysics Data System (ADS)

Papanastasiou, Elena C.; Zembylas, Michalinos

2006-12-01

AN EMPIRICAL INVESTIGATION OF DIFFERENCES BETWEEN MATHEMATICS SPECIALISTS AND NON-SPECIALISTS AT THE HIGH-SCHOOL LEVEL in Cyprus - The data obtained from high-school seniors for the Third International Mathematics and Science Study (TIMSS) for the country of Cyprus appear to be contradictory. Although Cypriot students did not perform well in mathematics in elementary school, middle school, and in the non-advanced sectors of high school, students in advanced mathematics courses in high school managed to perform exceptionally well. In seeking to account for this apparent disparity, the present study examines the differences between mathematics specialists and non-specialists at the high-school level and discusses the implications that these have for teaching practice. It shows how students educated in an environment that might not be optimal for producing high-achieving students in mathematics and science in elementary and middle school (according to the TIMSS) might nonetheless manage to excel in these fields at the end of their schooling. In conclusion, the authors address the implications of their study for similar educational systems in other developing countries.

Sampling and sensitivity analyses tools (SaSAT) for computational modelling

PubMed Central

Hoare, Alexander; Regan, David G; Wilson, David P

2008-01-01

SaSAT (Sampling and Sensitivity Analysis Tools) is a user-friendly software package for applying uncertainty and sensitivity analyses to mathematical and computational models of arbitrary complexity and context. The toolbox is built in Matlab®, a numerical mathematical software package, and utilises algorithms contained in the Matlab® Statistics Toolbox. However, Matlab® is not required to use SaSAT as the software package is provided as an executable file with all the necessary supplementary files. The SaSAT package is also designed to work seamlessly with Microsoft Excel but no functionality is forfeited if that software is not available. A comprehensive suite of tools is provided to enable the following tasks to be easily performed: efficient and equitable sampling of parameter space by various methodologies; calculation of correlation coefficients; regression analysis; factor prioritisation; and graphical output of results, including response surfaces, tornado plots, and scatterplots. Use of SaSAT is exemplified by application to a simple epidemic model. To our knowledge, a number of the methods available in SaSAT for performing sensitivity analyses have not previously been used in epidemiological modelling and their usefulness in this context is demonstrated. PMID:18304361

Mathematical and computational model for the analysis of micro hybrid rocket motor

NASA Astrophysics Data System (ADS)

Stoia-Djeska, Marius; Mingireanu, Florin

2012-11-01

The hybrid rockets use a two-phase propellant system. In the present work we first develop a simplified model of the coupling of the hybrid combustion process with the complete unsteady flow, starting from the combustion port and ending with the nozzle. The physical and mathematical model are adapted to the simulations of micro hybrid rocket motors. The flow model is based on the one-dimensional Euler equations with source terms. The flow equations and the fuel regression rate law are solved in a coupled manner. The platform of the numerical simulations is an implicit fourth-order Runge-Kutta second order cell-centred finite volume method. The numerical results obtained with this model show a good agreement with published experimental and numerical results. The computational model developed in this work is simple, computationally efficient and offers the advantage of taking into account a large number of functional and constructive parameters that are used by the engineers.

Divorce, approaches to learning, and children's academic achievement: a longitudinal analysis of mediated and moderated effects.

PubMed

Anthony, Christopher J; DiPerna, James Clyde; Amato, Paul R

2014-06-01

Data from the Early Childhood Longitudinal Study--Kindergarten Cohort (ECLS-K) were used to test the hypothesis that approaches to learning (ATL) mediates the link between parental divorce and academic achievement. Fixed effects regression was utilized to test for mediation, and subsequent moderation analyses examining gender and age at time of divorce also were conducted. Results indicated that divorce was associated with less growth in test scores and that ATL mediated 18% and 12% of this association in reading and mathematics respectively. Parental divorce also was associated with larger negative effects for children who experienced divorce at an older age as well as for girls' mathematics test scores. These findings contribute to the understanding of the impact of parental divorce on children's academic achievement and underscore the importance of focusing on the variability of child outcomes following parental divorce. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Combining ultrasonography and noncontrast helical computerized tomography to evaluate Holmium laser lithotripsy

PubMed Central

Mi, Jia; Li, Jie; Zhang, Qinglu; Wang, Xing; Liu, Hongyu; Cao, Yanlu; Liu, Xiaoyan; Sun, Xiao; Shang, Mengmeng; Liu, Qing

2016-01-01

Abstract The purpose of the study was to establish a mathematical model for correlating the combination of ultrasonography and noncontrast helical computerized tomography (NCHCT) with the total energy of Holmium laser lithotripsy. In this study, from March 2013 to February 2014, 180 patients with single urinary calculus were examined using ultrasonography and NCHCT before Holmium laser lithotripsy. The calculus location and size, acoustic shadowing (AS) level, twinkling artifact intensity (TAI), and CT value were all documented. The total energy of lithotripsy (TEL) and the calculus composition were also recorded postoperatively. Data were analyzed using Spearman's rank correlation coefficient, with the SPSS 17.0 software package. Multiple linear regression was also used for further statistical analysis. A significant difference in the TEL was observed between renal calculi and ureteral calculi (r = –0.565, P < 0.001), and there was a strong correlation between the calculus size and the TEL (r = 0.675, P < 0.001). The difference in the TEL between the calculi with and without AS was highly significant (r = 0.325, P < 0.001). The CT value of the calculi was significantly correlated with the TEL (r = 0.386, P < 0.001). A correlation between the TAI and TEL was also observed (r = 0.391, P < 0.001). Multiple linear regression analysis revealed that the location, size, and TAI of the calculi were related to the TEL, and the location and size were statistically significant predictors (adjusted r2 = 0.498, P < 0.001). A mathematical model correlating the combination of ultrasonography and NCHCT with TEL was established; this model may provide a foundation to guide the use of energy in Holmium laser lithotripsy. The TEL can be estimated by the location, size, and TAI of the calculus. PMID:27930563

Completing the Remedial Sequence and College-Level Credit-Bearing Math: Comparing Binary, Cumulative, and Continuation Ratio Logistic Regression Models

ERIC Educational Resources Information Center

Davidson, J. Cody

2016-01-01

Mathematics is the most common subject area of remedial need and the majority of remedial math students never pass a college-level credit-bearing math class. The majorities of studies that investigate this phenomenon are conducted at community colleges and use some type of regression model; however, none have used a continuation ratio model. The…

Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks.

PubMed

Duda, Piotr; Jaworski, Maciej; Rutkowski, Leszek

2018-03-01

One of the greatest challenges in data mining is related to processing and analysis of massive data streams. Contrary to traditional static data mining problems, data streams require that each element is processed only once, the amount of allocated memory is constant and the models incorporate changes of investigated streams. A vast majority of available methods have been developed for data stream classification and only a few of them attempted to solve regression problems, using various heuristic approaches. In this paper, we develop mathematically justified regression models working in a time-varying environment. More specifically, we study incremental versions of generalized regression neural networks, called IGRNNs, and we prove their tracking properties - weak (in probability) and strong (with probability one) convergence assuming various concept drift scenarios. First, we present the IGRNNs, based on the Parzen kernels, for modeling stationary systems under nonstationary noise. Next, we extend our approach to modeling time-varying systems under nonstationary noise. We present several types of concept drifts to be handled by our approach in such a way that weak and strong convergence holds under certain conditions. Finally, in the series of simulations, we compare our method with commonly used heuristic approaches, based on forgetting mechanism or sliding windows, to deal with concept drift. Finally, we apply our concept in a real life scenario solving the problem of currency exchange rates prediction.

The contribution of parent-child numeracy activities to young Chinese children's mathematical ability.

PubMed

Huang, Qi; Zhang, Xiao; Liu, Yingyi; Yang, Wen; Song, Zhanmei

2017-09-01

A growing body of recent research has shown that parent-child mathematical activities have a strong effect on children's mathematical learning. However, this research was conducted predominantly in Western societies and focused mainly on mothers' involvement in such activities. This study aimed to examine both mother-child and father-child numeracy activities in Hong Kong Chinese families and both parents' unique roles in predicting young Chinese children's mathematics ability. A sample of 104 Hong Kong Chinese children aged approximately 5 years and their mothers and fathers participated in this study. Mothers and fathers independently reported the frequency of their own numeracy activities with their children. Children were assessed individually using two measures of mathematical ability. Hierarchical regression models were used to investigate the contribution of parent-child numeracy activities to children's mathematical ability. Mothers' participation in number skill activities and fathers' participation in number game and application activities significantly predicted their children's mathematical performance even after controlling for background variables and children's language ability. This study extends previous research with a sample of Chinese kindergarten children and shows that parent-child numeracy activities are related to young children's mathematical ability. The findings highlight the important roles that mothers and fathers play in their young children's mathematical learning. © 2017 The British Psychological Society.

Two Enhancements of the Logarithmic Least-Squares Method for Analyzing Subjective Comparisons

DTIC Science & Technology

1989-03-25

error term. 1 For this model, the total sum of squares ( SSTO ), defined as n 2 SSTO = E (yi y) i=1 can be partitioned into error and regression sums...of the regression line around the mean value. Mathematically, for the model given by equation A.4, SSTO = SSE + SSR (A.6) A-4 where SSTO is the total...sum of squares (i.e., the variance of the yi’s), SSE is error sum of squares, and SSR is the regression sum of squares. SSTO , SSE, and SSR are given

Predicting academic self-handicapping in different age groups: the role of personal achievement goals and social goals.

PubMed

Leondari, Angeliki; Gonida, Eleftheria

2007-09-01

Academic self-handicapping refers to the use of impediments to successful performance on academic tasks. Previous studies have shown that it is related to personal achievement goals. A performance goal orientation is a positive predictor of self-handicapping, whereas a task goal orientation is unrelated to self-handicapping. The aim of this study was to examine the relationship between academic self-handicapping, goal orientations (task, performance-approach, performance-avoidance), social goals, future consequences and achievement in mathematics. An additional aim was to investigate grade-level and gender differences in relation to academic self-handicapping. Participants were 702 upper elementary, junior and senior high school students with approximately equal numbers of girls and boys. There were no grade-level or gender differences as regards the use of self-handicapping. The correlations among the variables revealed that, when the whole sample was considered, self-handicapping was positively related to performance goal orientations and pleasing significant others and negatively to achievement in mathematics. The results of hierarchical regression analysis showed that, in upper elementary and junior high schools, the association between achievement in mathematics and self-handicapping was mediated by performance-avoidance goals. In senior high school, only task goal orientation was a negative predictor of self-handicapping.

Clones in the Classroom: A Daily Diary Study of the Nonshared Environmental Relationship Between Monozygotic Twin Differences in School Experience and Achievement

PubMed Central

Asbury, Kathryn; Almeida, David; Hibel, Jacob; Harlaar, Nicole; Plomin, Robert

2010-01-01

Do genetically identical children experience the same classroom differently? Are nonshared classroom experiences associated with differences in achievement? We designed a telephone diary measure which we administered every school day for 2 weeks to 122 10-year-olds in 61 monozygotic (MZ) twin pairs. Each pair shared genes, a classroom, peers and a teacher. We found that MZ twins did experience their classrooms differently (rMZ < 0.65 for all measures of classroom experience). Furthermore, MZ differences in peer problems were significantly associated with MZ differences in Mathematics achievement (ES = 8%); differences in positivity about school were significantly associated with differences in Mathematics (ES = 15%) and Science (ES = 8%) achievement; and differences in ‘flow’ in Science lessons were associated with differences in Science achievement (ES = 12%). In a multiple regression analysis, MZ differences in positivity about school significantly predicted MZ differences in Mathematics achievement (R2 = 0.16, p < .01) and MZ differences in ‘flow’ in Science significantly predicted MZ differences in Science achievement (R2 = 0.10, p < .05). These results indicate that MZ twins experience the classroom differently and that differences in their experience are associated with differences in their achievement. PMID:19016614

Contributions of Executive Function and Spatial Skills to Preschool Mathematics Achievement

PubMed Central

Verdine, Brian N.; Irwin, Casey M.; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

2014-01-01

Early mathematics achievement is highly predictive of later mathematics performance. Here we investigate the influence of executive function (EF) and spatial skills, two generalizable skills often overlooked in mathematics curricula, on mathematics performance in preschoolers. Children (N = 44) of varying socio-economic status (SES) levels were assessed at age three on a new assessment of spatial skill (Test of Spatial Assembly, TOSA) and a vocabulary measure (the PPVT-4). The same children were tested at age four on the Beery Test of Visual-Motor Integration (VMI), as well as measures of EF, and mathematics. The TOSA was created specifically as an assessment for 3-year-olds, allowing the investigation of links between spatial, EF, and mathematical skills earlier than previously possible. Results of a hierarchical regression indicate that EF and spatial skills predict 70% of the variance in mathematics performance without an explicit math test, EF is an important predictor of math performance as prior research suggested, and spatial skills uniquely predict 27% of the variance in mathematics skills. Additional research is needed to understand if EF is truly malleable and whether EF and spatial skills may be leveraged to support early mathematics skills, especially for lower-SES children who are already falling behind in these skill areas by ages 3 and 4. These findings indicate that both skills are part of an important foundation for mathematics performance and may represent pathways for improving school readiness for mathematics. PMID:24874186

The relative importance of two different mathematical abilities to mathematical achievement.

PubMed

Nunes, Terezinha; Bryant, Peter; Barros, Rossana; Sylva, Kathy

2012-03-01

Two distinct abilities, mathematical reasoning and arithmetic skill, might make separate and specific contributions to mathematical achievement. However, there is little evidence to inform theory and educational practice on this matter. The aims of this study were (1) to assess whether mathematical reasoning and arithmetic make independent contributions to the longitudinal prediction of mathematical achievement over 5 years and (2) to test the specificity of this prediction. Data from Avon Longitudinal Study of Parents and Children (ALSPAC) were available on 2,579 participants for analyses of KS2 achievement and on 1,680 for the analyses of KS3 achievement. Hierarchical regression analyses were used to assess the independence and specificity of the contribution of mathematical reasoning and arithmetic skill to the prediction of achievement in KS2 and KS3 mathematics, science, and English. Age, intelligence, and working memory (WM) were controls in these analyses. Mathematical reasoning and arithmetic did make independent contributions to the prediction of mathematical achievement; mathematical reasoning was by far the stronger predictor of the two. These predictions were specific in so far as these measures were more strongly related to mathematics than to science or English. Intelligence and WM were non-specific predictors; intelligence contributed more to the prediction of science than of maths, and WM predicted maths and English equally well. There is clear justification for making a distinction between mathematical reasoning and arithmetic skills. The implication is that schools must plan explicitly to improve mathematical reasoning as well as arithmetic skills. ©2011 The British Psychological Society.

Temperature-viscosity models reassessed.

PubMed

Peleg, Micha

2017-05-04

The temperature effect on viscosity of liquid and semi-liquid foods has been traditionally described by the Arrhenius equation, a few other mathematical models, and more recently by the WLF and VTF (or VFT) equations. The essence of the Arrhenius equation is that the viscosity is proportional to the absolute temperature's reciprocal and governed by a single parameter, namely, the energy of activation. However, if the absolute temperature in K in the Arrhenius equation is replaced by T + b where both T and the adjustable b are in °C, the result is a two-parameter model, which has superior fit to experimental viscosity-temperature data. This modified version of the Arrhenius equation is also mathematically equal to the WLF and VTF equations, which are known to be equal to each other. Thus, despite their dissimilar appearances all three equations are essentially the same model, and when used to fit experimental temperature-viscosity data render exactly the same very high regression coefficient. It is shown that three new hybrid two-parameter mathematical models, whose formulation bears little resemblance to any of the conventional models, can also have excellent fit with r 2 ∼ 1. This is demonstrated by comparing the various models' regression coefficients to published viscosity-temperature relationships of 40% sucrose solution, soybean oil, and 70°Bx pear juice concentrate at different temperature ranges. Also compared are reconstructed temperature-viscosity curves using parameters calculated directly from 2 or 3 data points and fitted curves obtained by nonlinear regression using a larger number of experimental viscosity measurements.

Application of mathematical model methods for optimization tasks in construction materials technology

NASA Astrophysics Data System (ADS)

Fomina, E. V.; Kozhukhova, N. I.; Sverguzova, S. V.; Fomin, A. E.

2018-05-01

In this paper, the regression equations method for design of construction material was studied. Regression and polynomial equations representing the correlation between the studied parameters were proposed. The logic design and software interface of the regression equations method focused on parameter optimization to provide the energy saving effect at the stage of autoclave aerated concrete design considering the replacement of traditionally used quartz sand by coal mining by-product such as argillite. The mathematical model represented by a quadric polynomial for the design of experiment was obtained using calculated and experimental data. This allowed the estimation of relationship between the composition and final properties of the aerated concrete. The surface response graphically presented in a nomogram allowed the estimation of concrete properties in response to variation of composition within the x-space. The optimal range of argillite content was obtained leading to a reduction of raw materials demand, development of target plastic strength of aerated concrete as well as a reduction of curing time before autoclave treatment. Generally, this method allows the design of autoclave aerated concrete with required performance without additional resource and time costs.

Statistical considerations in the development of injury risk functions.

PubMed

McMurry, Timothy L; Poplin, Gerald S

2015-01-01

We address 4 frequently misunderstood and important statistical ideas in the construction of injury risk functions. These include the similarities of survival analysis and logistic regression, the correct scale on which to construct pointwise confidence intervals for injury risk, the ability to discern which form of injury risk function is optimal, and the handling of repeated tests on the same subject. The statistical models are explored through simulation and examination of the underlying mathematics. We provide recommendations for the statistically valid construction and correct interpretation of single-predictor injury risk functions. This article aims to provide useful and understandable statistical guidance to improve the practice in constructing injury risk functions.

Predicting Success in Psychological Statistics Courses.

PubMed

Lester, David

2016-06-01

Many students perform poorly in courses on psychological statistics, and it is useful to be able to predict which students will have difficulties. In a study of 93 undergraduates enrolled in Statistical Methods (18 men, 75 women; M age = 22.0 years, SD = 5.1), performance was significantly associated with sex (female students performed better) and proficiency in algebra in a linear regression analysis. Anxiety about statistics was not associated with course performance, indicating that basic mathematical skills are the best correlate for performance in statistics courses and can usefully be used to stream students into classes by ability. © The Author(s) 2016.

The Research of Regression Method for Forecasting Monthly Electricity Sales Considering Coupled Multi-factor

NASA Astrophysics Data System (ADS)

Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui

2018-01-01

The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.

A Meta-Analysis of Mathematics and Working Memory: Moderating Effects of Working Memory Domain, Type of Mathematics Skill, and Sample Characteristics

ERIC Educational Resources Information Center

Peng, Peng; Namkung, Jessica; Barnes, Marcia; Sun, Congying

2016-01-01

The purpose of this meta-analysis was to determine the relation between mathematics and working memory (WM) and to identify possible moderators of this relation including domains of WM, types of mathematics skills, and sample type. A meta-analysis of 110 studies with 829 effect sizes found a significant medium correlation of mathematics and WM, r…

Domain General Mediators of the Relation between Kindergarten Number Sense and First-Grade Mathematics Achievement

PubMed Central

Hassinger-Das, Brenna; Jordan, Nancy C.; Glutting, Joseph; Irwin, Casey; Dyson, Nancy

2013-01-01

Domain general skills that mediate the relation between kindergarten number sense and first-grade mathematics skills were investigated. Participants were 107 children who displayed low number sense in the fall of kindergarten. Controlling for background variables, multiple regression analyses showed that attention problems and executive functioning both were unique predictors of mathematics outcomes. Attention problems were more important for predicting first-grade calculation performance while executive functioning was more important for predicting first-grade performance on applied problems. Moreover, both executive functioning and attention problems were unique partial mediators of the relationship between kindergarten and first-grade mathematics skills. The results provide empirical support for developing interventions that target executive functioning and attention problems in addition to instruction in number skills for kindergartners with initial low number sense. PMID:24237789

Domain-general mediators of the relation between kindergarten number sense and first-grade mathematics achievement.

PubMed

Hassinger-Das, Brenna; Jordan, Nancy C; Glutting, Joseph; Irwin, Casey; Dyson, Nancy

2014-02-01

Domain-general skills that mediate the relation between kindergarten number sense and first-grade mathematics skills were investigated. Participants were 107 children who displayed low number sense in the fall of kindergarten. Controlling for background variables, multiple regression analyses showed that both attention problems and executive functioning were unique predictors of mathematics outcomes. Attention problems were more important for predicting first-grade calculation performance, whereas executive functioning was more important for predicting first-grade performance on applied problems. Moreover, both executive functioning and attention problems were unique partial mediators of the relationship between kindergarten and first-grade mathematics skills. The results provide empirical support for developing interventions that target executive functioning and attention problems in addition to instruction in number skills for kindergartners with initial low number sense. Copyright © 2013 Elsevier Inc. All rights reserved.

Mathematical Creativity and Mathematical Aptitude: A Cross-Lagged Panel Analysis

ERIC Educational Resources Information Center

Tyagi, Tarun Kumar

2016-01-01

Cross-lagged panel correlation (CLPC) analysis has been used to identify causal relationships between mathematical creativity and mathematical aptitude. For this study, 480 8th standard students were selected through a random cluster technique from 9 intermediate and high schools of Varanasi, India. Mathematical creativity and mathematical…

[Optimization of ultrasonic-assisted extraction of total flavonoids from leaves of the Artocarpus heterophyllus by response surface methodology].

PubMed

Wang, Hong-wu; Liu, Yan-qing; Wang, Yuan-hong

2011-07-01

To investigate the ultrasonic-assisted extract on of total flavonoids from leaves of the Artocarpus heterophyllus. Investigated the effects of ethanol concentration, extraction time, and liquid-solid ratio on flavonoids yield. A 17-run response surface design involving three factors at three levels was generated by the Design-Expert software and experimental data obtained were subjected to quadratic regression analysis to create a mathematical model describing flavonoids extraction. The optimum ultrasonic assisted extraction conditions were: ethanol volume fraction 69.4% and liquid-solid ratio of 22.6:1 for 32 min. Under these optimized conditions, the yield of flavonoids was 7.55 mg/g. The Box-Behnken design and response surface analysis can well optimize the ultrasonic-assisted extraction of total flavonoids from Artocarpus heterophyllus.

Multivariate linear regression analysis to identify general factors for quantitative predictions of implant stability quotient values

PubMed Central

Huang, Hairong; Xu, Zanzan; Shao, Xianhong; Wismeijer, Daniel; Sun, Ping; Wang, Jingxiao

2017-01-01

Objectives This study identified potential general influencing factors for a mathematical prediction of implant stability quotient (ISQ) values in clinical practice. Methods We collected the ISQ values of 557 implants from 2 different brands (SICace and Osstem) placed by 2 surgeons in 336 patients. Surgeon 1 placed 329 SICace implants, and surgeon 2 placed 113 SICace implants and 115 Osstem implants. ISQ measurements were taken at T1 (immediately after implant placement) and T2 (before dental restoration). A multivariate linear regression model was used to analyze the influence of the following 11 candidate factors for stability prediction: sex, age, maxillary/mandibular location, bone type, immediate/delayed implantation, bone grafting, insertion torque, I-stage or II-stage healing pattern, implant diameter, implant length and T1-T2 time interval. Results The need for bone grafting as a predictor significantly influenced ISQ values in all three groups at T1 (weight coefficients ranging from -4 to -5). In contrast, implant diameter consistently influenced the ISQ values in all three groups at T2 (weight coefficients ranging from 3.4 to 4.2). Other factors, such as sex, age, I/II-stage implantation and bone type, did not significantly influence ISQ values at T2, and implant length did not significantly influence ISQ values at T1 or T2. Conclusions These findings provide a rational basis for mathematical models to quantitatively predict the ISQ values of implants in clinical practice. PMID:29084260

Mathematical Modelling of Optimization of Structures of Monolithic Coverings Based on Liquid Rubbers

NASA Astrophysics Data System (ADS)

Turgumbayeva, R. Kh; Abdikarimov, M. N.; Mussabekov, R.; Sartayev, D. T.

2018-05-01

The paper considers optimization of monolithic coatings compositions using a computer and MPE methods. The goal of the paper was to construct a mathematical model of the complete factorial experiment taking into account its plan and conditions. Several regression equations were received. Dependence between content components and parameters of rubber, as well as the quantity of a rubber crumb, was considered. An optimal composition for manufacturing the material of monolithic coatings compositions was recommended based on experimental data.

Low back pain at school: unique risk deriving from unsatisfactory grade in maths and school-type recommendation.

PubMed

Erne, Cordula; Elfering, Achim

2011-12-01

Psychosocial stress and pain may relate to educational selection. At the end of primary school (International Standard Classification of Education: ISCED level 1) children are recommended for one of three performance-based lower secondary level types of school (ISCED level 2). The study examines the association of educational selection and other risk factors with pain in the upper back (UBP), lower back pain (LBP), peripheral (limb) pain (PP), and abdominal pain (AP). Teacher reports of unsatisfactory grades in mathematics, and official school-type recommendation are included as objective psychosocial risk factors. One hundred and ninety-two schoolchildren, aged between 10 and 13 from 11 classes of 7 schools in Switzerland participated in the cross-sectional study. In logistic regression analysis, predictor variables included age, sex, BMI, participation in sport, physical mobility, weight of satchel, hours of daily TV, video, and computer use, pupils' back pain reported by the mother and father, psychosocial strain, unsatisfactory grade in mathematics, and school-type recommendation. Analysis of pain drawings was highly reliable and revealed high prevalence rates of musculoskeletal pain in the last 4 weeks (UBP 15.3%, LBP 13:8%, PP 33.9%, AP 20.1%). Psychosocial risk factors were uniquely significant predictors of UBP (psychosocial strain), LBP (psychosocial strain, unsatisfactory grade in mathematics, school-type recommendation), and AP (school-type recommendation). In conclusion, selection in terms of educational school system was uniquely associated with LBP in schoolchildren. Stress caused by educational selection should be addressed in primary prevention of musculoskeletal pain in schoolchildren.

Stretch-dependent changes in surface profiles of the human crystalline lens during accommodation: A finite element study

PubMed Central

Pour, Hooman Mohammad; Kanapathipillai, Sangarapillai; Zarrabi, Khosrow; Manns, Fabrice; Ho, Arthur

2015-01-01

Background A nonlinear isotropic finite element (FE) model of a 29 year old human crystalline lens was constructed to study the effects of various geometrical parameters on lens accommodation. Methods The model simulates dis-accommodation by stretching of the lens and predicts the change in the lens capsule, cortex and nucleus surface profiles at select states of stretching/accommodation. Multiple regression analysis (MRA) is used to develop a stretch-dependent mathematical model relating the lens sagittal height to the radial position of the lens surface as a function of dis-accommodative stretch. A load analysis is performed to compare the FE results to empirical results from lens stretcher studies. Using the predicted geometrical changes, the optical response of the whole eye during accommodation was analysed by ray-tracing. Results Aspects of lens shape change relative to stretch were evaluated including change in diameter (d), central thickness (T) and accommodation (A). Maximum accommodation achieved was 10.29 D. From the MRA, the stretch-dependent mathematical model of the lens shape related lens curvatures as a function of lens ciliary stretch well (maximum mean-square residual error 2.5×10−3 µm, p<0.001). The results are compared with those from in vitro studies. Conclusions The FE and ray-tracing predictions are consistent with EVAS studies in terms of load and power change versus change in thickness. The mathematical stretch-dependent model of accommodation presented may have utility in investigating lens behaviour at states other than the relaxed or fully-accommodated states. PMID:25727940

Objective estimation of tropical cyclone innercore surface wind structure using infrared satellite images

NASA Astrophysics Data System (ADS)

Zhang, Changjiang; Dai, Lijie; Ma, Leiming; Qian, Jinfang; Yang, Bo

2017-10-01

An objective technique is presented for estimating tropical cyclone (TC) innercore two-dimensional (2-D) surface wind field structure using infrared satellite imagery and machine learning. For a TC with eye, the eye contour is first segmented by a geodesic active contour model, based on which the eye circumference is obtained as the TC eye size. A mathematical model is then established between the eye size and the radius of maximum wind obtained from the past official TC report to derive the 2-D surface wind field within the TC eye. Meanwhile, the composite information about the latitude of TC center, surface maximum wind speed, TC age, and critical wind radii of 34- and 50-kt winds can be combined to build another mathematical model for deriving the innercore wind structure. After that, least squares support vector machine (LSSVM), radial basis function neural network (RBFNN), and linear regression are introduced, respectively, in the two mathematical models, which are then tested with sensitivity experiments on real TC cases. Verification shows that the innercore 2-D surface wind field structure estimated by LSSVM is better than that of RBFNN and linear regression.

The relationships among high school STEM learning experiences, expectations, and mathematics and science efficacy and the likelihood of majoring in STEM in college

NASA Astrophysics Data System (ADS)

Sahin, Alpaslan; Ekmekci, Adem; Waxman, Hersh C.

2017-07-01

This study examines college students' science, technology, engineering, and mathematics (STEM) choices as they relate to high school experiences, parent, teacher, and self-expectations, and mathematics and science efficacy. Participants were 2246 graduates of a STEM-focused public Harmony Public Schools in Texas, Harmony Public Schools (HPS). Descriptive analyses indicated that the overall percentage of HPS graduates who chose a STEM major in college was greater than Texas state and national averages. Logistic regression analyses revealed that males and Asian students are more likely to choose a STEM major in college than females and non-Asian students, respectively. Moreover, students whose parents had a college degree in the U.S. are more likely to major in STEM fields than those who did not. Furthermore, males with higher mathematics efficacy and females with higher science efficacy are more likely to choose a STEM major than their counterparts with lower mathematics and science efficacy.

Investigating the incremental validity of cognitive variables in early mathematics screening.

PubMed

Clarke, Ben; Shanley, Lina; Kosty, Derek; Baker, Scott K; Cary, Mari Strand; Fien, Hank; Smolkowski, Keith

2018-03-26

The purpose of this study was to investigate the incremental validity of a set of domain general cognitive measures added to a traditional screening battery of early numeracy measures. The sample consisted of 458 kindergarten students of whom 285 were designated as severely at-risk for mathematics difficulty. Hierarchical multiple regression results indicated that Wechsler Abbreviated Scales of Intelligence (WASI) Matrix Reasoning and Vocabulary subtests, and Digit Span Forward and Backward measures explained a small, but unique portion of the variance in kindergarten students' mathematics performance on the Test of Early Mathematics Ability-Third Edition (TEMA-3) when controlling for Early Numeracy Curriculum Based Measurement (EN-CBM) screening measures (R² change = .01). Furthermore, the incremental validity of the domain general cognitive measures was relatively stronger for the severely at-risk sample. We discuss results from the study in light of instructional decision-making and note the findings do not justify adding domain general cognitive assessments to mathematics screening batteries. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Responsiveness to mathematical problem-solving instruction: comparing students at risk of mathematics disability with and without risk of reading disability.

PubMed

Fuchs, Lynn S; Fuchs, Douglas; Prentice, Karin

2004-01-01

This study assessed responsiveness to a 16-week mathematical problem-solving treatment as a function of students' risk for disability. Among 301 third graders, TerraNova scores were used to categorize students as at risk for both reading and mathematics disability (MDR/RDR; 20 control and 12 experimental), at risk for mathematics disability only (MDR-only; 5 and 8), at risk for reading disability only (RDR-only; 12 and 15), or not at risk (NDR; 60 and 69). Interactions among at-risk status, treatment, and time showed that as a function of treatment, MDR/RDR, MDR-only, and RDR-only students improved less than NDR students on computation and labeling, and MDR/RDR students improved less than all other groups on conceptual underpinnings. Exploratory regressions suggested that MDR/RDR students' math deficits or their underlying mechanisms explained a greater proportion of variance in responsiveness to problem-solving treatment than reading deficits or their underlying mechanisms.

Executive functioning as a predictor of children's mathematics ability: inhibition, switching, and working memory.

PubMed

Bull, R; Scerif, G

2001-01-01

Children's mathematical skills were considered in relation to executive functions. Using multiple measures--including the Wisconsin Card Sorting Task (WCST), dual-task performance, Stroop task, and counting span-it was found that mathematical ability was significantly correlated with all measures of executive functioning, with the exception of dual-task performance. Furthermore, regression analyses revealed that each executive function measure predicted unique variance in mathematics ability. These results are discussed in terms of a central executive with diverse functions (Shallice & Burgess, 1996) and with recent evidence from Miyake, et al. (2000) showing the unity and diversity among executive functions. It is proposed that the particular difficulties for children of lower mathematical ability are lack of inhibition and poor working memory, which result in problems with switching and evaluation of new strategies for dealing with a particular task. The practical and theoretical implications of these results are discussed, along with suggestions for task changes and longitudinal studies that would clarify theoretical and developmental issues related to executive functioning.

Exposure time independent summary statistics for assessment of drug dependent cell line growth inhibition.

PubMed

Falgreen, Steffen; Laursen, Maria Bach; Bødker, Julie Støve; Kjeldsen, Malene Krag; Schmitz, Alexander; Nyegaard, Mette; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

2014-06-05

In vitro generated dose-response curves of human cancer cell lines are widely used to develop new therapeutics. The curves are summarised by simplified statistics that ignore the conventionally used dose-response curves' dependency on drug exposure time and growth kinetics. This may lead to suboptimal exploitation of data and biased conclusions on the potential of the drug in question. Therefore we set out to improve the dose-response assessments by eliminating the impact of time dependency. First, a mathematical model for drug induced cell growth inhibition was formulated and used to derive novel dose-response curves and improved summary statistics that are independent of time under the proposed model. Next, a statistical analysis workflow for estimating the improved statistics was suggested consisting of 1) nonlinear regression models for estimation of cell counts and doubling times, 2) isotonic regression for modelling the suggested dose-response curves, and 3) resampling based method for assessing variation of the novel summary statistics. We document that conventionally used summary statistics for dose-response experiments depend on time so that fast growing cell lines compared to slowly growing ones are considered overly sensitive. The adequacy of the mathematical model is tested for doxorubicin and found to fit real data to an acceptable degree. Dose-response data from the NCI60 drug screen were used to illustrate the time dependency and demonstrate an adjustment correcting for it. The applicability of the workflow was illustrated by simulation and application on a doxorubicin growth inhibition screen. The simulations show that under the proposed mathematical model the suggested statistical workflow results in unbiased estimates of the time independent summary statistics. Variance estimates of the novel summary statistics are used to conclude that the doxorubicin screen covers a significant diverse range of responses ensuring it is useful for biological interpretations. Time independent summary statistics may aid the understanding of drugs' action mechanism on tumour cells and potentially renew previous drug sensitivity evaluation studies.

Exposure time independent summary statistics for assessment of drug dependent cell line growth inhibition

PubMed Central

2014-01-01

Background In vitro generated dose-response curves of human cancer cell lines are widely used to develop new therapeutics. The curves are summarised by simplified statistics that ignore the conventionally used dose-response curves’ dependency on drug exposure time and growth kinetics. This may lead to suboptimal exploitation of data and biased conclusions on the potential of the drug in question. Therefore we set out to improve the dose-response assessments by eliminating the impact of time dependency. Results First, a mathematical model for drug induced cell growth inhibition was formulated and used to derive novel dose-response curves and improved summary statistics that are independent of time under the proposed model. Next, a statistical analysis workflow for estimating the improved statistics was suggested consisting of 1) nonlinear regression models for estimation of cell counts and doubling times, 2) isotonic regression for modelling the suggested dose-response curves, and 3) resampling based method for assessing variation of the novel summary statistics. We document that conventionally used summary statistics for dose-response experiments depend on time so that fast growing cell lines compared to slowly growing ones are considered overly sensitive. The adequacy of the mathematical model is tested for doxorubicin and found to fit real data to an acceptable degree. Dose-response data from the NCI60 drug screen were used to illustrate the time dependency and demonstrate an adjustment correcting for it. The applicability of the workflow was illustrated by simulation and application on a doxorubicin growth inhibition screen. The simulations show that under the proposed mathematical model the suggested statistical workflow results in unbiased estimates of the time independent summary statistics. Variance estimates of the novel summary statistics are used to conclude that the doxorubicin screen covers a significant diverse range of responses ensuring it is useful for biological interpretations. Conclusion Time independent summary statistics may aid the understanding of drugs’ action mechanism on tumour cells and potentially renew previous drug sensitivity evaluation studies. PMID:24902483

Influence of beta-cyclodextrin complexation on glipizide release from hydroxypropyl methylcellulose matrix tablets.

PubMed

Shivakumar, H N; Desai, B G; Pandya, Saumyak; Karki, S S

2007-01-01

Glipizide was complexed with beta-cyclodextrin in an attempt to enhance the drug solubility. The phase solubility diagram was classified as A(L) type, which was characterized by an apparent 1:1 stability constant that had a value of 413.82 M(-1). Fourier transform infrared spectrophotometry, differential scanning calorimetry, powder x-ray diffractometry and proton nuclear magnetic resonance spectral analysis indicated considerable interaction between the drug and beta-cyclodextrin. A 2(3) factorial design was employed to prepare hydroxypropyl methylcellulose (HPMC) matrix tablets containing the drug or its complex. The effect of the total polymer loads (X1), levels of HPMC K100LV (X9), and complexation (X3) on release at first hour (Y1), 24 h (Y2), time taken for 50% release (Y3), and diffusion exponent (Y4) was systematically analyzed using the F test. Mathematical models containing only the significant terms (P < 0.05) were generated for each parameter by multiple linear regression analysis and analysis of variance. Complexation was found to exert a significant effect on Y1, Y2, and Y3, whereas total polymer loads significantly influenced all the responses. The models generated were validated by developing two new formulations with a combination of factors within the experimental domain. The experimental values of the response parameters were in close agreement with the predicted values, thereby proving-the validity of the generated mathematical models.

Lateral-Directional Parameter Estimation on the X-48B Aircraft Using an Abstracted, Multi-Objective Effector Model

NASA Technical Reports Server (NTRS)

Ratnayake, Nalin A.; Waggoner, Erin R.; Taylor, Brian R.

2011-01-01

The problem of parameter estimation on hybrid-wing-body aircraft is complicated by the fact that many design candidates for such aircraft involve a large number of aerodynamic control effectors that act in coplanar motion. This adds to the complexity already present in the parameter estimation problem for any aircraft with a closed-loop control system. Decorrelation of flight and simulation data must be performed in order to ascertain individual surface derivatives with any sort of mathematical confidence. Non-standard control surface configurations, such as clamshell surfaces and drag-rudder modes, further complicate the modeling task. In this paper, time-decorrelation techniques are applied to a model structure selected through stepwise regression for simulated and flight-generated lateral-directional parameter estimation data. A virtual effector model that uses mathematical abstractions to describe the multi-axis effects of clamshell surfaces is developed and applied. Comparisons are made between time history reconstructions and observed data in order to assess the accuracy of the regression model. The Cram r-Rao lower bounds of the estimated parameters are used to assess the uncertainty of the regression model relative to alternative models. Stepwise regression was found to be a useful technique for lateral-directional model design for hybrid-wing-body aircraft, as suggested by available flight data. Based on the results of this study, linear regression parameter estimation methods using abstracted effectors are expected to perform well for hybrid-wing-body aircraft properly equipped for the task.

The Development of Mathematical Knowledge for Teaching of Mathematics Teachers in Lesson Analysis Process

ERIC Educational Resources Information Center

Baki, Mujgan

2015-01-01

This study aims to explore the role of lesson analysis in the development of mathematical knowledge for teaching. For this purpose, a graduate course based on lesson analysis was designed for novice mathematics teachers. Throughout the course the teachers watched videos of group-mates and discussed the issues they identified in terms of…

The relationship between constructivist supervisory practices, school climate, and student proficiency in reading, mathematics, and science: Evidence from NELS:88

NASA Astrophysics Data System (ADS)

Molnar, John Alexander

In an effort to improve instruction and student learning, school reform efforts have become prevalent. School reformers have examined many aspects of the school experience, including learning theories such as behaviorism and constructivism, the changing roles of teachers and supervisors, and even the concept of the school itself. The theoretical framework for this study centered around constructivist learning theory. The study itself focused on the application of constructivist learning theory to the supervisory process. The study examined five areas of interest: (a) teachers' perceptions of constructivist supervisory behavior; (b) teachers' perceptions of efficacy and control in the classroom; (c) teachers' perceptions of school climate; (d) teachers' perceptions of job satisfaction, and (e) the influences of each of the aforementioned on student proficiency in mathematics, reading, and science. Data for the study was drawn from the first follow-up survey of the National Educational Longitudinal Study of 1988 (NELS: 88). NELS: 88 investigated a wide variety of factors that influence the educational process. The first follow-up focuses on environmental factors that affect teachers and students. Variables were selected from the NELS:88 data set that represented the areas to be examined. Factor analysis and correlational analysis were applied to ensure that the variables were measuring distinct constructs and to determine ways they could be grouped for analysis. Multiple linear regression analysis was applied to determine relationships among the individual and composite variables, controlling for student and teacher demographic factors. The results of the study suggest that varying relationships do exist between constructivist supervisory practices and the constructs measuring school climate and job satisfaction. The results also suggest that varying relationships exist between each of these factors and student proficiency in mathematics, reading, and science. Specifically, school climate, job satisfaction, and student proficiency were influenced by constructivist supervisory practices that included teachers' freedom to experiment with teaching and teachers' control over texts and materials.

Assessing Principal Component Regression Prediction of Neurochemicals Detected with Fast-Scan Cyclic Voltammetry

PubMed Central

2011-01-01

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook’s distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards. PMID:21966586

Assessing principal component regression prediction of neurochemicals detected with fast-scan cyclic voltammetry.

PubMed

Keithley, Richard B; Wightman, R Mark

2011-06-07

Principal component regression is a multivariate data analysis approach routinely used to predict neurochemical concentrations from in vivo fast-scan cyclic voltammetry measurements. This mathematical procedure can rapidly be employed with present day computer programming languages. Here, we evaluate several methods that can be used to evaluate and improve multivariate concentration determination. The cyclic voltammetric representation of the calculated regression vector is shown to be a valuable tool in determining whether the calculated multivariate model is chemically appropriate. The use of Cook's distance successfully identified outliers contained within in vivo fast-scan cyclic voltammetry training sets. This work also presents the first direct interpretation of a residual color plot and demonstrated the effect of peak shifts on predicted dopamine concentrations. Finally, separate analyses of smaller increments of a single continuous measurement could not be concatenated without substantial error in the predicted neurochemical concentrations due to electrode drift. Taken together, these tools allow for the construction of more robust multivariate calibration models and provide the first approach to assess the predictive ability of a procedure that is inherently impossible to validate because of the lack of in vivo standards.

Contributions of executive function and spatial skills to preschool mathematics achievement.

PubMed

Verdine, Brian N; Irwin, Casey M; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

2014-10-01

Early mathematics achievement is highly predictive of later mathematics performance. Here we investigated the influence of executive function (EF) and spatial skills, two generalizable skills often overlooked in mathematics curricula, on mathematics performance in preschoolers. Children (N=44) of varying socioeconomic status (SES) levels were assessed at 3 years of age on a new assessment of spatial skill (Test of Spatial Assembly, TOSA) and a vocabulary measure (Peabody Picture Vocabulary Test, PPVT). The same children were tested at 4 years of age on the Beery Test of Visual-Motor Integration (VMI) as well as on measures of EF and mathematics. The TOSA was created specifically as an assessment for 3-year-olds, allowing the investigation of links among spatial, EF, and mathematical skills earlier than previously possible. Results of a hierarchical regression indicate that EF and spatial skills predict 70% of the variance in mathematics performance without an explicit math test, EF is an important predictor of math performance as prior research suggested, and spatial skills uniquely predict 27% of the variance in mathematics skills. Additional research is needed to understand whether EF is truly malleable and whether EF and spatial skills may be leveraged to support early mathematics skills, especially for lower SES children who are already falling behind in these skill areas by 3 and 4 years of age. These findings indicate that both skills are part of an important foundation for mathematics performance and may represent pathways for improving school readiness for mathematics. Copyright © 2014 Elsevier Inc. All rights reserved.

Mathematical Idea Analysis: What Embodied Cognitive Science Can Say about the Human Nature of Mathematics.

ERIC Educational Resources Information Center

Nunez, Rafael E.

This paper gives a brief introduction to a discipline called the cognitive science of mathematics. The theoretical background of the arguments is based on embodied cognition and findings in cognitive linguistics. It discusses Mathematical Idea Analysis, a set of techniques for studying implicit structures in mathematics. Particular attention is…

Mathematical model of optical signals emitted by electrical discharges occuring in electroinsulating oil

NASA Astrophysics Data System (ADS)

Kozioł, Michał

2017-10-01

The article presents a parametric model describing the registered distributions spectrum of optical radiation emitted by electrical discharges generated in the systems: the needle- needle, the needleplate and in the system for surface discharges. Generation of electrical discharges and registration of the emitted radiation was carried out in three different electrical insulating oils: fabric new, operated (used) and operated with air bubbles. For registration of optical spectra in the range of ultraviolet, visible and near infrared a high resolution spectrophotometer was. The proposed mathematical model was developed in a regression procedure using gauss-sigmoid type function. The dependent variable was the intensity of the recorded optical signals. In order to estimate the optimal parameters of the model an evolutionary algorithm was used. The optimization procedure was performed in Matlab environment. For determination of the matching quality of theoretical parameters of the regression function to the empirical data determination coefficient R2 was applied.

Mathematical modeling in realistic mathematics education

NASA Astrophysics Data System (ADS)

Riyanto, B.; Zulkardi; Putri, R. I. I.; Darmawijoyo

2017-12-01

The purpose of this paper is to produce Mathematical modelling in Realistics Mathematics Education of Junior High School. This study used development research consisting of 3 stages, namely analysis, design and evaluation. The success criteria of this study were obtained in the form of local instruction theory for school mathematical modelling learning which was valid and practical for students. The data were analyzed using descriptive analysis method as follows: (1) walk through, analysis based on the expert comments in the expert review to get Hypothetical Learning Trajectory for valid mathematical modelling learning; (2) analyzing the results of the review in one to one and small group to gain practicality. Based on the expert validation and students’ opinion and answers, the obtained mathematical modeling problem in Realistics Mathematics Education was valid and practical.

Time series regression model for infectious disease and weather.

PubMed

Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

2015-10-01

Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Mathematical Modeling of Rotary Blood Pumps in a Pulsatile In Vitro Flow Environment.

PubMed

Pirbodaghi, Tohid

2017-08-01

Nowadays, sacrificing animals to develop medical devices and receive regulatory approval has become more common, which increases ethical concerns. Although in vivo tests are necessary for development and evaluation of new devices, nonetheless, with appropriate in vitro setups and mathematical models, a part of the validation process can be performed using these models to reduce the number of sacrificed animals. The main aim of this study is to present a mathematical model simulating the hydrodynamic function of a rotary blood pump (RBP) in a pulsatile in vitro flow environment. This model relates the pressure head of the RBP to the flow rate, rotational speed, and time derivatives of flow rate and rotational speed. To identify the model parameters, an in vitro setup was constructed consisting of a piston pump, a compliance chamber, a throttle, a buffer reservoir, and the CentriMag RBP. A 40% glycerin-water mixture as a blood analog fluid and deionized water were used in the hydraulic circuit to investigate the effect of viscosity and density of the working fluid on the model parameters. First, model variables were physically measured and digitally acquired. Second, an identification algorithm based on regression analysis was used to derive the model parameters. Third, the completed model was validated with a totally different set of in vitro data. The model is usable for both mathematical simulations of the interaction between the pump and heart and indirect pressure measurement in a clinical context. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Technical note: A linear model for predicting δ13 Cprotein.

PubMed

Pestle, William J; Hubbe, Mark; Smith, Erin K; Stevenson, Joseph M

2015-08-01

Development of a model for the prediction of δ(13) Cprotein from δ(13) Ccollagen and Δ(13) Cap-co . Model-generated values could, in turn, serve as "consumer" inputs for multisource mixture modeling of paleodiet. Linear regression analysis of previously published controlled diet data facilitated the development of a mathematical model for predicting δ(13) Cprotein (and an experimentally generated error term) from isotopic data routinely generated during the analysis of osseous remains (δ(13) Cco and Δ(13) Cap-co ). Regression analysis resulted in a two-term linear model (δ(13) Cprotein (%) = (0.78 × δ(13) Cco ) - (0.58× Δ(13) Cap-co ) - 4.7), possessing a high R-value of 0.93 (r(2)  = 0.86, P < 0.01), and experimentally generated error terms of ±1.9% for any predicted individual value of δ(13) Cprotein . This model was tested using isotopic data from Formative Period individuals from northern Chile's Atacama Desert. The model presented here appears to hold significant potential for the prediction of the carbon isotope signature of dietary protein using only such data as is routinely generated in the course of stable isotope analysis of human osseous remains. These predicted values are ideal for use in multisource mixture modeling of dietary protein source contribution. © 2015 Wiley Periodicals, Inc.

Impact of Using History of Mathematics on Students' Mathematics Attitude: A Meta-Analysis Study

ERIC Educational Resources Information Center

Bütüner, Suphi Onder

2015-01-01

The main objective of hereby study is to unearth the big picture, reaching studies about influence of using history of mathematics on attitude of mathematics among students. 6 studies with a total effect size of 14 that comply with coding protocol and comprise statistical values necessary for meta-analysis are combined via meta-analysis method…

Effects of phonological awareness and naming speed on mathematics skills in children with mild intellectual disabilities.

PubMed

Foster, Matthew E; Sevcik, Rose A; Romski, Maryann; Morris, Robin D

2015-01-01

Both phonological awareness (PA) and naming speed have been identified as two skills related to the development of mathematics skills for children with and without learning disabilities. The purpose of the present study was to investigate the relationships between PA and colour naming speed for 265 elementary school students with mild intellectual disabilities (MID). Participants were assessed using the Comprehensive Test of Phonological Processes and the KeyMath Revised Diagnostic Inventory of Essential Mathematics. Hierarchical regression analyses accounting for the effects of age indicated that children with MID rely on both PA and naming speed when solving mathematics problems, although PA was the more robust indicator of the two. As a whole, these results suggest that children with intellectual disabilities evidence the same types of reading and math relationships as shown for other populations of children.

Effect of pulsed current GTA welding parameters on the fusion zone microstructure of AA 6061 aluminium alloy

NASA Astrophysics Data System (ADS)

Kumar, T. Senthil; Balasubramanian, V.; Babu, S.; Sanavullah, M. Y.

2007-08-01

AA6061 aluminium alloy (Al-Mg-Si alloy) has gathered wide acceptance in the fabrication of food processing equipment, chemical containers, passenger cars, road tankers, and railway transport systems. The preferred process for welding these aluminium alloys is frequently Gas Tungsten Arc (GTA) welding due to its comparatively easy applicability and lower cost. In the case of single pass GTA welding of thinner sections of this alloy, the pulsed current has been found beneficial due to its advantages over the conventional continuous current processes. The use of pulsed current parameters has been found to improve the mechanical properties of the welds compared to those of continuous current welds of this alloy due to grain refinement occurring in the fusion zone. In this investigation, an attempt has been made to develop a mathematical model to predict the fusion zone grain diameter incorporating pulsed current welding parameters. Statistical tools such as design of experiments, analysis of variance, and regression analysis are used to develop the mathematical model. The developed model can be effectively used to predict the fusion grain diameter at a 95% confidence level for the given pulsed current parameters. The effect of pulsed current GTA welding parameters on the fusion zone grain diameter of AA 6061 aluminium alloy welds is reported in this paper.

Improving students’ mathematical representational ability through RME-based progressive mathematization

NASA Astrophysics Data System (ADS)

Warsito; Darhim; Herman, T.

2018-01-01

This study aims to determine the differences in the improving of mathematical representation ability based on progressive mathematization with realistic mathematics education (PMR-MP) with conventional learning approach (PB). The method of research is quasi-experiments with non-equivalent control group designs. The study population is all students of class VIII SMPN 2 Tangerang consisting of 6 classes, while the sample was taken two classes with purposive sampling technique. The experimental class is treated with PMR-MP while the control class is treated with PB. The instruments used are test of mathematical representation ability. Data analysis was done by t-test, ANOVA test, post hoc test, and descriptive analysis. The result of analysis can be concluded that: 1) there are differences of mathematical representation ability improvement between students treated by PMR-MP and PB, 2) no interaction between learning approach (PMR-MP, PB) and prior mathematics knowledge (PAM) to improve students’ mathematical representation; 3) Students’ mathematical representation improvement in the level of higher PAM is better than medium, and low PAM students. Thus, based on the process of mathematization, it is very important when the learning direction of PMR-MP emphasizes on the process of building mathematics through a mathematical model.

A Multifaceted Mathematical Approach for Complex Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alexander, F.; Anitescu, M.; Bell, J.

2012-03-07

Applied mathematics has an important role to play in developing the tools needed for the analysis, simulation, and optimization of complex problems. These efforts require the development of the mathematical foundations for scientific discovery, engineering design, and risk analysis based on a sound integrated approach for the understanding of complex systems. However, maximizing the impact of applied mathematics on these challenges requires a novel perspective on approaching the mathematical enterprise. Previous reports that have surveyed the DOE's research needs in applied mathematics have played a key role in defining research directions with the community. Although these reports have had significantmore » impact, accurately assessing current research needs requires an evaluation of today's challenges against the backdrop of recent advances in applied mathematics and computing. To address these needs, the DOE Applied Mathematics Program sponsored a Workshop for Mathematics for the Analysis, Simulation and Optimization of Complex Systems on September 13-14, 2011. The workshop had approximately 50 participants from both the national labs and academia. The goal of the workshop was to identify new research areas in applied mathematics that will complement and enhance the existing DOE ASCR Applied Mathematics Program efforts that are needed to address problems associated with complex systems. This report describes recommendations from the workshop and subsequent analysis of the workshop findings by the organizing committee.« less

Drawing Nomograms with R: applications to categorical outcome and survival data.

PubMed

Zhang, Zhongheng; Kattan, Michael W

2017-05-01

Outcome prediction is a major task in clinical medicine. The standard approach to this work is to collect a variety of predictors and build a model of appropriate type. The model is a mathematical equation that connects the outcome of interest with the predictors. A new patient with given clinical characteristics can be predicted for outcome with this model. However, the equation describing the relationship between predictors and outcome is often complex and the computation requires software for practical use. There is another method called nomogram which is a graphical calculating device allowing an approximate graphical computation of a mathematical function. In this article, we describe how to draw nomograms for various outcomes with nomogram() function. Binary outcome is fit by logistic regression model and the outcome of interest is the probability of the event of interest. Ordinal outcome variable is also discussed. Survival analysis can be fit with parametric model to fully describe the distributions of survival time. Statistics such as the median survival time, survival probability up to a specific time point are taken as the outcome of interest.

Development of an empirical mathematical model for describing and optimizing the hygiene potential of a thermophilic anaerobic bioreactor treating faeces.

PubMed

Lübken, M; Wichern, M; Bischof, F; Prechtl, S; Horn, H

2007-01-01

Poor sanitation and insufficient disposal of sewage and faeces are primarily responsible for water associated health problems in developing countries. Domestic sewage and faeces are prevalently discharged into surface waters which are used by the inhabitants as a source for drinking water. This paper presents a decentralized anaerobic process technique for handling of such domestic organic waste. Such an efficient and compact system for treating faeces and food waste may be of great benefit for developing countries. Besides a stable biogas production for energy generation, the reduction of bacterial pathogens is of particular importance. In our research we investigated the removal capacity of the reactor concerning pathogens, which has been operated under thermophilic conditions. Faecal coliforms and intestinal enterococci have been detected as indicator organisms for bacterial pathogens. By the multiple regression analysis technique an empirical mathematical model has been developed. The model shows a high correlation between removal efficiency and both, hydraulic retention time (HRT) and temperature. By this model an optimized HRT for defined bacterial pathogens effluent standards can be easily calculated. Thus, hygiene potential can be evaluated along with economic aspects. In this paper not only results for describing the hygiene potential of a thermophilic anaerobic bioreactor are presented, but also an exemplary method to draw the right conclusions out of biological tests with the aid of mathematical tools.

A mathematical prediction model incorporating molecular subtype for risk of non-sentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients: a retrospective analysis and nomogram development.

PubMed

Wang, Na-Na; Yang, Zheng-Jun; Wang, Xue; Chen, Li-Xuan; Zhao, Hong-Meng; Cao, Wen-Feng; Zhang, Bin

2018-04-25

Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort. We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort. Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025-2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111-23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714-3.892; P < 0.001), and the number of negative sentinel lymph nodes (OR = 0.686, 95% CI 0.575-0.817; P < 0.001) were independent statistically significant predictors of non-sentinel lymph node metastasis. Furthermore, luminal B (OR = 3.311, 95% CI 1.593-6.884; P = 0.001) and HER2 overexpression (OR = 4.308, 95% CI 1.097-16.912; P = 0.036) were independent and statistically significant predictor of non-sentinel lymph node metastasis versus luminal A. A regression model based on the results of multivariate analysis was established to predict the risk of non-sentinel lymph node metastasis, which had an AUC of 0.8188. The model was validated in the validation cohort and showed excellent diagnostic performance. The mathematical prediction model that incorporates five variables including breast cancer molecular subtype demonstrates excellent diagnostic performance in assessing the risk of non-sentinel lymph node metastasis in sentinel lymph node-positive patients. The prediction model could be of help surgeons in evaluating the risk of non-sentinel lymph node involvement for breast cancer patients; however, the model requires further validation in prospective studies.

The analysis of mathematics literacy on PMRI learning with media schoology of junior high school students

NASA Astrophysics Data System (ADS)

Wardono; Mariani, S.

2018-03-01

Indonesia as a developing country in the future will have high competitiveness if its students have high mathematics literacy ability. The current reality from year to year rankings of PISA mathematics literacy Indonesian students are still not good. This research is motivated by the importance and low ability of the mathematics literacy. The purpose of this study is to: (1) analyze the effectiveness of PMRI learning with media Schoology, (2) describe the ability of students' mathematics literacy on PMRI learning with media Schoology which is reviewed based on seven components of mathematics literacy, namely communication, mathematizing, representation, reasoning, devising strategies, using symbols, and using mathematics tool. The method used in this research is the method of sequential design method mix. Techniques of data collection using observation, interviews, tests, and documentation. Data analysis techniques use proportion test, appellate test, and use descriptive analysis. Based on the data analysis, it can be concluded; (1) PMRI learning with media Schoology effectively improve the ability of mathematics literacy because of the achievement of classical completeness, students' mathematics literacy ability in PMRI learning with media Schoology is higher than expository learning, and there is increasing ability of mathematics literacy in PMRI learning with media Schoology of 30%. (2) Highly capable students attain excellent mathematics literacy skills, can work using broad thinking with appropriate resolution strategies. Students who are capable of achieving good mathematics literacy skills can summarize information, present problem-solving processes, and interpret solutions. low-ability students have reached the level of ability of mathematics literacy good enough that can solve the problem in a simple way.

Mapping Mathematics in Classroom Discourse

ERIC Educational Resources Information Center

Herbel-Eisenmann, Beth A.; Otten, Samuel

2011-01-01

This article offers a particular analytic method from systemic functional linguistics, "thematic analysis," which reveals the mathematical meaning potentials construed in discourse. Addressing concerns that discourse analysis is too often content-free, thematic analysis provides a way to represent semantic structures of mathematical content,…

New Trends in Mathematics Teaching, Volume III.

ERIC Educational Resources Information Center

United Nations Educational, Scientific, and Cultural Organization, Paris (France).

Each of the ten chapters in this volume is intended to present an objective analysis of the trends of some important subtopic in mathematics education and each includes a bibliography for fuller study. The chapters cover primary school mathematics, algebra, geometry, probability and statistics, analysis, logic, applications of mathematics, methods…

Financial Mathematical Tasks in a Middle School Mathematics Textbook Series: A Content Analysis

ERIC Educational Resources Information Center

Hamburg, Maryanna P.

2009-01-01

This content analysis examined the distribution of financial mathematical tasks (FMTs), mathematical tasks that contain financial terminology and require financially related solutions, across the National Standards in K-12 Personal Finance Education categories (JumpStart Coalition, 2007), the thinking skills as identified by "A Taxonomy for…

The Design of Lessons Using Mathematics Analysis Software to Support Multiple Representations in Secondary School Mathematics

ERIC Educational Resources Information Center

Pierce, Robyn; Stacey, Kaye; Wander, Roger; Ball, Lynda

2011-01-01

Current technologies incorporating sophisticated mathematical analysis software (calculation, graphing, dynamic geometry, tables, and more) provide easy access to multiple representations of mathematical problems. Realising the affordances of such technology for students' learning requires carefully designed lessons. This paper reports on design…

Trend Analysis on Mathematics Achievements: A Comparative Study Using TIMSS Data

ERIC Educational Resources Information Center

Ker, H. W.

2013-01-01

Research addressed the importance of mathematics education for the students' preparation to enter scientific and technological workforce. This paper utilized Trends in International Mathematics and Science Study (TIMSS) 2011 data to conduct a global comparative analysis on mathematics performance at varied International Benchmark levels. The…

Visual-spatial abilities relate to mathematics achievement in children with heavy prenatal alcohol exposure

PubMed Central

Crocker, N.; Riley, E.P.; Mattson, S.N.

2014-01-01

Objective The current study examined the relationship between mathematics and attention, working memory, and visual memory in children with heavy prenatal alcohol exposure and controls. Method Fifty-six children (29 AE, 27 CON) were administered measures of global mathematics achievement (WRAT-3 Arithmetic & WISC-III Written Arithmetic), attention, (WISC-III Digit Span forward and Spatial Span forward), working memory (WISC-III Digit Span backward and Spatial Span backward), and visual memory (CANTAB Spatial Recognition Memory and Pattern Recognition Memory). The contribution of cognitive domains to mathematics achievement was analyzed using linear regression techniques. Attention, working memory and visual memory data were entered together on step 1 followed by group on step 2, and the interaction terms on step 3. Results Model 1 accounted for a significant amount of variance in both mathematics achievement measures, however, model fit improved with the addition of group on step 2. Significant predictors of mathematics achievement were Spatial Span forward and backward and Spatial Recognition Memory. Conclusions These findings suggest that deficits in spatial processing may be related to math impairments seen in FASD. In addition, prenatal alcohol exposure was associated with deficits in mathematics achievement, above and beyond the contribution of general cognitive abilities. PMID:25000323

Visual-spatial abilities relate to mathematics achievement in children with heavy prenatal alcohol exposure.

PubMed

Crocker, Nicole; Riley, Edward P; Mattson, Sarah N

2015-01-01

The current study examined the relationship between mathematics and attention, working memory, and visual memory in children with heavy prenatal alcohol exposure and controls. Subjects were 56 children (29 AE, 27 CON) who were administered measures of global mathematics achievement (WRAT-3 Arithmetic & WISC-III Written Arithmetic), attention, (WISC-III Digit Span forward and Spatial Span forward), working memory (WISC-III Digit Span backward and Spatial Span backward), and visual memory (CANTAB Spatial Recognition Memory and Pattern Recognition Memory). The contribution of cognitive domains to mathematics achievement was analyzed using linear regression techniques. Attention, working memory, and visual memory data were entered together on Step 1 followed by group on Step 2, and the interaction terms on Step 3. Model 1 accounted for a significant amount of variance in both mathematics achievement measures; however, model fit improved with the addition of group on Step 2. Significant predictors of mathematics achievement were Spatial Span forward and backward and Spatial Recognition Memory. These findings suggest that deficits in spatial processing may be related to math impairments seen in FASD. In addition, prenatal alcohol exposure was associated with deficits in mathematics achievement, above and beyond the contribution of general cognitive abilities. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Age estimation based on pulp chamber volume of first molars from cone-beam computed tomography images.

PubMed

Ge, Zhi-pu; Ma, Ruo-han; Li, Gang; Zhang, Ji-zong; Ma, Xu-chen

2015-08-01

To establish a method that can be used for human age estimation on the basis of pulp chamber volume of first molars and to identify whether the method is good enough for age estimation in real human cases. CBCT images of 373 maxillary first molars and 372 mandibular first molars were collected to establish the mathematical model from 190 female and 213 male patients whose age between 12 and 69 years old. The inclusion criteria of the first molars were: no caries, no excessive tooth wear, no dental restorations, no artifacts due to metal restorative materials present in adjacent teeth, and no pulpal calcification. All the CBCT images were acquired with a CBCT unit NewTom VG (Quantitative Radiology, Verona, Italy) and reconstructed with a voxel-size of 0.15mm. The images were subsequently exported as DICOM data sets and imported into an open source 3D image semi-automatic segmenting and voxel-counting software ITK-SNAP 2.4 for the calculation of pulp chamber volumes. A logarithmic regression analysis was conducted with age as dependent variable and pulp chamber volume as independent variables to establish a mathematical model for the human age estimation. To identify the precision and accuracy of the model for human age estimation, another 104 maxillary first molars and 103 mandibular first molars from 55 female and 57 male patients whose age between 12 and 67 years old were collected, too. Mean absolute error and root mean square error between the actual age and estimated age were used to determine the precision and accuracy of the mathematical model. The study was approved by the Institutional Review Board of Peking University School and Hospital of Stomatology. A mathematical model was suggested for: AGE=117.691-26.442×ln (pulp chamber volume). The regression was statistically significant (p=0.000<0.01). The coefficient of determination (R(2)) was 0.564. There is a mean absolute error of 8.122 and root mean square error of 5.603 between the actual age and estimated age for all the tested teeth. The pulp chamber volume of first molar is a useful index for the estimation of human age with reasonable precision and accuracy. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A frequency domain global parameter estimation method for multiple reference frequency response measurements

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.

Models of subjective response to in-flight motion data

NASA Technical Reports Server (NTRS)

Rudrapatna, A. N.; Jacobson, I. D.

1973-01-01

Mathematical relationships between subjective comfort and environmental variables in an air transportation system are investigated. As a first step in model building, only the motion variables are incorporated and sensitivities are obtained using stepwise multiple regression analysis. The data for these models have been collected from commercial passenger flights. Two models are considered. In the first, subjective comfort is assumed to depend on rms values of the six-degrees-of-freedom accelerations. The second assumes a Rustenburg type human response function in obtaining frequency weighted rms accelerations, which are used in a linear model. The form of the human response function is examined and the results yield a human response weighting function for different degrees of freedom.

Numerical analysis and experimental studies on solenoid common rail diesel injector with worn control valve

NASA Astrophysics Data System (ADS)

Krivtsov, S. N.; Yakimov, I. V.; Ozornin, S. P.

2018-03-01

A mathematical model of a solenoid common rail fuel injector was developed. Its difference from existing models is control valve wear simulation. A common rail injector of 0445110376 Series (Cummins ISf 2.8 Diesel engine) produced by Bosch Company was used as a research object. Injector parameters (fuel delivery and back leakage) were determined by calculation and experimental methods. GT-Suite model average R2 is 0.93 which means that it predicts the injection rate shape very accurately (nominal and marginal technical conditions of an injector). Numerical analysis and experimental studies showed that control valve wear increases back leakage and fuel delivery (especially at 160 MPa). The regression models for determining fuel delivery and back leakage effects on fuel pressure and energizing time were developed (for nominal and marginal technical conditions).

Vulnerability survival analysis: a novel approach to vulnerability management

NASA Astrophysics Data System (ADS)

Farris, Katheryn A.; Sullivan, John; Cybenko, George

2017-05-01

Computer security vulnerabilities span across large, enterprise networks and have to be mitigated by security engineers on a routine basis. Presently, security engineers will assess their "risk posture" through quantifying the number of vulnerabilities with a high Common Vulnerability Severity Score (CVSS). Yet, little to no attention is given to the length of time by which vulnerabilities persist and survive on the network. In this paper, we review a novel approach to quantifying the length of time a vulnerability persists on the network, its time-to-death, and predictors of lower vulnerability survival rates. Our contribution is unique in that we apply the cox proportional hazards regression model to real data from an operational IT environment. This paper provides a mathematical overview of the theory behind survival analysis methods, a description of our vulnerability data, and an interpretation of the results.

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

DOE PAGES

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent; ...

2018-03-06

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

Design and analysis of forward and reverse models for predicting defect accumulation, defect energetics, and irradiation conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stewart, James A.; Kohnert, Aaron A.; Capolungo, Laurent

The complexity of radiation effects in a material’s microstructure makes developing predictive models a difficult task. In principle, a complete list of all possible reactions between defect species being considered can be used to elucidate damage evolution mechanisms and its associated impact on microstructure evolution. However, a central limitation is that many models use a limited and incomplete catalog of defect energetics and associated reactions. Even for a given model, estimating its input parameters remains a challenge, especially for complex material systems. Here, we present a computational analysis to identify the extent to which defect accumulation, energetics, and irradiation conditionsmore » can be determined via forward and reverse regression models constructed and trained from large data sets produced by cluster dynamics simulations. A global sensitivity analysis, via Sobol’ indices, concisely characterizes parameter sensitivity and demonstrates how this can be connected to variability in defect evolution. Based on this analysis and depending on the definition of what constitutes the input and output spaces, forward and reverse regression models are constructed and allow for the direct calculation of defect accumulation, defect energetics, and irradiation conditions. Here, this computational analysis, exercised on a simplified cluster dynamics model, demonstrates the ability to design predictive surrogate and reduced-order models, and provides guidelines for improving model predictions within the context of forward and reverse engineering of mathematical models for radiation effects in a materials’ microstructure.« less

A mathematical approach for the simultaneous in vitro spectrophotometric analysis of rifampicin and isoniazid from modified-release anti-TB drug delivery systems.

PubMed

du Toit, Lisa; Pillay, Viness; Choonara, Yahya

2010-01-01

Dissolution testing with subsequent analysis is considered as an imperative tool for quality evaluation of the combination rifampicin-isoniazid (RIF-INH) combination. Partial least squares (PLS) regression has been successfully undertaken to select suitable predictor variables and to identify outliers for the generation of equations for RIF and INH determination in fixed-dose combinations (FDCs). The aim of this investigation was to ascertain the applicability of the described technique in testing a novel oral FDC anti-TB drug delivery system and currently available two-drug FDCs, in comparison to the United States Pharmacopeial method for analysis of RIF and INH Capsules with chromatographic determination of INH and colorimetric RIF determination. Regression equations generated employing the statistical coefficients satisfactorily predicted RIF release at each sampling point (R(2)>or=0.9350). There was an acceptable degree of correlation between the drug release data, as predicted by regressional analysis of UV spectrophotometric data, and chromatographic and colorimetric determination of INH (R(2)=0.9793 and R(2)=0.9739) and RIF (R(2)= 0.9976 and R(2)=0.9996) for the two-drug FDC and the novel oral anti-TB drug delivery system, respectively. Regressional analysis of UV spectrophotometric data for simultaneous RIF and INH prediction thus provides a simplified methodology for use in diverse research settings for the assurance of RIF bioavailability from FDC formulations, specifically modified-release forms.

Ratio Analysis: Where Investments Meet Mathematics.

ERIC Educational Resources Information Center

Barton, Susan D.; Woodbury, Denise

2002-01-01

Discusses ratio analysis by which investments may be evaluated. Requires the use of fundamental mathematics, problem solving, and a comparison of the mathematical results within the framework of industry. (Author/NB)

The Mathematics of the Return from Home Ownership.

ERIC Educational Resources Information Center

Vest, Floyd; Griffith, Reynolds

1991-01-01

A mathematical model or project analysis that calculates the financial return from home ownership is described. This analysis illustrates topics such as compound interest, annuities, amortization schedules, internal rate of return, and other elements of school and college mathematics up through numerical analysis. (KR)

Does the Value of Dynamic Assessment in Predicting End-of-First-Grade Mathematics Performance Differ as a Function of English Language Proficiency?

PubMed Central

Seethaler, Pamela M.; Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.

2015-01-01

The purpose of this study was to assess the added value of dynamic assessment (DA) beyond more conventional static measures for predicting individual differences in year-end 1st-grade calculation (CA) and word-problem (WP) performance, as a function of limited English proficiency (LEP) status. At the start of 1st grade, students (129 LEP; 163 non-LEP) were assessed on a brief static mathematics test, an extended static mathematics test, static tests of domain-general abilities associated with CAs and WPs (vocabulary; reasoning), and DA. Near end of 1st grade, they were assessed on CA and WP. Regression analyses indicated that the value of the predictor depends on the predicted outcome and LEP status. In predicting CAs, the extended mathematics test and DA uniquely explained variance for LEP children, with stronger predictive value for the extended mathematics test; for non-LEP children, the extended mathematics test was the only significant predictor. However, in predicting WPs, only DA and vocabulary were uniquely predictive for LEP children, with stronger value for DA; for non-LEP children, the extended mathematics test and DA were comparably uniquely predictive. Neither the brief static mathematics test nor reasoning was significant in predicting either outcome. The potential value of a gated screening process, using an extended mathematics assessment to predict CAs and using DA to predict WPs, is discussed. PMID:26523068

A reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

USGS Publications Warehouse

Raines, G.L.; Mihalasky, M.J.

2002-01-01

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. ?? 2002 International Association for Mathematical Geology.

Differential response rates to irradiation among patients with human papillomavirus positive and negative oropharyngeal cancer.

PubMed

Chen, Allen M; Li, Judy; Beckett, Laurel A; Zhara, Talia; Farwell, Gregory; Lau, Derick H; Gandour-Edwards, Regina; Vaughan, Andrew T; Purdy, James A

2013-01-01

To evaluate the responsiveness of human papillomavirus (HPV) -positive and HPV-negative oropharyngeal cancer to intensity-modulated radiotherapy (IMRT), using axial imaging obtained daily during the course of image-guided radiotherapy (IGRT). Observational cohort study with matched-pair analysis of patients irradiated for HPV-positive and HPV-negative oropharygeal cancer. Ten patients treated by IMRT to 70 Gy for locally advanced, HPV-positive squamous cell carcinoma of the oropharynx were matched to one HPV-negative control subject by age, gender, performance status, T-category, tumor location, and the use of concurrent chemotherapy. The gross tumor volume (GTV) was delineated on daily IGRT scans obtained via kilovoltage cone-beam computed tomography (CBCT). Mathematical modeling using fitted mixed-effects repeated measure analysis was performed to quantitatively and descriptively assess the trajectory of tumor regression. Patients with HPV-positive tumors experienced a more rapid rate of tumor regression between day 1 of IMRT and the beginning of week 2 (-33% Δ GTV) compared to their counterparts with HPV-negative tumors (-10% Δ GTV), which was statistically significant (p<0.001). During this initial period, the average absolute change in GTV was -22.9 cc/week for HPV-positive tumors and -5.9 cc/week for HPV-negative tumors (p<0.001). After week 2 of IMRT, the rates of GTV regression were comparable between the two groups. HPV-positive oropharyngeal cancers exhibited an enhanced response to radiation, characterized by a dramatically more rapid initial regression than those with HPV-negative tumors. Implications for treatment de-intensification in the context of future clinical trials and the possible mechanisms underlying this increased radiosensitivity will be discussed. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

Quantitative Analysis of the Interdisciplinarity of Applied Mathematics.

PubMed

Xie, Zheng; Duan, Xiaojun; Ouyang, Zhenzheng; Zhang, Pengyuan

2015-01-01

The increasing use of mathematical techniques in scientific research leads to the interdisciplinarity of applied mathematics. This viewpoint is validated quantitatively here by statistical and network analysis on the corpus PNAS 1999-2013. A network describing the interdisciplinary relationships between disciplines in a panoramic view is built based on the corpus. Specific network indicators show the hub role of applied mathematics in interdisciplinary research. The statistical analysis on the corpus content finds that algorithms, a primary topic of applied mathematics, positively correlates, increasingly co-occurs, and has an equilibrium relationship in the long-run with certain typical research paradigms and methodologies. The finding can be understood as an intrinsic cause of the interdisciplinarity of applied mathematics.

Stability Analysis of Finite Difference Schemes for Hyperbolic Systems, and Problems in Applied and Computational Linear Algebra.

DTIC Science & Technology

FINITE DIFFERENCE THEORY, * LINEAR ALGEBRA , APPLIED MATHEMATICS, APPROXIMATION(MATHEMATICS), BOUNDARY VALUE PROBLEMS, COMPUTATIONS, HYPERBOLAS, MATHEMATICAL MODELS, NUMERICAL ANALYSIS, PARTIAL DIFFERENTIAL EQUATIONS, STABILITY.

Mathematical Interventions for Secondary Students with Learning Disabilities and Mathematics Difficulties: A Meta-Analysis

ERIC Educational Resources Information Center

Jitendra, Asha K.; Lein, Amy E.; Im, Soo-hyun; Alghamdi, Ahmed A.; Hefte, Scott B.; Mouanoutoua, John

2018-01-01

This meta-analysis is the first to provide a quantitative synthesis of empirical evaluations of mathematical intervention programs implemented in secondary schools for students with learning disabilities and mathematics difficulties. Included studies used a treatment-control group design. A total of 19 experimental and quasi-experimental studies…

An Analysis of Mathematics Course Sequences for Low Achieving Students at a Comprehensive Technical High School

ERIC Educational Resources Information Center

Edge, D. Michael

2011-01-01

This non-experimental study attempted to determine how the different prescribed mathematic tracks offered at a comprehensive technical high school influenced the mathematics performance of low-achieving students on standardized assessments of mathematics achievement. The goal was to provide an analysis of any statistically significant differences…

Investigating kindergarteners' number sense and self-regulation scores in relation to their mathematics and Turkish scores in middle school

NASA Astrophysics Data System (ADS)

İvrendi, Asiye

2016-09-01

Number sense and self-regulation are considered foundational skills for later school learning. This study aimed to investigate the predictive power of kindergarten children's number sense and self-regulation scores on their mathematics and Turkish language examination scores in the 5th and 6th grades. The participants in this study were 5th grade ( n = 46) and 6th grade ( n = 28) students, whose number sense and self-regulation skills were measured when they were in kindergarten in 2009 and 2010. Data were analyzed through multiple regression. The results showed positive and mid-level correlations. The children's kindergarten number sense and self-regulation scores significantly predicted their 5th and 6th grade mathematics and Turkish language examination scores. Self-regulation was the stronger predictor of mathematics scores, whereas number sense scores were the better predictor of Turkish language examination scores. The findings from this study provide further evidence as to the critical role of children's early skills in middle school mathematics and language achievement.

Modeling and optimization of dough recipe for breadsticks

NASA Astrophysics Data System (ADS)

Krivosheev, A. Yu; Ponomareva, E. I.; Zhuravlev, A. A.; Lukina, S. I.; Alekhina, N. N.

2018-05-01

During the work, the authors studied the combined effect of non-traditional raw materials on indicators of quality breadsticks, mathematical methods of experiment planning were applied. The main factors chosen were the dosages of flaxseed flour and grape seed oil. The output parameters were the swelling factor of the products and their strength. Optimization of the formulation composition of the dough for bread sticks was carried out by experimental- statistical methods. As a result of the experiment, mathematical models were constructed in the form of regression equations, adequately describing the process of studies. The statistical processing of the experimental data was carried out by the criteria of Student, Cochran and Fisher (with a confidence probability of 0.95). A mathematical interpretation of the regression equations was given. Optimization of the formulation of the dough for bread sticks was carried out by the method of uncertain Lagrange multipliers. The rational values of the factors were determined: the dosage of flaxseed flour - 14.22% and grape seed oil - 7.8%, ensuring the production of products with the best combination of swelling ratio and strength. On the basis of the data obtained, a recipe and a method for the production of breadsticks "Idea" were proposed (TU (Russian Technical Specifications) 9117-443-02068106-2017).

Mathematical model of zinc absorption: effects of dietary calcium, protein and iron on zinc absorption

PubMed Central

Miller, Leland V.; Krebs, Nancy F.; Hambidge, K. Michael

2013-01-01

A previously described mathematical model of Zn absorption as a function of total daily dietary Zn and phytate was fitted to data from studies in which dietary Ca, Fe and protein were also measured. An analysis of regression residuals indicated statistically significant positive relationships between the residuals and Ca, Fe and protein, suggesting that the presence of any of these dietary components enhances Zn absorption. Based on the hypotheses that (1) Ca and Fe both promote Zn absorption by binding with phytate and thereby making it unavailable for binding Zn and (2) protein enhances the availability of Zn for transporter binding, the model was modified to incorporate these effects. The new model of Zn absorption as a function of dietary Zn, phytate, Ca, Fe and protein was then fitted to the data. The proportion of variation in absorbed Zn explained by the new model was 0·88, an increase from 0·82 with the original model. A reduced version of the model without Fe produced an equally good fit to the data and an improved value for the model selection criterion, demonstrating that when dietary Ca and protein are controlled for, there is no evidence that dietary Fe influences Zn absorption. Regression residuals and testing with additional data supported the validity of the new model. It was concluded that dietary Ca and protein modestly enhanced Zn absorption and Fe had no statistically discernable effect. Furthermore, the model provides a meaningful foundation for efforts to model nutrient interactions in mineral absorption. PMID:22617116

Mathematical model of zinc absorption: effects of dietary calcium, protein and iron on zinc absorption.

PubMed

Miller, Leland V; Krebs, Nancy F; Hambidge, K Michael

2013-02-28

A previously described mathematical model of Zn absorption as a function of total daily dietary Zn and phytate was fitted to data from studies in which dietary Ca, Fe and protein were also measured. An analysis of regression residuals indicated statistically significant positive relationships between the residuals and Ca, Fe and protein, suggesting that the presence of any of these dietary components enhances Zn absorption. Based on the hypotheses that (1) Ca and Fe both promote Zn absorption by binding with phytate and thereby making it unavailable for binding Zn and (2) protein enhances the availability of Zn for transporter binding, the model was modified to incorporate these effects. The new model of Zn absorption as a function of dietary Zn, phytate, Ca, Fe and protein was then fitted to the data. The proportion of variation in absorbed Zn explained by the new model was 0·88, an increase from 0·82 with the original model. A reduced version of the model without Fe produced an equally good fit to the data and an improved value for the model selection criterion, demonstrating that when dietary Ca and protein are controlled for, there is no evidence that dietary Fe influences Zn absorption. Regression residuals and testing with additional data supported the validity of the new model. It was concluded that dietary Ca and protein modestly enhanced Zn absorption and Fe had no statistically discernable effect. Furthermore, the model provides a meaningful foundation for efforts to model nutrient interactions in mineral absorption.

An Ecological Analysis of Mathematics Teachers' Noticing

ERIC Educational Resources Information Center

Jazby, Dan

2016-01-01

Most studies which investigate mathematics teacher noticing cast perception into a passive role. This study develops an ecological analysis of mathematics teachers' noticing in order to investigate how teachers actively look for information in classroom environments. This method of analysis is applied to data collected as an experienced primary…

Computer Simulation of Human Service Program Evaluations.

ERIC Educational Resources Information Center

Trochim, William M. K.; Davis, James E.

1985-01-01

Describes uses of computer simulations for the context of human service program evaluation. Presents simple mathematical models for most commonly used human service outcome evaluation designs (pretest-posttest randomized experiment, pretest-posttest nonequivalent groups design, and regression-discontinuity design). Translates models into single…

Least Squares Procedures.

ERIC Educational Resources Information Center

Hester, Yvette

Least squares methods are sophisticated mathematical curve fitting procedures used in all classical parametric methods. The linear least squares approximation is most often associated with finding the "line of best fit" or the regression line. Since all statistical analyses are correlational and all classical parametric methods are least…

Protocol Analysis of Group Problem Solving in Mathematics: A Cognitive-Metacognitive Framework for Assessment.

ERIC Educational Resources Information Center

Artzt, Alice F.; Armour-Thomas, Eleanor

The roles of cognition and metacognition were examined in the mathematical problem-solving behaviors of students as they worked in small groups. As an outcome, a framework that links the literature of cognitive science and mathematical problem solving was developed for protocol analysis of mathematical problem solving. Within this framework, each…

Mathematics Teaching Anxiety and Self-Efficacy Beliefs toward Mathematics Teaching: A Path Analysis

ERIC Educational Resources Information Center

Peker, Murat

2016-01-01

The purpose of this study was to investigate the relationship between pre-service primary school teachers' mathematics teaching anxiety and their self-efficacy beliefs toward mathematics teaching through path analysis. There were a total of 250 pre-service primary school teachers involved in this study. Of the total, 202 were female and 48 were…

Multivariate research in areas of phosphorus cast-iron brake shoes manufacturing using the statistical analysis and the multiple regression equations

NASA Astrophysics Data System (ADS)

Kiss, I.; Cioată, V. G.; Alexa, V.; Raţiu, S. A.

2017-05-01

The braking system is one of the most important and complex subsystems of railway vehicles, especially when it comes for safety. Therefore, installing efficient safe brakes on the modern railway vehicles is essential. Nowadays is devoted attention to solving problems connected with using high performance brake materials and its impact on thermal and mechanical loading of railway wheels. The main factor that influences the selection of a friction material for railway applications is the performance criterion, due to the interaction between the brake block and the wheel produce complex thermos-mechanical phenomena. In this work, the investigated subjects are the cast-iron brake shoes, which are still widely used on freight wagons. Therefore, the cast-iron brake shoes - with lamellar graphite and with a high content of phosphorus (0.8-1.1%) - need a special investigation. In order to establish the optimal condition for the cast-iron brake shoes we proposed a mathematical modelling study by using the statistical analysis and multiple regression equations. Multivariate research is important in areas of cast-iron brake shoes manufacturing, because many variables interact with each other simultaneously. Multivariate visualization comes to the fore when researchers have difficulties in comprehending many dimensions at one time. Technological data (hardness and chemical composition) obtained from cast-iron brake shoes were used for this purpose. In order to settle the multiple correlation between the hardness of the cast-iron brake shoes, and the chemical compositions elements several model of regression equation types has been proposed. Because a three-dimensional surface with variables on three axes is a common way to illustrate multivariate data, in which the maximum and minimum values are easily highlighted, we plotted graphical representation of the regression equations in order to explain interaction of the variables and locate the optimal level of each variable for maximal response. For the calculation of the regression coefficients, dispersion and correlation coefficients, the software Matlab was used.

A study of mathematics and science achievement scores among African American students and the impact of teacher-oriented variables on them through the Educational Longitudinal Study, 2002 (ELS: 2002) data

NASA Astrophysics Data System (ADS)

Walker, Valentine

The purpose of this dissertation was to utilize the ELS: 2002 longitudinal data to highlight the achievement of African American students relative to other racial sub-groups in mathematics and science and to highlight teacher oriented variables that might influence their achievement. Various statistical tools, including descriptive statistics, ANOVA, Multiple Regression were used to analyze data that was derived from the students', teachers' and administrations' questionnaires compiled in the base year of the study (2002) as well as the first follow-up transcript study (2006). The major findings are as follows: African American students performed lower than all other major racial subgroups in mathematics and science; Parental variables including SES and parental education were strong correlates of achievement in mathematics and science: The amount and type of mathematics and science courses students took were strong predictors of achievement in mathematics and science; Teachers' race, experience, certification status, graduate courses completed and professional development influenced African American students' achievement in mathematics and science; Aspects of classroom climate including teacher-pupil relationship, classroom management, students' perception of quality instructions, praise and rewards system might influence African American students' achievement in mathematics and science; Teachers' beliefs pertaining to students' background and intellectual ability might influence their educational expectation of African American students and subsequently student achievement in mathematics and science; Teaching strategies such as reviewing, lecturing and using graphing calculators had a positive influence on mathematics achievement while using computers, discussion and using other books than mathematics textbooks had negative influences on mathematics achievement; Computer use in science had positive influence on science achievement while homework had a positive influence on mathematics and science achievement among African American students. The application of these findings in settings populated with African American students might be important in increasing mathematics and science achievement among them.

How to begin a new topic in mathematics: does it matter to students' performance in mathematics?

PubMed

Ma, Xin; Papanastasiou, Constantinos

2006-08-01

The authors use Canadian data from the Third International Mathematics and Science Study to examine six instructional methods that mathematics teachers use to introduce new topics in mathematics on performance of eighth-grade students in six mathematical areas (mathematics as a whole, algebra, data analysis, fraction, geometry, and measurement). Results of multilevel analysis with students nested within schools show that the instructional methods of having the teacher explain the rules and definitions and looking at the textbook while the teacher talks about it had little instructional effects on student performance in any mathematical area. In contrast, the instructional method in which teachers try to solve an example related to the new topic was effective in promoting student performance across all mathematical areas.

An equation to predict the maximal lactate steady state from ramp-incremental exercise test data in cycling.

PubMed

Iannetta, Danilo; Fontana, Federico Y; Maturana, Felipe Mattioni; Inglis, Erin Calaine; Pogliaghi, Silvia; Keir, Daniel A; Murias, Juan M

2018-05-23

The maximal lactate steady state (MLSS) represents the highest exercise intensity at which an elevated blood lactate concentration ([Lac] b ) is stabilized above resting values. MLSS quantifies the boundary between the heavy-to-very-heavy intensity domains but its determination is not widely performed due to the number of trials required. This study aimed to: (i) develop a mathematical equation capable of predicting MLSS using variables measured during a single ramp-incremental cycling test and (ii) test the accuracy of the optimized mathematical equation. The predictive MLSS equation was determined by stepwise backward regression analysis of twelve independent variables measured in sixty individuals who had previously performed ramp-incremental exercise and in whom MLSS was known (MLSS obs ). Next, twenty-nine different individuals were prospectively recruited to test the accuracy of the equation. These participants performed ramp-incremental exercise to exhaustion and two-to-three 30-min constant-power output cycling bouts with [Lac] b sampled at regular intervals for determination of MLSS obs . Predicted MLSS (MLSS pred ) and MLSS obs in both phases of the study were compared by paired t-test, major-axis regression and Bland-Altman analysis. The predictor variables of MLSS were: respiratory compensation point (Wkg -1 ), peak oxygen uptake (V˙O 2peak ) (mlkg -1 min -1 ) and body mass (kg). MLSS pred was highly correlated with MLSS obs (r=0.93; p<0.01). When this equation was tested on the independent group, MLSS pred was not different from MLSS obs (234±43 vs. 234±44W; SEE 4.8W; r=0.99; p<0.01). These data support the validity of the predictive MLSS equation. We advocate its use as a time-efficient alternative to traditional MLSS testing in cycling. Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Stories about Math: An Analysis of Students' Mathematical Autobiographies

ERIC Educational Resources Information Center

Latterell, Carmen M.; Wilson, Janelle L.

2016-01-01

This paper analyzes 16 preservice secondary mathematics education majors' mathematical autobiographies. Participants wrote about their previous experiences with mathematics. All participants discussed why they wanted to become mathematics teachers with the key factors being past experience with mathematics teachers, previous success in mathematics…

Male Saudi Arabian freshman science majors at Jazan University: Their perceptions of parental educational practices on their science achievements

NASA Astrophysics Data System (ADS)

Alrehaly, Essa D.

Examination of Saudi Arabian educational practices is scarce, but increasingly important, especially in light of the country's pace in worldwide mathematics and science rankings. The purpose of the study is to understand and evaluate parental influence on male children's science education achievements in Saudi Arabia. Parental level of education and participant's choice of science major were used to identify groups for the purpose of data analysis. Data were gathered using five independent variables concerning parental educational practices (attitude, involvement, autonomy support, structure and control) and the dependent variable of science scores in high school. The sample consisted of 338 participants and was arbitrarily drawn from the science-based colleges (medical, engineering, and natural science) at Jazan University in Saudi Arabia. The data were tested using Pearson's analysis, backward multiple regression, one way ANOVA and independent t-test. The findings of the study reveal significant correlations for all five of the variables. Multiple regressions revealed that all five of the parents' educational practices indicators combined together could explain 19% of the variance in science scores and parental attitude toward science and educational involvement combined accounted for more than 18% of the variance. Analysis indicates that no significant difference is attributable to parental involvement and educational level. This finding is important because it indicates that, in Saudi Arabia, results are not consistent with research in Western or other Asian contexts.

Multivariate Regression Analysis of Winter Ozone Events in the Uinta Basin of Eastern Utah, USA

NASA Astrophysics Data System (ADS)

Mansfield, M. L.

2012-12-01

I report on a regression analysis of a number of variables that are involved in the formation of winter ozone in the Uinta Basin of Eastern Utah. One goal of the analysis is to develop a mathematical model capable of predicting the daily maximum ozone concentration from values of a number of independent variables. The dependent variable is the daily maximum ozone concentration at a particular site in the basin. Independent variables are (1) daily lapse rate, (2) daily "basin temperature" (defined below), (3) snow cover, (4) midday solar zenith angle, (5) monthly oil production, (6) monthly gas production, and (7) the number of days since the beginning of a multi-day inversion event. Daily maximum temperature and daily snow cover data are available at ten or fifteen different sites throughout the basin. The daily lapse rate is defined operationally as the slope of the linear least-squares fit to the temperature-altitude plot, and the "basin temperature" is defined as the value assumed by the same least-squares line at an altitude of 1400 m. A multi-day inversion event is defined as a set of consecutive days for which the lapse rate remains positive. The standard deviation in the accuracy of the model is about 10 ppb. The model has been combined with historical climate and oil & gas production data to estimate historical ozone levels.

Modeling the North American vertical datum of 1988 errors in the conterminous United States

NASA Astrophysics Data System (ADS)

Li, X.

2018-02-01

A large systematic difference (ranging from -20 cm to +130 cm) was found between NAVD 88 (North AmericanVertical Datum of 1988) and the pure gravimetric geoid models. This difference not only makes it very difficult to augment the local geoid model by directly using the vast NAVD 88 network with state-of-the-art technologies recently developed in geodesy, but also limits the ability of researchers to effectively demonstrate the geoid model improvements on the NAVD 88 network. Here, both conventional regression analyses based on various predefined basis functions such as polynomials, B-splines, and Legendre functions and the Latent Variable Analysis (LVA) such as the Factor Analysis (FA) are used to analyze the systematic difference. Besides giving a mathematical model, the regression results do not reveal a great deal about the physical reasons that caused the large differences in NAVD 88, which may be of interest to various researchers. Furthermore, there is still a significant amount of no-Gaussian signals left in the residuals of the conventional regression models. On the other side, the FA method not only provides a better not of the data, but also offers possible explanations of the error sources. Without requiring extra hypothesis tests on the model coefficients, the results from FA are more efficient in terms of capturing the systematic difference. Furthermore, without using a covariance model, a novel interpolating method based on the relationship between the loading matrix and the factor scores is developed for predictive purposes. The prediction error analysis shows that about 3-7 cm precision is expected in NAVD 88 after removing the systematic difference.

Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

PubMed

Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

2017-10-01

Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P < .001). Means of software machine-derived values differed significantly from actual PLT yield, 4.72 × 10 11 vs.6.12 × 10 11 , respectively, (P < .001). The following equation was developed to adjust these values: actual PLT yield= 0.221 + (1.254 × theoretical platelet yield). ROC curve model showed an optimal apheresis device software prediction cut-off of 4.65 × 10 11 to obtain a DP, with a sensitivity of 82.2%, specificity of 93.3%, and an area under the curve (AUC) of 0.909. Trima Accel v6.0 software consistently underestimated PLT yields. Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

Meta-Analysis of Mathematic Basic-Fact Fluency Interventions: A Component Analysis

ERIC Educational Resources Information Center

Codding, Robin S.; Burns, Matthew K.; Lukito, Gracia

2011-01-01

Mathematics fluency is a critical component of mathematics learning yet few attempts have been made to synthesize this research base. Seventeen single-case design studies with 55 participants were reviewed using meta-analytic procedures. A component analysis of practice elements was conducted and treatment intensity and feasibility were examined.…

An Analysis of Problem-Posing Tasks in Chinese and US Elementary Mathematics Textbooks

ERIC Educational Resources Information Center

Cai, Jinfa; Jiang, Chunlian

2017-01-01

This paper reports on 2 studies that examine how mathematical problem posing is integrated in Chinese and US elementary mathematics textbooks. Study 1 involved a historical analysis of the problem-posing (PP) tasks in 3 editions of the most widely used elementary mathematics textbook series published by People's Education Press in China over 3…

Representational change and strategy use in children's number line estimation during the first years of primary school.

PubMed

White, Sonia L J; Szűcs, Dénes

2012-01-04

The objective of this study was to scrutinize number line estimation behaviors displayed by children in mathematics classrooms during the first three years of schooling. We extend existing research by not only mapping potential logarithmic-linear shifts but also provide a new perspective by studying in detail the estimation strategies of individual target digits within a number range familiar to children. Typically developing children (n = 67) from Years 1-3 completed a number-to-position numerical estimation task (0-20 number line). Estimation behaviors were first analyzed via logarithmic and linear regression modeling. Subsequently, using an analysis of variance we compared the estimation accuracy of each digit, thus identifying target digits that were estimated with the assistance of arithmetic strategy. Our results further confirm a developmental logarithmic-linear shift when utilizing regression modeling; however, uniquely we have identified that children employ variable strategies when completing numerical estimation, with levels of strategy advancing with development. In terms of the existing cognitive research, this strategy factor highlights the limitations of any regression modeling approach, or alternatively, it could underpin the developmental time course of the logarithmic-linear shift. Future studies need to systematically investigate this relationship and also consider the implications for educational practice.

Representational change and strategy use in children's number line estimation during the first years of primary school

PubMed Central

2012-01-01

Background The objective of this study was to scrutinize number line estimation behaviors displayed by children in mathematics classrooms during the first three years of schooling. We extend existing research by not only mapping potential logarithmic-linear shifts but also provide a new perspective by studying in detail the estimation strategies of individual target digits within a number range familiar to children. Methods Typically developing children (n = 67) from Years 1-3 completed a number-to-position numerical estimation task (0-20 number line). Estimation behaviors were first analyzed via logarithmic and linear regression modeling. Subsequently, using an analysis of variance we compared the estimation accuracy of each digit, thus identifying target digits that were estimated with the assistance of arithmetic strategy. Results Our results further confirm a developmental logarithmic-linear shift when utilizing regression modeling; however, uniquely we have identified that children employ variable strategies when completing numerical estimation, with levels of strategy advancing with development. Conclusion In terms of the existing cognitive research, this strategy factor highlights the limitations of any regression modeling approach, or alternatively, it could underpin the developmental time course of the logarithmic-linear shift. Future studies need to systematically investigate this relationship and also consider the implications for educational practice. PMID:22217191

[A novel approach to NIR spectral quantitative analysis: semi-supervised least-squares support vector regression machine].

PubMed

Li, Lin; Xu, Shuo; An, Xin; Zhang, Lu-Da

2011-10-01

In near infrared spectral quantitative analysis, the precision of measured samples' chemical values is the theoretical limit of those of quantitative analysis with mathematical models. However, the number of samples that can obtain accurately their chemical values is few. Many models exclude the amount of samples without chemical values, and consider only these samples with chemical values when modeling sample compositions' contents. To address this problem, a semi-supervised LS-SVR (S2 LS-SVR) model is proposed on the basis of LS-SVR, which can utilize samples without chemical values as well as those with chemical values. Similar to the LS-SVR, to train this model is equivalent to solving a linear system. Finally, the samples of flue-cured tobacco were taken as experimental material, and corresponding quantitative analysis models were constructed for four sample compositions' content(total sugar, reducing sugar, total nitrogen and nicotine) with PLS regression, LS-SVR and S2 LS-SVR. For the S2 LS-SVR model, the average relative errors between actual values and predicted ones for the four sample compositions' contents are 6.62%, 7.56%, 6.11% and 8.20%, respectively, and the correlation coefficients are 0.974 1, 0.973 3, 0.923 0 and 0.948 6, respectively. Experimental results show the S2 LS-SVR model outperforms the other two, which verifies the feasibility and efficiency of the S2 LS-SVR model.

Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

PubMed Central

Chung, Moo K.; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K.

2014-01-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface. PMID:25791435

An overview of the mathematical and statistical analysis component of RICIS

NASA Technical Reports Server (NTRS)

Hallum, Cecil R.

1987-01-01

Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.

Contribution of spoken language and socio-economic background to adolescents' educational achievement at age 16 years.

PubMed

Spencer, Sarah; Clegg, Judy; Stackhouse, Joy; Rush, Robert

2017-03-01

Well-documented associations exist between socio-economic background and language ability in early childhood, and between educational attainment and language ability in children with clinically referred language impairment. However, very little research has looked at the associations between language ability, educational attainment and socio-economic background during adolescence, particularly in populations without language impairment. To investigate: (1) whether adolescents with higher educational outcomes overall had higher language abilities; and (2) associations between adolescent language ability, socio-economic background and educational outcomes, specifically in relation to Mathematics, English Language and English Literature GCSE grade. A total of 151 participants completed five standardized language assessments measuring vocabulary, comprehension of sentences and spoken paragraphs, and narrative skills and one nonverbal assessment when between 13 and 14 years old. These data were compared with the participants' educational achievement obtained upon leaving secondary education (16 years old). Univariate logistic regressions were employed to identify those language assessments and demographic factors that were associated with achieving a targeted A * -C grade in English Language, English Literature and Mathematics General Certificate of Secondary Education (GCSE) at 16 years. Further logistic regressions were then conducted to examine further the contribution of socio-economic background and spoken language skills in the multivariate models. Vocabulary, comprehension of sentences and spoken paragraphs, and mean length utterance in a narrative task along with socio-economic background contributed to whether participants achieved an A * -C grade in GCSE Mathematics and English Language and English Literature. Nonverbal ability contributed to English Language and Mathematics. The results of multivariate logistic regressions then found that vocabulary skills were particularly relevant to all three GCSE outcomes. Socio-economic background only remained important for English Language, once language assessment scores and demographic information were considered. Language ability, and in particular vocabulary, plays an important role for educational achievement. Results confirm a need for ongoing support for spoken language ability throughout secondary education and a potential role for speech and language therapy provision in the continuing drive to reduce the gap in educational attainment between groups from differing socio-economic backgrounds. © 2016 Royal College of Speech and Language Therapists.

Gender differences associated with enrollment in the Texas Academy of Mathematics and Science

NASA Astrophysics Data System (ADS)

Burns, Robert Thomas

This study sought to determine if different factors had influenced females and males to select engineering/science-related studies at the Texas Academy of Mathematics and Science (TAMS). The data were collected in the fall semester in 1997 at TAMS located on the University of North Texas campus from a survey of factors reported in the literature that had influenced students to enroll in engineering/science-related curriculum. Of the 380 TAMS students enrolled fall semester, 303 or 85% participated in the study. Those who participated included 135 or 45% females and 168 or 55% males. A dichotomous discriminant function analysis to identify relationships between the criterion variable (gender) and the predictor variable (factors) was used. The analysis of variance (ANOVA) was used to identify any significant predictor (factor) when the criterion was gender. Analysis of the data indicated no difference between females and males concerning factors that influenced them to enroll in TAMS. Neither discriminant function analysis nor the regression analysis using weighted least squares could significantly establish any relationship that could predict a student to be female or male with respect to factors that influenced them to enroll in TAMS. The factors were ranked utilizing the Thurstone equal appearing intervals scale for both females and males. Both females and males in TAMS ranked extrinsic interest including job opportunity, salary, and promotion, as the most important factor. The least important factor for both females and males was family encouragement. The findings indicate that TAMS students based their enrollment decision on factors independent of those suggested in the literature as applying to males and females. This may have resulted from the fact that these students are a unique population biased toward valuing a math/science curriculum.

Middle school students' attitudes toward math and STEM career interests: A 4-year follow-up study

NASA Astrophysics Data System (ADS)

Schneider, Madalyn R.

The purpose of the current study is to examine middle school students' attitudes toward math, intent to pursue STEM-related education and occupations, and STEM interest from middle school to high school. The data used in this study are from a larger, on-going National Science Foundation (NSF) grant-funded study that is investigating middle school students' disengagement while using the Assistments system (Baker, Heffernan & San Pedro, 2012), a computer-based math tutoring system. The NSF grant study aims to explore how disengagement with STEM material can aid in the prediction of students' college enrollment as well as how it may interact with other factors affecting students' career choices (San Pedro, Baker, Bowers, Heffernan, 2013). Participants are students from urban and suburban schools in Massachusetts measured first in middle school and again four years later. Measures at Time 1 included: various items related to attitudes toward mathematics, occupations they could see themselves doing as adults, and the Brief Self-Control Scale (Tangney, Baumeister, & Luzio Boone, 2004). Measures at Time 2 included: items requesting the students' current mathematics and science courses and intended majors or occupations following high school graduation. Exploratory factor analysis, multiple regression and logistic regression analyses were used to test the following four hypotheses: I. There will be several distinct factors that emerge to provide information about middle school students' attitudes toward math; II. Students' attitudes toward math will correlate positively and significantly with students' intent to pursue STEM-related careers at Time 1 with a medium effect; III. Middle school attitudes toward mathematics will relate positively and significantly to level of high school mathematics and science courses with a medium effect; IV. Middle school intent to pursue STEM will correlate positively and significantly with high school intent to pursue STEM majors/careers with a medium effect. Results supported a 2-factor model of Attitudes toward Mathematics consisting of Math Self-Concept and Attitudes toward Assistments. Other significant findings include: a positive relationship between students' Attitudes toward Assistments and level of math class taken in high school; a positive relationship between students' Math Self-Concept and Self Control; a positive relationship between Self Control and students' endorsement of STEM careers while in middle school, and discrepancy between male and female students' endorsement of STEM careers as early as middle school. Although many of the study's primary hypotheses were not supported, the present study provides a framework and baseline for several important considerations. Limitations, including those related to the present study's small sample size, and future implications of the present study, which add to career development literature in STEM, are discussed in regard to both research and practice. Keywords: career development, middle school, attitudes, math, STEM, self-concept

Choice of mathematical models for technological process of glass rod drawing

NASA Astrophysics Data System (ADS)

Alekseeva, L. B.

2017-10-01

The technological process of drawing glass rods (light guides) is considered. Automated control of the drawing process is reduced to the process of making decisions to ensure a given quality. The drawing process is considered as a control object, including the drawing device (control device) and the optical fiber forming zone (control object). To study the processes occurring in the formation zone, mathematical models are proposed, based on the continuum mechanics basics. To assess the influence of disturbances, a transfer function is obtained from the basis of the wave equation. Obtaining the regression equation also adequately describes the drawing process.

ESTIMATING LOW-FLOW FREQUENCIES OF UNGAGED STREAMS IN NEW ENGLAND.

USGS Publications Warehouse

Wandle, S. William

1987-01-01

Equations to estimate low flows were developed using multiple-regression analysis with a sample of 48 river basins, which were selected from the U. S. Geological Survey's network of gaged river basins in Massachusetts, New Hampshire, Rhode Island, Vermont, and southwestern Maine. Low-flow characteristics are represented by the 7Q2 and 7Q10 (the annual minimum 7-day mean low flow at the 2- and 10-year recurrence intervals). These statistics for each of the 48 basins were determined from a low-flow frequency analysis of streamflow records for 1942-71, or from a graphical or mathematical relationship if the record did not cover this 30-year period. Estimators for the mean and variance of the 7-day low flows at the index and short-term sites were used for two stations where discharge measurements of base flow were available and for two sites where the graphical technique was unsatisfactory.

[Ontogeny-specific interaction of psychophysiological mechanisms of emotional perception and educational achievement in students].

PubMed

Dmitrieva, E S; Gel'man, V Ia; Zaĭtseva, K A; Orlov, A M

2003-01-01

In order to explore the process of adaptation of children to school environment psychophysiological characteristics of perception of emotional speech information and school progress were experimentally studied. Forty-six schoolchildren of three age groups (7-10, 11-13, and 14-17 years old) participated in the study. In experimental session, a test sentence was presented to a subject through headphones with two emotional intonations (joy and anger) and without emotional expression. A subject had to recognize the type of emotion. His/her answers were recorded. School progress was determined by year grades in Russian, foreign language, and mathematics. Analysis of variance and linear regression analysis showed that ontogenetic features of a correlation between psychophysiological mechanisms of emotion recognition and school progress were gender- and subject-dependent. This correlation was stronger in 7-13-year-old children than in senior children. This age boundary was passed by the girls earlier than by the boys.

Literature review of some selected types of results and statistical analyses of total-ozone data. [for the ozonosphere

NASA Technical Reports Server (NTRS)

Myers, R. H.

1976-01-01

The depletion of ozone in the stratosphere is examined, and causes for the depletion are cited. Ground station and satellite measurements of ozone, which are taken on a worldwide basis, are discussed. Instruments used in ozone measurement are discussed, such as the Dobson spectrophotometer, which is credited with providing the longest and most extensive series of observations for ground based observation of stratospheric ozone. Other ground based instruments used to measure ozone are also discussed. The statistical differences of ground based measurements of ozone from these different instruments are compared to each other, and to satellite measurements. Mathematical methods (i.e., trend analysis or linear regression analysis) of analyzing the variability of ozone concentration with respect to time and lattitude are described. Various time series models which can be employed in accounting for ozone concentration variability are examined.

Design and statistical optimization of glipizide loaded lipospheres using response surface methodology.

PubMed

Shivakumar, Hagalavadi Nanjappa; Patel, Pragnesh Bharat; Desai, Bapusaheb Gangadhar; Ashok, Purnima; Arulmozhi, Sinnathambi

2007-09-01

A 32 factorial design was employed to produce glipizide lipospheres by the emulsification phase separation technique using paraffin wax and stearic acid as retardants. The effect of critical formulation variables, namely levels of paraffin wax (X1) and proportion of stearic acid in the wax (X2) on geometric mean diameter (dg), percent encapsulation efficiency (% EE), release at the end of 12 h (rel12) and time taken for 50% of drug release (t50), were evaluated using the F-test. Mathematical models containing only the significant terms were generated for each response parameter using the multiple linear regression analysis (MLRA) and analysis of variance (ANOVA). Both formulation variables studied exerted a significant influence (p < 0.05) on the response parameters. Numerical optimization using the desirability approach was employed to develop an optimized formulation by setting constraints on the dependent and independent variables. The experimental values of dg, % EE, rel12 and t50 values for the optimized formulation were found to be 57.54 +/- 1.38 mum, 86.28 +/- 1.32%, 77.23 +/- 2.78% and 5.60 +/- 0.32 h, respectively, which were in close agreement with those predicted by the mathematical models. The drug release from lipospheres followed first-order kinetics and was characterized by the Higuchi diffusion model. The optimized liposphere formulation developed was found to produce sustained anti-diabetic activity following oral administration in rats.

The Role and Characteristics of Tactile Graphics in Secondary Mathematics and Science Textbooks in Braille

ERIC Educational Resources Information Center

Smith, Derrick W.; Smothers, Sinikka M.

2012-01-01

Introduction: The purpose of the study presented here was to determine how well tactile graphics (specifically data analysis graphs) in secondary mathematics and science braille textbooks correlated with the print graphics. Method: A content analysis was conducted on 598 separate data analysis graphics from 10 mathematics and science textbooks.…

An Evaluation of Grades 9 and 10 Mathematics Textbooks vis-a-vis Fostering Problem Solving Skills

ERIC Educational Resources Information Center

Buishaw, Alemayehu; Ayalew, Assaye

2013-01-01

This study sought to evaluate the adequacy of integration of problematic situations and general problem-solving strategies (heuristics) in grades 9 and 10 mathematics textbooks. Grade 9 and grade 10 mathematics textbooks were used for analysis. Document analysis and interview were used as data gathering instruments. Document analysis was carried…

Landslide-susceptibility analysis using light detection and ranging-derived digital elevation models and logistic regression models: a case study in Mizunami City, Japan

NASA Astrophysics Data System (ADS)

Wang, Liang-Jie; Sawada, Kazuhide; Moriguchi, Shuji

2013-01-01

To mitigate the damage caused by landslide disasters, different mathematical models have been applied to predict landslide spatial distribution characteristics. Although some researchers have achieved excellent results around the world, few studies take the spatial resolution of the database into account. Four types of digital elevation model (DEM) ranging from 2 to 20 m derived from light detection and ranging technology to analyze landslide susceptibility in Mizunami City, Gifu Prefecture, Japan, are presented. Fifteen landslide-causative factors are considered using a logistic-regression approach to create models for landslide potential analysis. Pre-existing landslide bodies are used to evaluate the performance of the four models. The results revealed that the 20-m model had the highest classification accuracy (71.9%), whereas the 2-m model had the lowest value (68.7%). In the 2-m model, 89.4% of the landslide bodies fit in the medium to very high categories. For the 20-m model, only 83.3% of the landslide bodies were concentrated in the medium to very high classes. When the cell size decreases from 20 to 2 m, the area under the relative operative characteristic increases from 0.68 to 0.77. Therefore, higher-resolution DEMs would provide better results for landslide-susceptibility mapping.

Alignment Content Analysis of TIMSS and PISA Mathematics and Science Assessments Using the Surveys of Enacted Curriculum Methodology

ERIC Educational Resources Information Center

Council of Chief State School Officers, 2009

2009-01-01

In Fall 2008, the Council of Chief State School Officers (CCSSO) conducted an alignment content analysis of the 2007 TIMSS Mathematics and Science education assessments for students at grades 4 and 8 and the 2006 PISA Mathematics and Science Literacy assessments for students at age 15 (i.e., TIMSS--Trends in Mathematics and Science Study,…

Simple linear and multivariate regression models.

PubMed

Rodríguez del Águila, M M; Benítez-Parejo, N

2011-01-01

In biomedical research it is common to find problems in which we wish to relate a response variable to one or more variables capable of describing the behaviour of the former variable by means of mathematical models. Regression techniques are used to this effect, in which an equation is determined relating the two variables. While such equations can have different forms, linear equations are the most widely used form and are easy to interpret. The present article describes simple and multiple linear regression models, how they are calculated, and how their applicability assumptions are checked. Illustrative examples are provided, based on the use of the freely accessible R program. Copyright © 2011 SEICAP. Published by Elsevier Espana. All rights reserved.

Approximate Model of Zone Sedimentation

NASA Astrophysics Data System (ADS)

Dzianik, František

2011-12-01

The process of zone sedimentation is affected by many factors that are not possible to express analytically. For this reason, the zone settling is evaluated in practice experimentally or by application of an empirical mathematical description of the process. The paper presents the development of approximate model of zone settling, i.e. the general function which should properly approximate the behaviour of the settling process within its entire range and at the various conditions. Furthermore, the specification of the model parameters by the regression analysis of settling test results is shown. The suitability of the model is reviewed by graphical dependencies and by statistical coefficients of correlation. The approximate model could by also useful on the simplification of process design of continual settling tanks and thickeners.

Permeability Evaluation Through Chitosan Membranes Using Taguchi Design

PubMed Central

Sharma, Vipin; Marwaha, Rakesh Kumar; Dureja, Harish

2010-01-01

In the present study, chitosan membranes capable of imitating permeation characteristics of diclofenac diethylamine across animal skin were prepared using cast drying method. The effect of concentration of chitosan, concentration of cross-linking agent (NaTPP), crosslinking time was studied using Taguchi design. Taguchi design ranked concentration of chitosan as the most important factor influencing the permeation parameters of diclofenac diethylamine. The flux of the diclofenac diethylamine solution through optimized chitosan membrane (T9) was found to be comparable to that obtained across rat skin. The mathematical model developed using multilinear regression analysis can be used to formulate chitosan membranes that can mimic the desired permeation characteristics. The developed chitosan membranes can be utilized as a substitute to animal skin for in vitro permeation studies. PMID:21179329

Permeability evaluation through chitosan membranes using taguchi design.

PubMed

Sharma, Vipin; Marwaha, Rakesh Kumar; Dureja, Harish

2010-01-01

In the present study, chitosan membranes capable of imitating permeation characteristics of diclofenac diethylamine across animal skin were prepared using cast drying method. The effect of concentration of chitosan, concentration of cross-linking agent (NaTPP), crosslinking time was studied using Taguchi design. Taguchi design ranked concentration of chitosan as the most important factor influencing the permeation parameters of diclofenac diethylamine. The flux of the diclofenac diethylamine solution through optimized chitosan membrane (T9) was found to be comparable to that obtained across rat skin. The mathematical model developed using multilinear regression analysis can be used to formulate chitosan membranes that can mimic the desired permeation characteristics. The developed chitosan membranes can be utilized as a substitute to animal skin for in vitro permeation studies.

Computer-aided molecular modeling techniques for predicting the stability of drug cyclodextrin inclusion complexes in aqueous solutions

NASA Astrophysics Data System (ADS)

Faucci, Maria Teresa; Melani, Fabrizio; Mura, Paola

2002-06-01

Molecular modeling was used to investigate factors influencing complex formation between cyclodextrins and guest molecules and predict their stability through a theoretical model based on the search for a correlation between experimental stability constants ( Ks) and some theoretical parameters describing complexation (docking energy, host-guest contact surfaces, intermolecular interaction fields) calculated from complex structures at a minimum conformational energy, obtained through stochastic methods based on molecular dynamic simulations. Naproxen, ibuprofen, ketoprofen and ibuproxam were used as model drug molecules. Multiple Regression Analysis allowed identification of the significant factors for the complex stability. A mathematical model ( r=0.897) related log Ks with complex docking energy and lipophilic molecular fields of cyclodextrin and drug.

Clinical multifactorial analysis of early postoperative seizures in elderly patients following meningioma resection

PubMed Central

ZHANG, BO; WANG, DAN; GUO, YUNBAO; YU, JINLU

2015-01-01

The aim of the present study was to identify the major factors correlated with early postoperative seizures in elderly patients who had undergone a meningioma resection, and subsequently, to develop a logistic regression equation for assessing the seizures risk. Fourteen factors possibly correlated with early postoperative seizures in a cohort of 209 elderly patients who had undergone meningioma resection, as analyzed by multifactorial stepwise logistic regression. Phenobarbital sodium (0.1 g, intramuscularly) was administered to all 209 patients 30 min prior to undergoing surgery. All the patients had no previous history of seizures. The correlation of the 14 clinical factors (gender, tumor site, dyskinesia, peritumoral brain edema (PTBE), tumor diameter, pre- and postoperative prophylaxes, surgery time, tumor adhesion, circumscription, blood supply, intraoperative transfusion, original site of the tumor and dysphasia) was assessed in association with the risk for post-operative seizures. Tumor diameter, postoperative prophylactic antiepileptic drug (PPAD) administration, PTBE and tumor site were entered as risk factors into a mathematical regression model. The odds ratio (OR) of the tumor diameter was >1, and PPAD administration showed an OR >1, relative to a non-prophylactic group. A logistic regression equation was obtained and the sensitivity, specificity and misdiagnosis rates were 91.4, 74.3 and 25.7%, respectively. Tumor diameter, PPAD administration, PTBE and tumor site were closely correlated with early postoperative seizures; PTBE and PPAD administration were risk and protective factors, respectively. PMID:26137257

Modeling of laser transmission contour welding process using FEA and DoE

NASA Astrophysics Data System (ADS)

Acherjee, Bappa; Kuar, Arunanshu S.; Mitra, Souren; Misra, Dipten

2012-07-01

In this research, a systematic investigation on laser transmission contour welding process is carried out using finite element analysis (FEA) and design of experiments (DoE) techniques. First of all, a three-dimensional thermal model is developed to simulate the laser transmission contour welding process with a moving heat source. The commercial finite element code ANSYS® multi-physics is used to obtain the numerical results by implementing a volumetric Gaussian heat source, and combined convection-radiation boundary conditions. Design of experiments together with regression analysis is then employed to plan the experiments and to develop mathematical models based on simulation results. Four key process parameters, namely power, welding speed, beam diameter, and carbon black content in absorbing polymer, are considered as independent variables, while maximum temperature at weld interface, weld width, and weld depths in transparent and absorbing polymers are considered as dependent variables. Sensitivity analysis is performed to determine how different values of an independent variable affect a particular dependent variable.

Exsanguinated blood volume estimation using fractal analysis of digital images.

PubMed

Sant, Sonia P; Fairgrieve, Scott I

2012-05-01

The estimation of bloodstain volume using fractal analysis of digital images of passive blood stains is presented. Binary digital photos of bloodstains of known volumes (ranging from 1 to 7 mL), dispersed in a defined area, were subjected to image analysis using FracLac V. 2.0 for ImageJ. The box-counting method was used to generate a fractal dimension for each trial. A positive correlation between the generated fractal number and the volume of blood was found (R(2) = 0.99). Regression equations were produced to estimate the volume of blood in blind trials. An error rate ranging from 78% for 1 mL to 7% for 6 mL demonstrated that as the volume increases so does the accuracy of the volume estimation. This method used in the preliminary study proved that bloodstain patterns may be deconstructed into mathematical parameters, thus removing the subjective element inherent in other methods of volume estimation. © 2012 American Academy of Forensic Sciences.

Detecting isotopic ratio outliers

NASA Astrophysics Data System (ADS)

Bayne, C. K.; Smith, D. H.

An alternative method is proposed for improving isotopic ratio estimates. This method mathematically models pulse-count data and uses iterative reweighted Poisson regression to estimate model parameters to calculate the isotopic ratios. This computer-oriented approach provides theoretically better methods than conventional techniques to establish error limits and to identify outliers.

Mathematics is always invisible, Professor Dowling

NASA Astrophysics Data System (ADS)

Cable, John

2015-09-01

This article provides a critical evaluation of a technique of analysis, the Social Activity Method, recently offered by Dowling (2013) as a `gift' to mathematics education. The method is found to be inadequate, firstly, because it employs a dichotomy (between `expression' and `content') instead of a finer analysis (into symbols, concepts and setting or phenomena), and, secondly, because the distinction between `public' and `esoteric' mathematics, although interesting, is allowed to obscure the structure of the mathematics itself. There is also criticism of what Dowling calls the `myth of participation', which denies the intimate links between mathematics and the rest of the universe that lie at the heart of mathematical pedagogy. Behind all this lies Dowling's `essentially linguistic' conception of mathematics, which is criticised on the dual ground that it ignores the chastening experience of formalism in mathematical philosophy and that linguistics itself has taken a wrong turn and ignores lessons that might be learnt from mathematics education.

Factors predicting teachers' attitudes towards the use of ICT in teaching and learning

NASA Astrophysics Data System (ADS)

Ayub, Ahmad Fauzi Mohd; Bakar, Kamariah Abu; Ismail, Rohayati

2015-10-01

Technology has revolutionized in the field of Education. The importance of technology in schools cannot be ignored. While it is important that mathematics teachers should have positive attitudes towards adopting ICT in their teaching, various problems can arise when integrating ICT into classroom lessons. This study explored the factors that influence the attitudes of mathematic teachers in the integration of ICT in the teaching and learning process. A total of 187 mathematics teachers from the state of Selangor in Malaysia were randomly selected from a stratified cluster sample. The research examined five factors that were postulated to impact teachers' attitudes towards the integration of ICT in their lessons, viz. teachers' technology competence, school culture, access to ICT, school support, and years of classroom teaching experience. The findings showed that the teachers' attitudes towards using ICT in teaching and learning were positively correlated with the teachers' technology competence [r = .41; p < .01], ICT school culture [r = .261; p < .01], school support [r = .366; p < .01] and access to ICT resources [r = .220; p < .01]. However, a negative relationship existed between years of teaching and attitudes towards using ICT in teaching and learning [r = -0.192; p < .01]. A multiple regression analysis showed that 29.1% of the variation in teachers' attitudes towards using ICT in the classroom was explained by the variation in teachers' technology competence, school support and school culture, with the effects of teaching experience and ICT resource access being negligible.

Cardiorespiratory Fitness and Muscular Strength as Mediators of the Influence of Fatness on Academic Achievement.

PubMed

García-Hermoso, Antonio; Esteban-Cornejo, Irene; Olloquequi, Jordi; Ramírez-Vélez, Robinson

2017-08-01

To examine the combined association of fatness and physical fitness components (cardiorespiratory fitness [CRF] and muscular strength) with academic achievement, and to determine whether CRF and muscular strength are mediators of the association between fatness and academic achievement in a nationally representative sample of adolescents from Chile. Data were obtained for a sample of 36 870 adolescents (mean age, 13.8 years; 55.2% boys) from the Chilean System for the Assessment of Educational Quality test for eighth grade in 2011, 2013, and 2014. Physical fitness tests included CRF (20-m shuttle run) and muscular strength (standing long jump). Weight, height, and waist circumference were assessed, and body mass index and waist circumference-to-height ratio were calculated. Academic achievement in language and mathematics was assessed using standardized tests. The PROCESS script developed by Hayes was used for mediation analysis. Compared with unfit and high-fatness adolescents, fit and low-fatness adolescents had significantly higher odds for attaining high academic achievement in language and mathematics. However, in language, unfit and low-fatness adolescents did not have significantly higher odds for obtaining high academic achievement. Those with high fatness had higher academic achievement (both language and mathematics) if they were fit. Linear regression models suggest a partial or full mediation of physical fitness in the association of fatness variables with academic achievement. CRF and muscular strength may attenuate or even counteract the adverse influence of fatness on academic achievement in adolescents. Copyright © 2017 Elsevier Inc. All rights reserved.

Teacher's Guide to Secondary Mathematics.

ERIC Educational Resources Information Center

Duval County Schools, Jacksonville, FL.

This is a teacher's guide to secondary school mathematics. Developed for use in the Duval County Public Schools, Jacksonville, Florida. Areas of mathematics covered are algebra, analysis, calculus, computer literacy, computer science, geometry, analytic geometry, general mathematics, consumer mathematics, pre-algebra, probability and statistics,…

A structural equation modeling analysis of students' understanding in basic mathematics

NASA Astrophysics Data System (ADS)

Oktavia, Rini; Arif, Salmawaty; Ferdhiana, Ridha; Yuni, Syarifah Meurah; Ihsan, Mahyus

2017-11-01

This research, in general, aims to identify incoming students' understanding and misconceptions of several basic concepts in mathematics. The participants of this study are the 2015 incoming students of Faculty of Mathematics and Natural Science of Syiah Kuala University, Indonesia. Using an instrument that were developed based on some anecdotal and empirical evidences on students' misconceptions, a survey involving 325 participants was administered and several quantitative and qualitative analysis of the survey data were conducted. In this article, we discuss the confirmatory factor analysis using Structural Equation Modeling (SEM) on factors that determine the new students' overall understanding of basic mathematics. The results showed that students' understanding on algebra, arithmetic, and geometry were significant predictors for their overall understanding of basic mathematics. This result supported that arithmetic and algebra are not the only predictors of students' understanding of basic mathematics.

A mathematical model for ethanol fermentation from oil palm trunk sap using Saccharomyces cerevisiae

NASA Astrophysics Data System (ADS)

Sultana, S.; Jamil, Norazaliza Mohd; Saleh, E. A. M.; Yousuf, A.; Faizal, Che Ku M.

2017-09-01

This paper presents a mathematical model and solution strategy of ethanol fermentation for oil palm trunk (OPT) sap by considering the effect of substrate limitation, substrate inhibition product inhibition and cell death. To investigate the effect of cell death rate on the fermentation process we extended and improved the current mathematical model. The kinetic parameters of the model were determined by nonlinear regression using maximum likelihood function. The temporal profiles of sugar, cell and ethanol concentrations were modelled by a set of ordinary differential equations, which were solved numerically by the 4th order Runge-Kutta method. The model was validated by the experimental data and the agreement between the model and experimental results demonstrates that the model is reasonable for prediction of the dynamic behaviour of the fermentation process.

Statistical optimization of medium components and growth conditions by response surface methodology to enhance phenol degradation by Pseudomonas putida.

PubMed

Annadurai, Gurusamy; Ling, Lai Yi; Lee, Jiunn-Fwu

2008-02-28

In this work, a four-level Box-Behnken factorial design was employed combining with response surface methodology (RSM) to optimize the medium composition for the degradation of phenol by pseudomonas putida (ATCC 31800). A mathematical model was then developed to show the effect of each medium composition and their interactions on the biodegradation of phenol. Response surface method was using four levels like glucose, yeast extract, ammonium sulfate and sodium chloride, which also enabled the identification of significant effects of interactions for the batch studies. The biodegradation of phenol on Pseudomonas putida (ATCC 31800) was determined to be pH-dependent and the maximum degradation capacity of microorganism at 30 degrees C when the phenol concentration was 0.2 g/L and the pH of the solution was 7.0. Second order polynomial regression model was used for analysis of the experiment. Cubic and quadratic terms were incorporated into the regression model through variable selection procedures. The experimental values are in good agreement with predicted values and the correlation coefficient was found to be 0.9980.

Effectiveness of Mathematical Word Problem Solving Interventions for Students with Learning Disabilities and Mathematics Difficulties: A Meta-Analysis

ERIC Educational Resources Information Center

Lein, Amy E.

2016-01-01

This meta-analysis synthesized the findings from 23 published and five unpublished experimental or quasi-experimental group design studies on word problem-solving instruction for K-12 students with learning disabilities (LD) and mathematics difficulties (MD). A secondary purpose of this meta-analysis was to analyze the relation between treatment…

Predicting First Graders' Development of Calculation versus Word-Problem Performance: The Role of Dynamic Assessment.

PubMed

Seethaler, Pamela M; Fuchs, Lynn S; Fuchs, Douglas; Compton, Donald L

2012-02-01

The purpose of this study was to assess the value of dynamic assessment (DA; degree of scaffolding required to learn unfamiliar mathematics content) for predicting 1(st)-grade calculations (CA) and word problems (WP) development, while controlling for the role of traditional assessments. Among 184 1(st) graders, predictors (DA, Quantity Discrimination, Test of Mathematics Ability, language, and reasoning) were assessed near the start of 1(st) grade. CA and WP were assessed near the end of 1(st) grade. Planned regression and commonality analyses indicated that for forecasting CA development, Quantity Discrimination, which accounted for 8.84% of explained variance, was the single most powerful predictor, followed by Test of Mathematics Ability and DA; language and reasoning were not uniquely predictive. By contrast, for predicting WP development, DA was the single most powerful predictor, which accounted for 12.01% of explained variance, with Test of Mathematics Ability, Quantity Discrimination, and language also uniquely predictive. Results suggest that different constellations of cognitive resources are required for CA versus WP development and that DA may be useful in predicting 1(st)-grade mathematics development, especially WP.

Predicting First Graders’ Development of Calculation versus Word-Problem Performance: The Role of Dynamic Assessment

PubMed Central

Seethaler, Pamela M.; Fuchs, Lynn S.; Fuchs, Douglas; Compton, Donald L.

2012-01-01

The purpose of this study was to assess the value of dynamic assessment (DA; degree of scaffolding required to learn unfamiliar mathematics content) for predicting 1st-grade calculations (CA) and word problems (WP) development, while controlling for the role of traditional assessments. Among 184 1st graders, predictors (DA, Quantity Discrimination, Test of Mathematics Ability, language, and reasoning) were assessed near the start of 1st grade. CA and WP were assessed near the end of 1st grade. Planned regression and commonality analyses indicated that for forecasting CA development, Quantity Discrimination, which accounted for 8.84% of explained variance, was the single most powerful predictor, followed by Test of Mathematics Ability and DA; language and reasoning were not uniquely predictive. By contrast, for predicting WP development, DA was the single most powerful predictor, which accounted for 12.01% of explained variance, with Test of Mathematics Ability, Quantity Discrimination, and language also uniquely predictive. Results suggest that different constellations of cognitive resources are required for CA versus WP development and that DA may be useful in predicting 1st-grade mathematics development, especially WP. PMID:22347725

Measuring Developmental Students' Mathematics Anxiety

ERIC Educational Resources Information Center

Ding, Yanqing

2016-01-01

This study conducted an item-level analysis of mathematics anxiety and examined the dimensionality of mathematics anxiety in a sample of developmental mathematics students (N = 162) by Multi-dimensional Random Coefficients Multinominal Logit Model (MRCMLM). The results indicate a moderately correlated factor structure of mathematics anxiety (r =…

Objectively measured sedentary time and academic achievement in schoolchildren.

PubMed

Lopes, Luís; Santos, Rute; Mota, Jorge; Pereira, Beatriz; Lopes, Vítor

2017-03-01

This study aimed to evaluate the relationship between objectively measured total sedentary time and academic achievement (AA) in Portuguese children. The sample comprised of 213 children (51.6% girls) aged 9.46 ± 0.43 years, from the north of Portugal. Sedentary time was measured with accelerometry, and AA was assessed using the Portuguese Language and Mathematics National Exams results. Multilevel linear regression models were fitted to assess regression coefficients predicting AA. The results showed that objectively measured total sedentary time was not associated with AA, after adjusting for potential confounders.

Numerical investigations of hybrid rocket engines

NASA Astrophysics Data System (ADS)

Betelin, V. B.; Kushnirenko, A. G.; Smirnov, N. N.; Nikitin, V. F.; Tyurenkova, V. V.; Stamov, L. I.

2018-03-01

Paper presents the results of numerical studies of hybrid rocket engines operating cycle including unsteady-state transition stage. A mathematical model is developed accounting for the peculiarities of diffusion combustion of fuel in the flow of oxidant, which is composed of oxygen-nitrogen mixture. Three dimensional unsteady-state simulations of chemically reacting gas mixture above thermochemically destructing surface are performed. The results show that the diffusion combustion brings to strongly non-uniform fuel mass regression rate in the flow direction. Diffusive deceleration of chemical reaction brings to the decrease of fuel regression rate in the longitudinal direction.

Where are the women? Campus climate and the degree aspirations of women in science, technology, engineering and mathematics programs

NASA Astrophysics Data System (ADS)

Schulz, Phyllis

Women remain underrepresented in science, technology, engineering, and mathematics (STEM) at all levels of higher education, which has become a concern in the competitive global marketplace. Using both quantitative and qualitative analysis, this dissertation sought to learn more about how the campus climate and self-concept influence the degree aspirations of female undergraduate students majoring in STEM programs. Using the Beginning Post-Secondary dataset, regression analyses showed that a student's initial degree aspirations, SAT scores, and interactions with faculty were all positively related to their degree aspirations three years later. Interviews with seven current STEM undergraduates confirmed the importance of interaction with faculty and suggested undergraduate research and classroom experiences also play a role in the degree aspirations of STEM students. Three of the seven students interviewed began their undergraduate educations as non-STEM majors, suggesting that the traditional STEM pipeline may no longer be the norm. These findings suggest that both future research and current practitioners should focus on undergraduate STEM classroom and research experiences. Additionally, the characteristics of students who switch into STEM majors should be explored so that we may continue to expand the number of students pursuing STEM degrees.

Big school, small school: (re)testing assumptions about high school size, school engagement and mathematics achievement.

PubMed

Weiss, Christopher C; Carolan, Brian V; Baker-Smith, E Christine

2010-02-01

In an effort to increase both adolescents' engagement with school and academic achievement, school districts across the United States have created small high schools. However, despite the widespread adoption of size reduction reforms, relatively little is known about the relationship between size, engagement and outcomes in high school. In response, this article employs a composite measure of engagement that combines organizational, sociological, and psychological theories. We use this composite measure with the most recent nationally-representative dataset of tenth graders, Educational Longitudinal Study: 2002, (N = 10,946, 46% female) to better assess a generalizable relationship among school engagement, mathematics achievement and school size with specific focus on cohort size. Findings confirm these measures to be highly related to student engagement. Furthermore, results derived from multilevel regression analysis indicate that, as with school size, moderately sized cohorts or grade-level groups provide the greatest engagement advantage for all students and that there are potentially harmful changes when cohorts grow beyond 400 students. However, it is important to note that each group size affects different students differently, eliminating the ability to prescribe an ideal cohort or school size.

Virtual Monoenergetic Images From a Novel Dual-Layer Spectral Detector Computed Tomography Scanner in Portal Venous Phase: Adjusted Window Settings Depending on Assessment Focus Are Essential for Image Interpretation.

PubMed

Hickethier, Tilman; Iuga, Andra-Iza; Lennartz, Simon; Hauger, Myriam; Byrtus, Jonathan; Luetkens, Julian A; Haneder, Stefan; Maintz, David; Doerner, Jonas

We aimed to determine optimal window settings for conventional polyenergetic (PolyE) and virtual monoenergetic images (MonoE) derived from abdominal portal venous phase computed tomography (CT) examinations on a novel dual-layer spectral-detector CT (SDCT). From 50 patients, SDCT data sets MonoE at 40 kiloelectron volt as well as PolyE were reconstructed and best individual window width and level values manually were assessed separately for evaluation of abdominal arteries as well as for liver lesions. Via regression analysis, optimized individual values were mathematically calculated. Subjective image quality parameters, vessel, and liver lesion diameters were measured to determine influences of different W/L settings. Attenuation and contrast-to-noise values were significantly higher in MonoE compared with PolyE. Compared with standard settings, almost all adjusted W/L settings varied significantly and yielded higher subjective scoring. No differences were found between manually adjusted and mathematically calculated W/L settings. PolyE and MonoE from abdominal portal venous phase SDCT examinations require appropriate W/L settings depending on reconstruction technique and assessment focus.

Time-frequency analysis : mathematical analysis of the empirical mode decomposition.

DOT National Transportation Integrated Search

2009-01-01

Invented over 10 years ago, empirical mode : decomposition (EMD) provides a nonlinear : time-frequency analysis with the ability to successfully : analyze nonstationary signals. Mathematical : Analysis of the Empirical Mode Decomposition : is a...

A Structural Analysis on Korean Young Children's Mathematical Ability and Its Related Children's and Mothers' Variables

ERIC Educational Resources Information Center

Lee, Hye Jung; Kim, Jihyun

2016-01-01

The objective of this study is to examine the structural relationships among variables that predict the mathematical ability of young children, namely young children's mathematical attitude, exposure to private mathematical learning, mothers' view about their children's mathematical learning, and mothers' mathematical attitude. To this end, we…

Effect of Using Mathematics Laboratory in Teaching Mathematics on the Achievement of Mathematics Students

ERIC Educational Resources Information Center

Okigbo, Ebele C.; Osuafor, Abigail M.

2008-01-01

The study investigated the effect of using mathematics laboratory in teaching on students' achievement in Junior Secondary School Mathematics. A total of 100 JS 3 Mathematics students were involved in the study. The study is a quasi-experimental research. Results were analyzed using mean, standard deviation and analysis of covariance (ANCOVA).…

Unified heat kernel regression for diffusion, kernel smoothing and wavelets on manifolds and its application to mandible growth modeling in CT images.

PubMed

Chung, Moo K; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K

2015-05-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel method is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, the method is applied to characterize the localized growth pattern of mandible surfaces obtained in CT images between ages 0 and 20 by regressing the length of displacement vectors with respect to a surface template. Copyright © 2015 Elsevier B.V. All rights reserved.

Gender differences in mathematics anxiety and the relation to mathematics performance while controlling for test anxiety

PubMed Central

2012-01-01

Background Mathematics anxiety (MA), a state of discomfort associated with performing mathematical tasks, is thought to affect a notable proportion of the school age population. Some research has indicated that MA negatively affects mathematics performance and that girls may report higher levels of MA than boys. On the other hand some research has indicated that boys’ mathematics performance is more negatively affected by MA than girls’ performance is. The aim of the current study was to measure girls’ and boys’ mathematics performance as well as their levels of MA while controlling for test anxiety (TA) a construct related to MA but which is typically not controlled for in MA studies. Methods Four-hundred and thirty three British secondary school children in school years 7, 8 and 10 completed customised mental mathematics tests and MA and TA questionnaires. Results No gender differences emerged for mathematics performance but levels of MA and TA were higher for girls than for boys. Girls and boys showed a positive correlation between MA and TA and a negative correlation between MA and mathematics performance. TA was also negatively correlated with mathematics performance, but this relationship was stronger for girls than for boys. When controlling for TA, the negative correlation between MA and performance remained for girls only. Regression analyses revealed that MA was a significant predictor of performance for girls but not for boys. Conclusions Our study has revealed that secondary school children experience MA. Importantly, we controlled for TA which is typically not controlled for in MA studies. Girls showed higher levels of MA than boys and high levels of MA were related to poorer levels of mathematics performance. As well as potentially having a detrimental effect on ‘online’ mathematics performance, past research has shown that high levels of MA can have negative consequences for later mathematics education. Therefore MA warrants attention in the mathematics classroom, particularly because there is evidence that MA develops during the primary school years. Furthermore, our study showed no gender difference in mathematics performance, despite girls reporting higher levels of MA. These results might suggest that girls may have had the potential to perform better than boys in mathematics however their performance may have been attenuated by their higher levels of MA. Longitudinal research is needed to investigate the development of MA and its effect on mathematics performance. PMID:22769743

Gender differences in mathematics anxiety and the relation to mathematics performance while controlling for test anxiety.

PubMed

Devine, Amy; Fawcett, Kayleigh; Szűcs, Dénes; Dowker, Ann

2012-07-09

Mathematics anxiety (MA), a state of discomfort associated with performing mathematical tasks, is thought to affect a notable proportion of the school age population. Some research has indicated that MA negatively affects mathematics performance and that girls may report higher levels of MA than boys. On the other hand some research has indicated that boys' mathematics performance is more negatively affected by MA than girls' performance is. The aim of the current study was to measure girls' and boys' mathematics performance as well as their levels of MA while controlling for test anxiety (TA) a construct related to MA but which is typically not controlled for in MA studies. Four-hundred and thirty three British secondary school children in school years 7, 8 and 10 completed customised mental mathematics tests and MA and TA questionnaires. No gender differences emerged for mathematics performance but levels of MA and TA were higher for girls than for boys. Girls and boys showed a positive correlation between MA and TA and a negative correlation between MA and mathematics performance. TA was also negatively correlated with mathematics performance, but this relationship was stronger for girls than for boys. When controlling for TA, the negative correlation between MA and performance remained for girls only. Regression analyses revealed that MA was a significant predictor of performance for girls but not for boys. Our study has revealed that secondary school children experience MA. Importantly, we controlled for TA which is typically not controlled for in MA studies. Girls showed higher levels of MA than boys and high levels of MA were related to poorer levels of mathematics performance. As well as potentially having a detrimental effect on 'online' mathematics performance, past research has shown that high levels of MA can have negative consequences for later mathematics education. Therefore MA warrants attention in the mathematics classroom, particularly because there is evidence that MA develops during the primary school years. Furthermore, our study showed no gender difference in mathematics performance, despite girls reporting higher levels of MA. These results might suggest that girls may have had the potential to perform better than boys in mathematics however their performance may have been attenuated by their higher levels of MA. Longitudinal research is needed to investigate the development of MA and its effect on mathematics performance.

Regression Analyses of Self-Regulatory Concepts to Predict Community College Math Achievement and Persistence

ERIC Educational Resources Information Center

Gramlich, Stephen Peter

2010-01-01

Open door admissions at community colleges bring returning adults, first timers, low achievers, disabled persons, and immigrants. Passing and retention rates for remedial and non-developmental math courses can be comparatively inadequate (LAVC, 2005; CCPRDC, 2000; SBCC, 2004; Seybert & Soltz, 1992; Waycaster, 2002). Mathematics achievement…

Attitudes of university precalculus students toward mathematics.

PubMed

Alkhateeb, Haitham M; Mji, Andile

2005-04-01

To investigate the attitudes of 200 university students (83% freshmen) toward mathematics, a questionnaire was administered to report on their attitudes toward mathematics. Analysis indicated that students studying precalculus had a somewhat positive attitude toward mathematics.

Mathematical Working Space and Paradigms as an Analysis Tool for the Teaching and Learning of Analysis

ERIC Educational Resources Information Center

Delgadillo, Elizabeth Montoya; Vivier, Laurent

2016-01-01

Mathematical working space (MWS) is a model that is used in research in mathematics education, particularly in the field of geometry. Some MWS elements are independent of the field while other elements must be adapted to the field in question. In this paper, we develop the MWS model for the field of analysis with an identification of paradigms. We…

Dynamic Geometry Software Improves Mathematical Achievement: Systematic Review and Meta-Analysis

ERIC Educational Resources Information Center

Chan, Kan Kan; Leung, Siu Wai

2014-01-01

Dynamic geometry software (DGS) aims to enhance mathematics education. This systematic review and meta-analysis evaluated the quasi-experimental studies on the effectiveness of DGS-based instruction in improving students' mathematical achievement. Research articles published between 1990 and 2013 were identified from major databases according to a…

Primary Trait Analysis to Assess a Learner-Centered, Upper-Level Mathematics Course

ERIC Educational Resources Information Center

Alsardary, Salar; Pontiggia, Laura; Hamid, Mohammed; Blumberg, Phyllis

2011-01-01

This study presents a primary trait analysis of a learner-centered, discrete mathematics course based on student-to-student instruction. The authors developed a scoring rubric for the primary traits: conceptual knowledge, procedural knowledge, application of understanding, and mathematical communication skills. Eleven students took an exam…

Research in progress in applied mathematics, numerical analysis, and computer science

NASA Technical Reports Server (NTRS)

1990-01-01

Research conducted at the Institute in Science and Engineering in applied mathematics, numerical analysis, and computer science is summarized. The Institute conducts unclassified basic research in applied mathematics in order to extend and improve problem solving capabilities in science and engineering, particularly in aeronautics and space.

Problematising the Pursuit of Progress in Mathematics Education

ERIC Educational Resources Information Center

Llewellyn, Anna

2016-01-01

In this article, I use a Foucauldian poststructural analysis to examine productions of progress within key discursive spaces of mathematics education. These sites of production are educational policy, mathematics education research and case studies of primary school student-teachers in England. From my analysis, I show how progress governs what is…

The Attitudes of First Year Senior Secondary School Students toward Their Science Classes in the Sudan

NASA Astrophysics Data System (ADS)

Lado, Longun Moses

This study examined the influence of a set of relevant independent variables on students' decision to major in math or science disciplines, on the one hand, or arts or humanities disciplines, on the other. The independent variables of interest in the study were students' attitudes toward science, their gender, their socioeconomic status, their age, and the strength and direction of parents' and peers' influences on their academic decisions. The study answered five research questions that concerned students' intention in math or science, the association between students' attitudes and their choice to major in math or science, the extent to which parents' and peers' perspectives influence students' choice of major, and the influence of a combination of relevant variables on students' choice of major. The scholarly context for the study was literature relating to students' attitudes toward science and math, their likelihood of taking courses or majoring in science or math and various conditions influencing their attitudes and actions with respect to enrollment in science or math disciplines. This literature suggested that students' experiences, their gender, parents' and peers' influence, their socio-economic status, teachers' treatment of them, school curricula, school culture, and other variables may influence students' attitudes toward science and math and their decision regarding the study of these subjects. The study used a questionnaire comprised of 28 items to elicit information from students. Based upon cluster sampling of secondary schools, the researcher surveyed 1000 students from 10 secondary schools and received 987 responses. The researcher used SPSS to analyze students' responses. Descriptive statistics, logistic regression, and multiple regression analyses to provide findings that address the study's research questions. The following are the major findings from the study: (1) The instrument used to measure students' attitudes toward science and mathematics was not highly reliable, perhaps contributing to an attenuation of the relationship between attitude toward science and mathematics and choice of a science or mathematics major (rather than an arts or humanities major). (2) Far more students than the researcher had anticipated provided responses indicating that they planned to major in a science or mathematics discipline rather than an arts or humanities discipline. (3) Students' attitudes towards math and science were more favorable than the researcher anticipated based on findings from previous related studies. This result suggests the possibility of social desirability bias in students' responses. (4) Three significant predicator variables contributed to a significant logistic regression equation in which choice of science or mathematics major was the dependent variable: gender (negative association), attitude toward science and math (positive association), and peer influence 1 (positive association). Gender was the strongest predictor. (5) Five significant predictor variables contributed to a significant multiple linear regression equation in which attitude toward science and mathematics was the dependent variable: peer influence 1 (positive association), parent influence 1 (positive association), parent influence 2 (positive association), books in home (positive association), and peer influence 2 (positive association). The results reveal that among the targeted variables (gender, attitude, peer influence 1, peer influence 2, parent influence 1, parent influence 2, books in home, and age) only gender, peer influence 1, and attitude were significant predictors of students' major in math or science.

Graphing Calculator Exposure of Mathematics Learning in a Partially Technology Incorporated Environment

ERIC Educational Resources Information Center

Kharuddin, Azrul Fazwan; Ismail, Noor Azina

2017-01-01

Integrating technology in the mathematics curriculum has become a necessary task for curriculum developers as well as mathematics practitioners across the world and time. In general research studies seeking a better understanding of how best to integrate mathematics analysis tools with mathematics subject matter normally observe mathematics…

Mathematical Writing Errors in Expository Writings of College Mathematics Students

ERIC Educational Resources Information Center

Guce, Ivee K.

2017-01-01

Despite the efforts to confirm the effectiveness of writing in learning mathematics, analysis on common errors in mathematical writings has not received sufficient attention. This study aimed to provide an account of the students' procedural explanations in terms of their commonly committed errors in mathematical writing. Nine errors in…

Pre-Service Teachers' Mathematics Content Knowledge: Implications for How Mathematics Is Taught in Higher Education

ERIC Educational Resources Information Center

Lowrie, Tom; Jorgensen, Robyn

2016-01-01

This investigation explored pre-service teachers' mathematics content knowledge (MCK) and beliefs associated with mathematics education practices. An Exploratory Factor Analysis, conducted on a beliefs and attitudes questionnaire, produced three common attitude factors associated with (1) inquiry-based teaching; (2) how mathematics knowledge is…

Special relativity from observer's mathematics point of view

NASA Astrophysics Data System (ADS)

Khots, Boris; Khots, Dmitriy

2015-09-01

When we create mathematical models for quantum theory of light we assume that the mathematical apparatus used in modeling, at least the simplest mathematical apparatus, is infallible. In particular, this relates to the use of "infinitely small" and "infinitely large" quantities in arithmetic and the use of Newton - Cauchy definitions of a limit and derivative in analysis. We believe that is where the main problem lies in contemporary study of nature. We have introduced a new concept of Observer's Mathematics (see www.mathrelativity.com). Observer's Mathematics creates new arithmetic, algebra, geometry, topology, analysis and logic which do not contain the concept of continuum, but locally coincide with the standard fields. We use Einstein special relativity principles and get the analogue of classical Lorentz transformation. This work considers this transformation from Observer's Mathematics point of view.

Value of Construction Company and its Dependence on Significant Variables

NASA Astrophysics Data System (ADS)

Vítková, E.; Hromádka, V.; Ondrušková, E.

2017-10-01

The paper deals with the value of the construction company assessment respecting usable approaches and determinable variables. The reasons of the value of the construction company assessment are different, but the most important reasons are the sale or the purchase of the company, the liquidation of the company, the fusion of the company with another subject or the others. According the reason of the value assessment it is possible to determine theoretically different approaches for valuation, mainly it concerns about the yield method of valuation and the proprietary method of valuation. Both approaches are dependant of detailed input variables, which quality will influence the final assessment of the company´s value. The main objective of the paper is to suggest, according to the analysis, possible ways of input variables, mainly in the form of expected cash-flows or the profit, determination. The paper is focused mainly on methods of time series analysis, regression analysis and mathematical simulation utilization. As the output, the results of the analysis on the case study will be demonstrated.

Elaine Hale | NREL

Science.gov Websites

Analysis Center. Areas of Expertise Mathematical modeling, simulation, and optimization of complex Industrial and Applied Mathematics Mathematical Optimization Society Featured Publications Stoll, Brady

A new approach to correct the QT interval for changes in heart rate using a nonparametric regression model in beagle dogs.

PubMed

Watanabe, Hiroyuki; Miyazaki, Hiroyasu

2006-01-01

Over- and/or under-correction of QT intervals for changes in heart rate may lead to misleading conclusions and/or masking the potential of a drug to prolong the QT interval. This study examines a nonparametric regression model (Loess Smoother) to adjust the QT interval for differences in heart rate, with an improved fitness over a wide range of heart rates. 240 sets of (QT, RR) observations collected from each of 8 conscious and non-treated beagle dogs were used as the materials for investigation. The fitness of the nonparametric regression model to the QT-RR relationship was compared with four models (individual linear regression, common linear regression, and Bazett's and Fridericia's correlation models) with reference to Akaike's Information Criterion (AIC). Residuals were visually assessed. The bias-corrected AIC of the nonparametric regression model was the best of the models examined in this study. Although the parametric models did not fit, the nonparametric regression model improved the fitting at both fast and slow heart rates. The nonparametric regression model is the more flexible method compared with the parametric method. The mathematical fit for linear regression models was unsatisfactory at both fast and slow heart rates, while the nonparametric regression model showed significant improvement at all heart rates in beagle dogs.

Mathematical Modelling Research in Turkey: A Content Analysis Study

ERIC Educational Resources Information Center

Çelik, H. Coskun

2017-01-01

The aim of the present study was to examine the mathematical modelling studies done between 2004 and 2015 in Turkey and to reveal their tendencies. Forty-nine studies were selected using purposeful sampling based on the term, "mathematical modelling" with Higher Education Academic Search Engine. They were analyzed with content analysis.…

Schooled Mathematics and Cultural Knowledge

ERIC Educational Resources Information Center

de Abreu, Guida; Cline, Tony

2003-01-01

In this article it is argued that due recognition of the cultural nature of schooled mathematics requires an analysis that locates these practices in their social-political context. That analysis will need to provide an account of the social valorisation of mathematical practices and its impact on learning. It is suggested that the link between…

Selecting Intervention Strategies: Using Brief Experimental Analysis for Mathematics Problems

ERIC Educational Resources Information Center

Codding, Robin S.; Baglici, Stephanie; Gottesman, Dana; Johnson, Mitchelle; Kert, Allison Schaffer; Lebeouf, Patricia

2009-01-01

Although brief experimental analysis (BEA) procedures have been effective for aiding instructional decision making in the area of reading, there is a paucity of research extending this technology to mathematics. This study extends the literature on mathematics BEA by using an abridged data series that compares skill- and performance-based…

Neutral model analysis of landscape patterns from mathematical morphology

Treesearch

Kurt H. Riitters; Peter Vogt; Pierre Soille; Jacek Kozak; Christine Estreguil

2007-01-01

Mathematical morphology encompasses methods for characterizing land-cover patterns in ecological research and biodiversity assessments. This paper reports a neutral model analysis of patterns in the absence of a structuring ecological process, to help set standards for comparing and interpreting patterns identified by mathematical morphology on real land-cover maps. We...

Humanizing Mathematics: An Amalgamation of Constructionist Theory and Situated Cognition in the Mathematics Classroom

ERIC Educational Resources Information Center

Reilly, Brian M.

2017-01-01

A primary contributor to facilitating student learning in mathematics includes the mathematics teacher. The design of instructional delivery, presentation of engaging activities and analysis of student feedback are the key responsibilities that mathematics teachers are tasked with in order to present learning opportunities to the students. The…

Mathematics Placement Test: Typical Results with Unexpected Outcomes

ERIC Educational Resources Information Center

Ingalls, Victoria

2011-01-01

Based on the results of a prior case-study analysis of mathematics placement at one university, the mathematics department developed and piloted a mathematics placement test. This article describes the implementation process for a mathematics placement test and further analyzes the test results for the pilot group. As an unexpected result, the…

Content Analysis of Jordanian Elementary Textbooks during 1970-2013 as Case Study

ERIC Educational Resources Information Center

Abed, Eman Rasmi; Al-Absi, Mohammad Mustafa

2015-01-01

This study aims to determine types of mathematic disciplines (in term of topics) in Jordanian Elementary textbooks. This study evaluates mathematics text books especially in the period between 1970 and 2013 and identifies types and quantities of mathematics. To examine the relative quantity of mathematics, branches of mathematics, presentation…

Students' Satisfaction with an Undergraduate Primary Education Teaching Practicum Design on Developing Technological, Pedagogical and Mathematical Knowledge

NASA Astrophysics Data System (ADS)

Doukakis, Spyros; Koilias, Christos; Chionidou-Moskofoglou, Maria

During the 2008-2009 spring semester, 25 fourth-year undergraduate primary teachers attended the compulsory course "Teaching Mathematics-Practicum Phase". The course was organised so as to incorporate ICT and special mathematical scenarios in the teaching approaches of undergraduate primary teachers. This article presents course satisfaction of participants as found in the research study. A set of powerful ordinal regression methods has been applied on a survey database. The most important results focus on the determination of the course's weak and strong points, according to the MUSA methodology. The results show a high satisfaction level from the course. The global satisfaction level reaches 98% whereas partial (per criterion) satisfaction levels range from 90% to 97%, the lowest rate corresponding to the theoretical component of the course. The findings raise a number of research questions regarding ICT integration in undergraduate primary teachers' teaching practice.

Development and Validation of a Mathematical Model for Olive Oil Oxidation

NASA Astrophysics Data System (ADS)

Rahmouni, K.; Bouhafa, H.; Hamdi, S.

2009-03-01

A mathematical model describing the stability or the susceptibility to oxidation of extra virgin olive oil has been developed. The model has been resolved by an iterative method using differential finite method. It was validated by experimental data of extra virgin olive oil (EVOO) oxidation. EVOO stability was tested by using a Rancimat at four different temperatures 60, 70, 80 and 90° C until peroxide accumulation reached 20 [meq/kg]. Peroxide formation is speed relatively slow; fits zero order reaction with linear regression coefficients varying from 0, 98 to 0, 99. The mathematical model was used to predict the shelf life of bulk conditioned olive oil. This model described peroxide accumulation inside a container in excess of oxygen as a function of time at various positions from the interface air/oil. Good correlations were obtained between theoretical and experimental values.

From Efficacy Trial to Large Scale Effectiveness Trial: A Tier 2 Mathematics Intervention for First Graders with Difficulties in Mathematics

ERIC Educational Resources Information Center

Rolfhus, Eric; Clarke, Ben; Decker, Lauren E.; Williams, Chuck; Dimino, Joseph

2013-01-01

Large scale longitudinal research (Morgan, Farkas, & Wu, 2009) and a meta-analysis (Duncan et al., 2007) have found that early mathematics achievement is a strong predictor of later mathematics achievement. In fact, end of Kindergarten and end of grade 1 mathematics achievement on ECLS-K and similar mathematics proficiency measures tends to be…

Quantitative analysis of bayberry juice acidity based on visible and near-infrared spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao Yongni; He Yong; Mao Jingyuan

Visible and near-infrared (Vis/NIR) reflectance spectroscopy has been investigated for its ability to nondestructively detect acidity in bayberry juice. What we believe to be a new, better mathematic model is put forward, which we have named principal component analysis-stepwise regression analysis-backpropagation neural network (PCA-SRA-BPNN), to build a correlation between the spectral reflectivity data and the acidity of bayberry juice. In this model, the optimum network parameters,such as the number of input nodes, hidden nodes, learning rate, and momentum, are chosen by the value of root-mean-square (rms) error. The results show that its prediction statistical parameters are correlation coefficient (r) ofmore » 0.9451 and root-mean-square error of prediction(RMSEP) of 0.1168. Partial least-squares (PLS) regression is also established to compare with this model. Before doing this, the influences of various spectral pretreatments (standard normal variate, multiplicative scatter correction, S. Golay first derivative, and wavelet package transform) are compared. The PLS approach with wavelet package transform preprocessing spectra is found to provide the best results, and its prediction statistical parameters are correlation coefficient (r) of 0.9061 and RMSEP of 0.1564. Hence, these two models are both desirable to analyze the data from Vis/NIR spectroscopy and to solve the problem of the acidity prediction of bayberry juice. This supplies basal research to ultimately realize the online measurements of the juice's internal quality through this Vis/NIR spectroscopy technique.« less

The Interaction of Learning Disability Status and Student Demographic Characteristics on Mathematics Growth.

PubMed

Stevens, Joseph J; Schulte, Ann C

This study examined mathematics achievement growth of students without disabilities (SWoD) and students with learning disabilities (LD) and tested whether growth and LD status interacted with student demographic characteristics. Growth was estimated in a statewide sample of 79,554 students over Grades 3 to 7. The LD group was significantly lower in achievement in each grade and had less growth than the SWoD group. We also found that student demographic characteristics were significantly related to mathematics growth, but only three demographic characteristics were statistically significant as interactions. We found that LD-SWoD differences at Grade 3 were moderated by student sex, while Black race/ethnicity and free or reduced lunch (FRL) status moderated LD-SWoD differences at all grades. These results provide practitioners and policy makers with more specific information about which particular LD students show faster or slower growth in mathematics. Our results show that simply including predictors in a regression equation may produce different results than direct testing of interactions and achievement gaps may be larger for some LD subgroups of students than previously reported.

Young children's core symbolic and nonsymbolic quantitative knowledge in the prediction of later mathematics achievement.

PubMed

Geary, David C; vanMarle, Kristy

2016-12-01

At the beginning of preschool (M = 46 months of age), 197 (94 boys) children were administered tasks that assessed a suite of nonsymbolic and symbolic quantitative competencies as well as their executive functions, verbal and nonverbal intelligence, preliteracy skills, and their parents' education level. The children's mathematics achievement was assessed at the end of preschool (M = 64 months). We used a series of Bayesian and standard regression analyses to winnow this broad set of competencies down to the core subset of quantitative skills that predict later mathematics achievement, controlling other factors. This knowledge included children's fluency in reciting the counting string, their understanding of the cardinal value of number words, and recognition of Arabic numerals, as well as their sensitivity to the relative quantity of 2 collections of objects. The results inform theoretical models of the foundations of children's early quantitative development and have practical implications for the design of early interventions for children at risk for poor long-term mathematics achievement. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Guided Tour of Mathematical Methods - 2nd Edition

NASA Astrophysics Data System (ADS)

Snieder, Roel

2004-09-01

Mathematical methods are essential tools for all physical scientists. This second edition provides a comprehensive tour of the mathematical knowledge and techniques that are needed by students in this area. In contrast to more traditional textbooks, all the material is presented in the form of problems. Within these problems the basic mathematical theory and its physical applications are well integrated. The mathematical insights that the student acquires are therefore driven by their physical insight. Topics that are covered include vector calculus, linear algebra, Fourier analysis, scale analysis, complex integration, Green's functions, normal modes, tensor calculus, and perturbation theory. The second edition contains new chapters on dimensional analysis, variational calculus, and the asymptotic evaluation of integrals. This book can be used by undergraduates, and lower-level graduate students in the physical sciences. It can serve as a stand-alone text, or as a source of problems and examples to complement other textbooks. All the material is presented in the form of problems Mathematical insights are gained by getting the reader to develop answers themselves Many applications of the mathematics are given

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

PubMed

Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

2016-01-01

One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science

PubMed Central

Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

2016-01-01

One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

On the Formal-Logical Analysis of the Foundations of Mathematics Applied to Problems in Physics

NASA Astrophysics Data System (ADS)

Kalanov, Temur Z.

2016-03-01

Analysis of the foundations of mathematics applied to problems in physics was proposed. The unity of formal logic and of rational dialectics is methodological basis of the analysis. It is shown that critical analysis of the concept of mathematical quantity - central concept of mathematics - leads to the following conclusion: (1) The concept of ``mathematical quantity'' is the result of the following mental operations: (a) abstraction of the ``quantitative determinacy of physical quantity'' from the ``physical quantity'' at that the ``quantitative determinacy of physical quantity'' is an independent object of thought; (b) abstraction of the ``amount (i.e., abstract number)'' from the ``quantitative determinacy of physical quantity'' at that the ``amount (i.e., abstract number)'' is an independent object of thought. In this case, unnamed, abstract numbers are the only sign of the ``mathematical quantity''. This sign is not an essential sign of the material objects. (2) The concept of mathematical quantity is meaningless, erroneous, and inadmissible concept in science because it represents the following formal-logical and dialectical-materialistic error: negation of the existence of the essential sign of the concept (i.e., negation of the existence of the essence of the concept) and negation of the existence of measure of material object.

The Development and Implementation of an Inquiry-Based Poster Project on Sustainability in a Large Non-Majors Environmental Science Course

ERIC Educational Resources Information Center

Schmitt-Harsh, Mikaela; Harsh, Joseph A.

2013-01-01

In the past decade, systematic studies have indicated a significant regression in scientific literacy in nonscience students and students across science, technology, engineering, and mathematics disciplines in higher education. Of particular concern, evaluations of introductory lecture-based undergraduate courses have indicated deficiencies in…

Validity Evidence for Games as Assessment Environments. CRESST Report 773

ERIC Educational Resources Information Center

Delacruz, Girlie C.; Chung, Gregory K. W. K.; Baker, Eva L.

2010-01-01

This study provides empirical evidence of a highly specific use of games in education--the assessment of the learner. Linear regressions were used to examine the predictive and convergent validity of a math game as assessment of mathematical understanding. Results indicate that prior knowledge significantly predicts game performance. Results also…

Deriving the Quadratic Regression Equation Using Algebra

ERIC Educational Resources Information Center

Gordon, Sheldon P.; Gordon, Florence S.

2004-01-01

In discussions with leading educators from many different fields, MAA's CRAFTY (Curriculum Renewal Across the First Two Years) committee found that one of the most common mathematical themes in those other disciplines is the idea of fitting a function to a set of data in the least squares sense. The representatives of those partner disciplines…

Analysis mathematical literacy skills in terms of the students’ metacognition on PISA-CPS model

NASA Astrophysics Data System (ADS)

Ovan; Waluya, S. B.; Nugroho, S. E.

2018-03-01

This research was aimed to know the effectiveness of PISA-CPS model and desceibe the mathematical literacy skills (KLM) in terms of the students’ metacognition. This study used Mixed Methods approaches with the concurrent embedded desaign. The technique of data analysis on quantitative research done analysis of lesson plan, prerequisite test, test hypotesis 1 and hypotesis test. While qualitative research done data reduction, data presentation, and drawing conclution and data verification. The subject of this study was the students of Grade Eight (VIII) of SMP Islam Sultan Agung 4 Semarang, Central Java. The writer analyzed the data with quantitative and qualitative approaches based on the metacognition of the students in low, medium and high groups. Subsequently, taken the mathematical literacy skills (KLM) from students’ metacognition in low, medium, and high . The results of the study showed that the PISA-CPS model was complete and the students’ mathematical literacy skills in terms of the students’ metacognition taught by the PISA-CPS model was higher than the expository learning. metacognitions’ students classified low hadmathematical literacy skills (KLM) less good, metacognitions’ students classified medium had mathematical literacy skills (KLM) good enough, metacognitions’ students classified high had mathematical literacy skills (KLM) very good. Based onresult analysis got conclusion that the PISA-CPS model was effective toward the students’ mathematical literacy skills (KLM). To increase the students’ mathematical literacy skills (KLM), the teachers need to provide reinforcements in the form of the exercises so that the student’s mathematical literacy was achieved at level 5 and level 6.

Reflectance spectroscopy of fresh whole leaves for the estimation of chemical concentration

NASA Technical Reports Server (NTRS)

Curran, Paul J.; Dungan, Jennifer L.; Macler, Bruce A.; Plummer, Stephen E.; Peterson, David L.

1992-01-01

Remotely sensed plant-canopy data in the visible and near-IR ranges are used to establish relations between the canopy reflectance and the chemical content of the leaves. The mathematical relation is generated by means of stepwise regression based on the derivative reflectance at certain wavelengths. Fourier filtering and sample control are used to minimize instrument noise and spectral overlap respectively, and absorption features are noted that correspond to sugar and protein. The coefficients of determination between estimated and measured concentrations are at least 0.82 for such substances as starch and chlorophyll. It is recommended in the analysis of remotly sensed canopy data that the chemicals with strong spectral overlaps with the chemical of interest be accounted for in order to estimate foliar chemical concentrations accurately.

Toward an Analysis of Video Games for Mathematics Education

ERIC Educational Resources Information Center

Offenholley, Kathleen

2011-01-01

Video games have tremendous potential in mathematics education, yet there is a push to simply add mathematics to a video game without regard to whether the game structure suits the mathematics, and without regard to the level of mathematical thought being learned in the game. Are students practicing facts, or are they problem-solving? This paper…

A Critical Discourse Analysis of Practical Problems in a Foundation Mathematics Course at a South African University

ERIC Educational Resources Information Center

le Roux, Kate; Adler, Jill

2016-01-01

Mathematical problems that make links to the everyday and to disciplines other than mathematics--variously referred to as practical, realistic, real-world or applied problems in the literature--feature in school and undergraduate mathematics reforms aimed at increasing mathematics participation in contexts of inequity and diversity. In this…

The Unit of Analysis in Mathematics Education: Bridging the Political-Technical Divide?

ERIC Educational Resources Information Center

Ernest, Paul

2016-01-01

Mathematics education is a complex, multi-disciplinary field of study which treats a wide range of diverse but interrelated areas. These include the nature of mathematics, the learning of mathematics, its teaching, and the social context surrounding both the discipline and applications of mathematics itself, as well as its teaching and learning.…

Applying an Alternative Mathematics Pedagogy for Students with Weak Mathematics: Meta-Analysis of Alternative Pedagogies

ERIC Educational Resources Information Center

Lake, Warren; Wallin, Margie; Woolcott, Geoff; Boyd, Wendy; Foster, Alan; Markopoulos, Christos; Boyd, William

2017-01-01

Student mathematics performance and the need for work-ready graduates to be mathematics-competent is a core issue for many universities. While both student and teacher are responsible for learning outcomes, there is a need to explicitly acknowledge the weak mathematics foundation of many university students. A systematic literature review was…

An Analysis of Mathematics Interventions: Increased Time-on-Task Compared with Computer-Assisted Mathematics Instruction

ERIC Educational Resources Information Center

Calhoun, James M., Jr.

2011-01-01

Student achievement is not progressing on mathematics as measured by state, national, and international assessments. Much of the research points to mathematics curriculum and instruction as the root cause of student failure to achieve at levels comparable to other nations. Since mathematics is regarded as a gate keeper to many educational…

In the Middle of Nowhere: How a Textbook Can Position the Mathematics Learner

ERIC Educational Resources Information Center

Herbel-Eisenmann, Beth; Wagner, David

2005-01-01

We outline a framework for investigating how a mathematics textbook positions the mathematics learner. We use tools and concepts from discourse analysis, a field of linguistic scholarship, to illustrate the ways in which a textbook can position people in relation to mathematics and how the text can position the mathematics learner in relation to…

An Analysis of Pre-Service Mathematics Teachers' Performance in Modelling Tasks in Terms of Spatial Visualisation Ability

ERIC Educational Resources Information Center

Tasova, Halil Ibrahim; Delice, Ali

2012-01-01

Mathematical modelling involves mathematical constructions chosen to represent some real world situations and the relationships among them; it is the process of expressing a real world situation mathematically. Visualisation can play a significant role in the development of thinking or understanding mathematical concepts, and also makes abstract…

Integrating Social Justice with Mathematics and Science: An Analysis of Student Teacher Lessons

ERIC Educational Resources Information Center

Garii, Barbara; Rule, Audrey C.

2009-01-01

Student teachers have difficulty planning lessons that fully integrate social justice with mathematics/science content. This study was a content analysis of 26 poster presentations of mathematics or science lessons incorporating social justice issues made by student teachers (20F, 6M) at a mid-sized college in central New York State. The presented…

Mathematics in the Making: Mapping Verbal Discourse in Polya's "Let Us Teach Guessing" Lesson

ERIC Educational Resources Information Center

Truxaw, Mary P.; DeFranco, Thomas C.

2007-01-01

This paper describes a detailed analysis of verbal discourse within an exemplary mathematics lesson--that is, George Polya teaching in the Mathematics Association of America [MAA] video classic, "Let Us Teach Guessing" (1966). The results of the analysis reveal an inductive model of teaching that represents recursive cycles rather than linear…

Logical-Mathematical Constructions in an Initial Course at the University: A View of Their Syntactic, Semantic and Pragmatic Aspects

ERIC Educational Resources Information Center

Falsetti, Marcela; Alvarez, Marisa

2015-01-01

We present an analysis of students' formal constructions in mathematics regarding to syntactic, semantic and pragmatic aspects. The analyzed tasks correspond to students of the Course of Mathematics for the admission to the university. Our study was qualitative, consisted in the identification, analysis and interpretation, focused in logic…

Objects, Signs, and Representations in the Semio-Cognitive Analysis of the Processes Involved in Teaching and Learning Mathematics: A Duvalian Perspective

ERIC Educational Resources Information Center

Iori, Maura

2017-01-01

In mathematical activities and in the analysis of mathematics teaching-learning processes, "objects," "signs", and "representations" are often mentioned, where the meaning assigned to those words is sometimes very broad, sometimes limited, other times intuitive, allusive, or not completely clear. On the other hand, as…

The Development of a Mathematics Self-Report Inventory for Turkish Elementary Students

ERIC Educational Resources Information Center

Akin, Ayça; Güzeller, Cem Oktay; Evcan, Sinem Sezer

2016-01-01

The purpose of the current study is to develop a mathematics self-report inventory (MSRI) to measure Turkish elementary students' mathematics expectancy beliefs and task values based on the expectancy-value theory of achievement motivation. In Study-1 (n = 1,315), exploratory factor analysis (EFA) and reliability analysis are used to evaluate the…

Finnish Mathematics Teaching from a Reform Perspective: A Video-Based Case-Study Analysis

ERIC Educational Resources Information Center

Andrews, Paul

2013-01-01

This article offers a qualitative analysis of videotaped mathematics lessons taught by four teachers in a provincial university city in Finland. My study is framed not only by Finnish success on Programme for International Student Assessment (PISA) but also by the objectives of current mathematics education reform, which are consistent with PISA's…

Mathematics Majors at an All-Women's College: Exploring Identity and Context

ERIC Educational Resources Information Center

Musselman, Alexandria Theakston

2017-01-01

Drawing on identity theory, sociocultural theories of learning, and discourse analysis, I engage in an analysis of in-depth, individual interviews with four mathematics majors at an all-women's college over an academic year. The purpose of this qualitative study is to gain insight into the mathematical identities of senior women mathematics…

A Role for Language Analysis in Mathematics Textbook Analysis

ERIC Educational Resources Information Center

O'Keeffe, Lisa; O'Donoghue, John

2015-01-01

In current textbook analysis research, there is a strong focus on the content, structure and expectation presented by the textbook as elements for analysis. This research moves beyond such foci and proposes a framework for textbook language analysis which is intended to be integrated into an overall framework for mathematics textbook analysis. The…

The association of iron status with educational performance and intelligence among adolescents.

PubMed

Dissanayake, D S; Kumarasiri, P V R; Nugegoda, D B; Dissanayake, D M

2009-09-01

The aim was to identify the association of iron status with educational performance and intelligence of adolescents. This was a cross sectional comparative study among adolescents aged 13-15 years. Each iron deficient student was matched with an iron sufficient student from the same school, class and sex. Iron status was based on haemoglobin and serum ferritin levels. The marks for mathematics, science, Sinhala language and social science were considered to assess educational performance. Intelligence was measured by Raven's Standard progressive matrices. All the possible confounders and effect modifiers were considered. Home visits to a sub-sample checked the quality of data. The final analysis included 188 students (94 matched pairs). Neither educational performance nor intelligence showed significant associations with the iron status. The severity of the iron deficiency did not relate to these cognitive variables either. Twenty-three and 8 co-variables showed statistically significant associations with educational performance and intelligence respectively. Following a multiple regression analysis intelligence, the enthusiasm of the student towards learning, occupational ambition, household possession, problems at home and private tuition for mathematics were key factors predicting educational performance. Stunting and educational level of the mother were important factors influencing intelligence. Iron status does not play a major role in educational performance and intelligence of school going adolescents. Several factors affect educational performance and intelligence. This study highlights the difficulty in extrapolating the findings of similar studies to different ecological settings.

HbA1c values calculated from blood glucose levels using truncated Fourier series and implementation in standard SQL database language.

PubMed

Temsch, W; Luger, A; Riedl, M

2008-01-01

This article presents a mathematical model to calculate HbA1c values based on self-measured blood glucose and past HbA1c levels, thereby enabling patients to monitor diabetes therapy between scheduled checkups. This method could help physicians to make treatment decisions if implemented in a system where glucose data are transferred to a remote server. The method, however, cannot replace HbA1c measurements; past HbA1c values are needed to gauge the method. The mathematical model of HbA1c formation was developed based on biochemical principles. Unlike an existing HbA1c formula, the new model respects the decreasing contribution of older glucose levels to current HbA1c values. About 12 standard SQL statements embedded in a php program were used to perform Fourier transform. Regression analysis was used to gauge results with previous HbA1c values. The method can be readily implemented in any SQL database. The predicted HbA1c values thus obtained were in accordance with measured values. They also matched the results of the HbA1c formula in the elevated range. By contrast, the formula was too "optimistic" in the range of better glycemic control. Individual analysis of two subjects improved the accuracy of values and reflected the bias introduced by different glucometers and individual measurement habits.

Contemplating Symbolic Literacy of First Year Mathematics Students

ERIC Educational Resources Information Center

Bardini, Caroline; Pierce, Robyn; Vincent, Jill

2015-01-01

Analysis of mathematical notations must consider both syntactical aspects of symbols and the underpinning mathematical concept(s) conveyed. We argue that the construct of "syntax template" provides a theoretical framework to analyse undergraduate mathematics students' written solutions, where we have identified several types of…

Exploring Wind Power: Improving Mathematical Thinking through Digital Fabrication

ERIC Educational Resources Information Center

Tillman, Daniel A.; An, Song A.; Cohen, Jonathan D.; Kjellstrom, William; Boren, Rachel L.

2014-01-01

This mixed methods study examined the impacts of digital fabrication activities that were integrated into contextualized mathematics education. The study investigated the students' mathematics content knowledge and attitudes. Data analysis yielded two key findings regarding our intervention combined with the other mathematics activities resulted…

The Role of Reasoning in the Australian Curriculum: Mathematics

ERIC Educational Resources Information Center

McCluskey, Catherine; Mulligan, Joanne; Mitchelmore, Mike

2016-01-01

The mathematical proficiencies in the "Australian Curriculum: Mathematics" of understanding, problem solving, reasoning, and fluency are intended to be entwined actions that work together to build generalised understandings of mathematical concepts. A content analysis identifying the incidence of key proficiency terms (KPTs) embedded in…

Mathematics reflecting sensorimotor organization.

PubMed

McCollum, Gin

2003-02-01

This review combines short presentations of several mathematical approaches that conceptualize issues in sensorimotor neuroscience from different perspectives and levels of analysis. The intricate organization of neural structures and sensorimotor performance calls for characterization using a variety of mathematical approaches. This review points out the prospects for mathematical neuroscience: in addition to computational approaches, there is a wide variety of mathematical approaches that provide insight into the organization of neural systems. By starting from the perspective that provides the greatest clarity, a mathematical approach avoids specificity that is inaccurate in characterizing the inherent biological organization. Approaches presented include the mathematics of ordered structures, motion-phase space, subject-coincident coordinates, equivalence classes, topological biodynamics, rhythm space metric, and conditional dynamics. Issues considered in this paper include unification of levels of analysis, response equivalence, convergence, relationship of physics to motor control, support of rhythms, state transitions, and focussing on low-dimensional subspaces of a high-dimensional sensorimotor space.

A Western Dietary Pattern Is Associated with Poor Academic Performance in Australian Adolescents

PubMed Central

Nyaradi, Anett; Li, Jianghong; Hickling, Siobhan; Foster, Jonathan K.; Jacques, Angela; Ambrosini, Gina L.; Oddy, Wendy H.

2015-01-01

The aim of this study was to investigate cross-sectional associations between dietary patterns and academic performance among 14-year-old adolescents. Study participants were from the Western Australian Pregnancy Cohort (Raine) Study. A food frequency questionnaire was administered when the adolescents were 14 years old, and from the dietary data, a ‘Healthy’ and a ‘Western’ dietary pattern were identified by factor analysis. The Western Australian Literacy and Numeracy Assessment (WALNA) results from grade nine (age 14) were linked to the Raine Study data by The Western Australian Data Linkage Branch. Associations between the dietary patterns and the WALNA (mathematics, reading and writing scores) were assessed using multivariate linear regression models adjusting for family and socioeconomic characteristics. Complete data on dietary patterns, academic performance and covariates were available for individuals across the different analyses as follows: n = 779 for mathematics, n = 741 for reading and n = 470 for writing. Following adjustment, significant negative associations between the ‘Western’ dietary pattern and test scores for mathematics (β = −13.14; 95% CI: −24.57; −1.76); p = 0.024) and reading (β = −19.16; 95% CI: −29.85; −8.47; p ≤ 0.001) were observed. A similar trend was found with respect to writing (β = −17.28; 95% CI: −35.74; 1.18; p = 0.066). ANOVA showed significant trends in estimated means of academic scores across quartiles for both the Western and Healthy patterns. Higher scores for the ‘Western’ dietary pattern are associated with poorer academic performance in adolescence. PMID:25898417

The relationships between spatial ability, logical thinking, mathematics performance and kinematics graph interpretation skills of 12th grade physics students

NASA Astrophysics Data System (ADS)

Bektasli, Behzat

Graphs have a broad use in science classrooms, especially in physics. In physics, kinematics is probably the topic for which graphs are most widely used. The participants in this study were from two different grade-12 physics classrooms, advanced placement and calculus-based physics. The main purpose of this study was to search for the relationships between student spatial ability, logical thinking, mathematical achievement, and kinematics graphs interpretation skills. The Purdue Spatial Visualization Test, the Middle Grades Integrated Process Skills Test (MIPT), and the Test of Understanding Graphs in Kinematics (TUG-K) were used for quantitative data collection. Classroom observations were made to acquire ideas about classroom environment and instructional techniques. Factor analysis, simple linear correlation, multiple linear regression, and descriptive statistics were used to analyze the quantitative data. Each instrument has two principal components. The selection and calculation of the slope and of the area were the two principal components of TUG-K. MIPT was composed of a component based upon processing text and a second component based upon processing symbolic information. The Purdue Spatial Visualization Test was composed of a component based upon one-step processing and a second component based upon two-step processing of information. Student ability to determine the slope in a kinematics graph was significantly correlated with spatial ability, logical thinking, and mathematics aptitude and achievement. However, student ability to determine the area in a kinematics graph was only significantly correlated with student pre-calculus semester 2 grades. Male students performed significantly better than female students on the slope items of TUG-K. Also, male students performed significantly better than female students on the PSAT mathematics assessment and spatial ability. This study found that students have different levels of spatial ability, logical thinking, and mathematics aptitude and achievement levels. These different levels were related to student learning of kinematics and they need to be considered when kinematics is being taught. It might be easier for students to understand the kinematics graphs if curriculum developers include more activities related to spatial ability and logical thinking.

Multilingualism in indigenous mathematics education: an epistemic matter

NASA Astrophysics Data System (ADS)

Parra, Aldo; Trinick, Tony

2017-12-01

An investigation into an aspect of indigenous education provides the opportunity to forefront an epistemological discussion about mathematical knowledge. This paper analyses indigenous peoples' educational experiences in Colombia and Aotearoa/New Zealand of mathematics education, focusing on, among other things, sociolinguistic issues such as language planning. In these experiences, researchers, teachers and local communities, working together, elaborated their respective languages to create a corpus of lexicon that has enabled the teaching of Western mathematics. An analysis using decolonial theory is made, showing how this corpus development works to enable the teaching of [Western] mathematics resulted in investigations into culture, language and mathematics that revealed an interplay among knowledge and power. Such analysis raises issues about the epistemology of mathematics and the politics of knowledge, analogous with current discussions on multilingualism in mathematics education and in ethnomathematics. The paper concludes that mathematics educators can explore and take advantage of the sociolinguistic and epistemological issues that arise when an indigenous language is elaborated in a short period of time in comparison to other languages which have been developed incrementally over hundreds of years and thus much more difficult to critique.

ERT to aid in WSN based early warning system for landslides

NASA Astrophysics Data System (ADS)

T, H.

2017-12-01

Amrita University's landslide monitoring and early warning system using Wireless Sensor Networks (WSN) consists of heterogeneous sensors like rain gauge, moisture sensor, piezometer, geophone, inclinometer, tilt meter etc. The information from the sensors are accurate and limited to that point. In order to monitor a large area, ERT can be used in conjunction with WSN technology. To accomplish the feasibility of ERT in landslide early warning along with WSN technology, we have conducted experiments in Amrita's landslide laboratory setup. The experiment was aimed to simulate landslide, and monitor the changes happening in the soil using moisture sensor and ERT. Simulating moisture values from resistivity measurements to a greater accuracy can help in landslide monitoring for large areas. For accomplishing the same we have adapted two mathematical approaches, 1) Regression analysis between resistivity measurements and actual moisture values from moisture sensor, and 2) Using Waxman Smith model to simulate moisture values from resistivity measurements. The simulated moisture values from Waxman Smith model is compared with the actual moisture values and the Mean Square Error (MSE) is found to be 46.33. Regression curve is drawn for the resistivity vs simulated moisture values from Waxman model, and it is compared with the regression curve of actual model, which is shown in figure-1. From figure-1, it is clear that there the regression curve from actual moisture values and the regression curve from simulated moisture values, follow the similar pattern and there is a small difference between them. Moisture values can be simulated to a greater accuracy using actual regression equation, but the limitation is that, regression curves will differ for different sites and different soils. Regression equation from actual moisture values can be used, if we have conducted experiment in the laboratory for a particular soil sample, otherwise with the knowledge of soil properties, Waxman model can be used to simulate moisture values. The promising results assure that, ERT measurements when used in conjunction with WSN technique, vital paramters triggering landslides like moisture can be simulated for a large area, which will help in providing early warning for large areas.

Safety evaluation model of urban cross-river tunnel based on driving simulation.

PubMed

Ma, Yingqi; Lu, Linjun; Lu, Jian John

2017-09-01

Currently, Shanghai urban cross-river tunnels have three principal characteristics: increased traffic, a high accident rate and rapidly developing construction. Because of their complex geographic and hydrological characteristics, the alignment conditions in urban cross-river tunnels are more complicated than in highway tunnels, so a safety evaluation of urban cross-river tunnels is necessary to suggest follow-up construction and changes in operational management. A driving risk index (DRI) for urban cross-river tunnels was proposed in this study. An index system was also constructed, combining eight factors derived from the output of a driving simulator regarding three aspects of risk due to following, lateral accidents and driver workload. Analytic hierarchy process methods and expert marking and normalization processing were applied to construct a mathematical model for the DRI. The driving simulator was used to simulate 12 Shanghai urban cross-river tunnels and a relationship was obtained between the DRI for the tunnels and the corresponding accident rate (AR) via a regression analysis. The regression analysis results showed that the relationship between the DRI and the AR mapped to an exponential function with a high degree of fit. In the absence of detailed accident data, a safety evaluation model based on factors derived from a driving simulation can effectively assess the driving risk in urban cross-river tunnels constructed or in design.

A regression analysis of filler particle content to predict composite wear.

PubMed

Jaarda, M J; Wang, R F; Lang, B R

1997-01-01

It has been hypothesized that composite wear is correlated to filler particle content. There is a paucity of research to substantiate this theory despite numerous projects evaluating the correlation. The purpose of this study was to determine whether a linear relationship existed between composite wear and filler particle content of 12 composites. In vivo wear data had been previously collected for the 12 composites and served as basis for this study. Scanning electron microscopy and backscatter electron imaging were combined with digital imaging analysis to develop "profile maps" of the filler particle composition of the composites. These profile maps included eight parameters: (1) total number of filler particles/28742.6 microns2, (2) percent of area occupied by all of the filler particles, (3) mean filler particle size, (4) percent of area occupied by the matrix, (5) percent of area occupied by filler particles, r (radius) 1.0 < or = micron, (6) percent of area occupied by filler particles, r = 1.0 < or = 4.5 microns, (7) percent of area occupied by filler particles, r = 4.5 < or = 10 microns, and (8) percent of area occupied by filler particles, r > 10 microns. Forward stepwise regression analyses were used with composite wear as the dependent variable and the eight parameters as independent variables. The results revealed a linear relationship between composite wear and the filler particle content. A mathematical formula was developed to predict composite wear.

Error analysis of mathematical problems on TIMSS: A case of Indonesian secondary students

NASA Astrophysics Data System (ADS)

Priyani, H. A.; Ekawati, R.

2018-01-01

Indonesian students’ competence in solving mathematical problems is still considered as weak. It was pointed out by the results of international assessment such as TIMSS. This might be caused by various types of errors made. Hence, this study aimed at identifying students’ errors in solving mathematical problems in TIMSS in the topic of numbers that considered as the fundamental concept in Mathematics. This study applied descriptive qualitative analysis. The subject was three students with most errors in the test indicators who were taken from 34 students of 8th graders. Data was obtained through paper and pencil test and student’s’ interview. The error analysis indicated that in solving Applying level problem, the type of error that students made was operational errors. In addition, for reasoning level problem, there are three types of errors made such as conceptual errors, operational errors and principal errors. Meanwhile, analysis of the causes of students’ errors showed that students did not comprehend the mathematical problems given.

Insights into Fourier Synthesis and Analysis: Part 2--A Simplified Mathematics.

ERIC Educational Resources Information Center

Moore, Guy S. M.

1988-01-01

Introduced is an analysis of a waveform into its Fourier components. Topics included are simplified analysis of a square waveform, a triangular waveform, half-wave rectified alternating current (AC), and impulses. Provides the mathematical expression and simplified analysis diagram of each waveform. (YP)

Communication and Academic Vocabulary in Mathematics: A Content Analysis of Prompts Eliciting Written Responses in Two Elementary Mathematics Textbooks

ERIC Educational Resources Information Center

Joseph, Christine M.

2012-01-01

The purpose of this study was to investigate how writing in mathematics is treated in one 4th grade National Science Foundation (NSF)-funded mathematics textbook titled "Everyday Mathematics" and one publisher-generated textbook titled "enVision MATH." The developed framework provided categories to support each of the research…

The Effect of Teacher Education Programs on Future Elementary Mathematics Teachers' Knowledge: A Five-Country Analysis Using TEDS-M Data

ERIC Educational Resources Information Center

Qian, Hong; Youngs, Peter

2016-01-01

This article addresses the problem of how opportunities to learn in teacher education programs influence future elementary mathematics teachers' knowledge. This study used data collected for the Teacher Education and Development Study in Mathematics (TEDS-M). TEDS-M measured the mathematics content knowledge (MCK) and the mathematics pedagogical…

Effects of Secondary School Students' Perceptions of Mathematics Education Quality on Mathematics Anxiety and Achievement

ERIC Educational Resources Information Center

Çiftçi, S. Koza

2015-01-01

The two aims of this study are as follows: (1) to compare the differences in mathematics anxiety and achievement in secondary school students according to their perceptions of the quality of their mathematics education via a cluster analysis and (2) to test the effects of the perception of mathematics education quality on anxiety and achievement…

Visual working memory and number sense: Testing the double deficit hypothesis in mathematics.

PubMed

Toll, Sylke W M; Kroesbergen, Evelyn H; Van Luit, Johannes E H

2016-09-01

Evidence exists that there are two main underlying cognitive factors in mathematical difficulties: working memory and number sense. It is suggested that real math difficulties appear when both working memory and number sense are weak, here referred to as the double deficit (DD) hypothesis. The aim of this study was to test the DD hypothesis within a longitudinal time span of 2 years. A total of 670 children participated. The mean age was 4.96 years at the start of the study and 7.02 years at the end of the study. At the end of the first year of kindergarten, both visual-spatial working memory and number sense were measured by two different tasks. At the end of first grade, mathematical performance was measured with two tasks, one for math facts and one for math problems. Multiple regressions revealed that both visual working memory and symbolic number sense are predictors of mathematical performance in first grade. Symbolic number sense appears to be the strongest predictor for both math areas (math facts and math problems). Non-symbolic number sense only predicts performance in math problems. Multivariate analyses of variance showed that a combination of visual working memory and number sense deficits (NSDs) leads to the lowest performance on mathematics. Our DD hypothesis was confirmed. Both visual working memory and symbolic number sense in kindergarten are related to mathematical performance 2 years later, and a combination of visual working memory and NSDs leads to low performance in mathematical performance. © 2016 The British Psychological Society.

An Intersectional Analysis of Latin@ College Women's Counter-Stories in Mathematics

ERIC Educational Resources Information Center

Leyva, Luis A.

2016-01-01

In this article, the author discusses the intersectionality of mathematics experiences for two Latin@ college women pursuing mathematics-intensive STEM (science, technology, engineering, and mathematics) majors at a large, predominantly White university. The author employs intersectionality and poststructural theories to explore and make meaning…

Mathematics Coursework Regulates Growth in Mathematics Achievement

ERIC Educational Resources Information Center

Ma, Xin; Wilkins, Jesse L. M.

2007-01-01

Using data from the Longitudinal Study of American Youth (LSAY), we examined the extent to which students' mathematics coursework regulates (influences) the rate of growth in mathematics achievement during middle and high school. Graphical analysis showed that students who started middle school with higher achievement took individual mathematics…

Teachers' Perception of Social Justice in Mathematics Classrooms

ERIC Educational Resources Information Center

Panthi, Ram Krishna; Luitel, Bal Chandra; Belbase, Shashidhar

2017-01-01

The purpose of this study was to explore mathematics teachers' perception of social justice in mathematics classrooms. We applied interpretive qualitative method for data collection, analysis, and interpretation through iterative process. We administered in-depth semi-structured interviews to capture the perceptions of three mathematics teachers…

Mathematical Identity for a Sustainable Future: An Interpretative Phenomenological Analysis

ERIC Educational Resources Information Center

Pipere, Anita; Micule, Ilona

2014-01-01

Individual in-depth, semi-structured interviews with three mathematics teachers were conducted to investigate the dynamics of their life-long relationships with mathematics, synthesised as mathematical identity from different identity positions in the context of dialogical self. The qualitative data were scrutinised employing interpretive…

Teachers' Perception of Social Justice in Mathematics Classrooms

ERIC Educational Resources Information Center

Panthi, Ram Krishna; Luitel, Bal Chandra; Belbase, Shashidhar

2018-01-01

The purpose of this study was to explore mathematics teachers' perception of social justice in mathematics classrooms. We applied interpretive qualitative method for data collection, analysis, and interpretation through iterative process. We administered in-depth semi-structured interviews to capture the perceptions of three mathematics teachers…

Modern Versus Traditional Mathematics

ERIC Educational Resources Information Center

Roberts, A. M.

1974-01-01

The effect of different secondary school mathematics syllabi on first-year performance in college-level mathematics was studied in an attempt to evaluate the syllabus change. Students with a modern mathematics background performed sigficantly better on most first-year units. A topic-by-topic analysis of results is included. (DT)

Some aspects of mathematical and chemical modeling of complex chemical processes

NASA Technical Reports Server (NTRS)

Nemes, I.; Botar, L.; Danoczy, E.; Vidoczy, T.; Gal, D.

1983-01-01

Some theoretical questions involved in the mathematical modeling of the kinetics of complex chemical process are discussed. The analysis is carried out for the homogeneous oxidation of ethylbenzene in the liquid phase. Particular attention is given to the determination of the general characteristics of chemical systems from an analysis of mathematical models developed on the basis of linear algebra.

Mathematics Education Research in Turkey: A Content Analysis Study

ERIC Educational Resources Information Center

Ciltas, Alper; Guler, Gursel; Sozbilir, Mustafa

2012-01-01

In this study, a content analysis of research is aimed in the field of mathematics education of Turkish researchers. To this aim, the investigation of 359 article were made which were accessed from web in full text between 1987 and 2009 years and which were published in the field of mathematics education from 32 different journals. 27 of these…

The Effect of Syllabus on Mathematical Knowledge

ERIC Educational Resources Information Center

Belsom, C. G. H.; Elton, L. R. B.

1974-01-01

Item analysis of a mathematics preknowledge test given to physics students revealed that significant differences existed on certain items between groups of students who had followed different mathematics syllabuses. (MLH)

The relationship between learning mathematics and general cognitive ability in primary school.

PubMed

Cowan, Richard; Hurry, Jane; Midouhas, Emily

2018-06-01

Three relationships between learning mathematics and general cognitive ability have been hypothesized: The educational hypothesis that learning mathematics develops general cognitive skills, the psychometric hypothesis that differences in general cognitive ability cause differences in mathematical attainment, and the reciprocal influence hypothesis that developments in mathematical ability and general cognitive ability influence each other. These hypotheses are assessed with a sample of 948 children from the Twins Early Development Study who were assessed at 7, 9, and 10 years on mathematics, English, and general cognitive ability. A cross-lagged path analysis with mathematics and general cognitive ability measures supports the reciprocal influence hypothesis between 7 and 9 and between 9 and 10. A second analysis including English assessments only provides evidence of a reciprocal relationship between 7 and 9. Statement of Contribution What is already known on this subject? The correlations between mathematical attainment, literacy, and measures of general cognitive skills are well established. The role of literacy in developing general cognitive skills is emerging. What the present study adds? Mathematics contributes to the development of general cognitive skills. General cognitive ability contributes to mathematical development between 7 and 10. These findings support the hypothesis of reciprocal influence between mathematics and general cognitive ability, at least between 7 and 9. © 2017 The British Psychological Society.

Mathematical and information maintenance of biometric systems

NASA Astrophysics Data System (ADS)

Boriev, Z.; Sokolov, S.; Nyrkov, A.; Nekrasova, A.

2016-04-01

This article describes the different mathematical methods for processing biometric data. A brief overview of methods for personality recognition by means of a signature is conducted. Mathematical solutions of a dynamic authentication method are considered. Recommendations on use of certain mathematical methods, depending on specific tasks, are provided. Based on the conducted analysis of software and the choice made in favor of the wavelet analysis, a brief basis for its use in the course of software development for biometric personal identification is given for the purpose of its practical application.

Prostate Cancer Predictive Simulation Modelling, Assessing the Risk Technique (PCP-SMART): Introduction and Initial Clinical Efficacy Evaluation Data Presentation of a Simple Novel Mathematical Simulation Modelling Method, Devised to Predict the Outcome of Prostate Biopsy on an Individual Basis.

PubMed

Spyropoulos, Evangelos; Kotsiris, Dimitrios; Spyropoulos, Katherine; Panagopoulos, Aggelos; Galanakis, Ioannis; Mavrikos, Stamatios

2017-02-01

We developed a mathematical "prostate cancer (PCa) conditions simulating" predictive model (PCP-SMART), from which we derived a novel PCa predictor (prostate cancer risk determinator [PCRD] index) and a PCa risk equation. We used these to estimate the probability of finding PCa on prostate biopsy, on an individual basis. A total of 371 men who had undergone transrectal ultrasound-guided prostate biopsy were enrolled in the present study. Given that PCa risk relates to the total prostate-specific antigen (tPSA) level, age, prostate volume, free PSA (fPSA), fPSA/tPSA ratio, and PSA density and that tPSA ≥ 50 ng/mL has a 98.5% positive predictive value for a PCa diagnosis, we hypothesized that correlating 2 variables composed of 3 ratios (1, tPSA/age; 2, tPSA/prostate volume; and 3, fPSA/tPSA; 1 variable including the patient's tPSA and the other, a tPSA value of 50 ng/mL) could operate as a PCa conditions imitating/simulating model. Linear regression analysis was used to derive the coefficient of determination (R 2 ), termed the PCRD index. To estimate the PCRD index's predictive validity, we used the χ 2 test, multiple logistic regression analysis with PCa risk equation formation, calculation of test performance characteristics, and area under the receiver operating characteristic curve analysis using SPSS, version 22 (P < .05). The biopsy findings were positive for PCa in 167 patients (45.1%) and negative in 164 (44.2%). The PCRD index was positively signed in 89.82% positive PCa cases and negative in 91.46% negative PCa cases (χ 2 test; P < .001; relative risk, 8.98). The sensitivity was 89.8%, specificity was 91.5%, positive predictive value was 91.5%, negative predictive value was 89.8%, positive likelihood ratio was 10.5, negative likelihood ratio was 0.11, and accuracy was 90.6%. Multiple logistic regression revealed the PCRD index as an independent PCa predictor, and the formulated risk equation was 91% accurate in predicting the probability of finding PCa. On the receiver operating characteristic analysis, the PCRD index (area under the curve, 0.926) significantly (P < .001) outperformed other, established PCa predictors. The PCRD index effectively predicted the prostate biopsy outcome, correctly identifying 9 of 10 men who were eventually diagnosed with PCa and correctly ruling out PCa for 9 of 10 men who did not have PCa. Its predictive power significantly outperformed established PCa predictors, and the formulated risk equation accurately calculated the probability of finding cancer on biopsy, on an individual patient basis. Copyright © 2016 Elsevier Inc. All rights reserved.

Mathematical and Numerical Analysis of Model Equations on Interactions of the HIV/AIDS Virus and the Immune System

NASA Astrophysics Data System (ADS)

Parumasur, N.; Willie, R.

2008-09-01

We consider a simple HIV/AIDs finite dimensional mathematical model on interactions of the blood cells, the HIV/AIDs virus and the immune system for consistence of the equations to the real biomedical situation that they model. A better understanding to a cure solution to the illness modeled by the finite dimensional equations is given. This is accomplished through rigorous mathematical analysis and is reinforced by numerical analysis of models developed for real life cases.

The Integration of Science and Mathematics Education: Highlights from the NSF/SSMA Wingspread Conference Plenary Papers.

ERIC Educational Resources Information Center

Berlin, Donna F.

1994-01-01

Summarizes plenary papers presented at the NSF/SSMA Wingspread Conference to explore ways to improve science and mathematics education through integration. Themes included analysis of integration; divergence of mathematics education from science education; technological perspectives; promoting mathematical and scientific inquiry; and school…

The Alchemy of Mathematical Experience: A Psychoanalysis of Student Writings.

ERIC Educational Resources Information Center

Early, Robert E.

1992-01-01

Shares a psychological look at student images of mathematical learning and problem solving through students' writings about mathematical experiences. The analysis is done from a Jungian psychoanalytic orientation with the goal of assisting students develop a deeper perspective from which to view their mathematics experience. (MDH)

Kindergarten Children's Interactions with Touchscreen Mathematics Virtual Manipulatives: An Innovative Mixed Methods Analysis

ERIC Educational Resources Information Center

Tucker, Stephen I.; Lommatsch, Christina W.; Moyer-Packenham, Patricia S.; Anderson-Pence, Katie L.; Symanzik, Jürgen

2017-01-01

The purpose of this study was to examine patterns of mathematical practices evident during children's interactions with touchscreen mathematics virtual manipulatives. Researchers analyzed 33 Kindergarten children's interactions during activities involving apps featuring mathematical content of early number sense or quantity in base ten, recorded…

Contrasting Knowledge for Elementary and Secondary Mathematics Teaching

ERIC Educational Resources Information Center

Rowland, Tim

2012-01-01

This paper describes and analyses two mathematics lessons, one with very young pupils, about subtraction, the other for lower secondary school pupils, about gradients [slopes] and graphs. The focus of the analysis is on teacher knowledge, and on the fundamental mathematical and mathematics-pedagogical prerequisites that underpin teaching these…

Cross-National Patterns of Gender Differences in Mathematics: A Meta-Analysis

ERIC Educational Resources Information Center

Else-Quest, Nicole M.; Hyde, Janet Shibley; Linn, Marcia C.

2010-01-01

A gender gap in mathematics achievement persists in some nations but not in others. In light of the underrepresentation of women in careers in science, technology, mathematics, and engineering, increasing research attention is being devoted to understanding gender differences in mathematics achievement, attitudes, and affect. The gender…

Prospective Secondary Mathematics Teachers' Reflections on Teaching after Their First Teaching Experience

ERIC Educational Resources Information Center

Yazgan-Sag, Gönül; Emre-Akdogan, Elçin; Argün, Ziya

2016-01-01

The aim of our study was to examine prospective secondary mathematics teachers' reflections about teaching after their first teaching experience. We carried out five interviews during the two semesters with four Turkish prospective secondary mathematics teachers. The data analysis suggests that prospective secondary mathematics teachers'…

Students attitude towards calculus subject: Bumiputera case-study

NASA Astrophysics Data System (ADS)

Awang, Noorehan; Ilias, Mohd Rijal; Che Hussain, Wan Siti Esah; Mokhtar, Siti Fairus

2013-04-01

Mathematics has always become the most dislike subject among other subjects in school. Study showed that attitudes of students in science subjects such as mathematics were closely related to how they solve problems, accessing ideas and making a right decision. According to another study on mathematics achievement of eighth grade students in Malaysia, mathematics grades among bumiputera students was lower when compared to other races such as Chinese and Indians. The poor performance was due to their attitude and pre-conceived ideas towards the subject. Therefore, this study was designed todetermine the criteria and subcriteria that were considered important in measuring students' attitude toward mathematics among the bumiputeras. Factor analysis was carried out to identify the groups among criterion. Instrument used to measure mathematics attitude was Test of Mathematics Related Attitude (TOMRA) which measured student attitudes in four criteria: normality of mathematics, attitudes towards mathematics inquiry, adoption of mathematics attitude and enjoyment of mathematics lessons. The target population of this study was all computer science and quantitative science students who enrolled Calculus subject in UiTM Kedah. Findings shows that there are two criteria that influenced students attitude toward mathematics namely normality of mathematics with eleven subcriteria and enjoyment of mathematics with eight subcriteria. From the analysis it shows that the total percentage of variation explained is 35.071% with 0.837 Cronbach's alpha reliability test. The findings will help the lecturers, parents and society to consider what action should be taken to install interest and positive attitude of bumiputera students towards mathematics and thus improve their achievement.

A Comparison of Mathematical Models of Fish Mercury Concentration as a Function of Atmospheric Mercury Deposition Rate and Watershed Characteristics

NASA Astrophysics Data System (ADS)

Smith, R. A.; Moore, R. B.; Shanley, J. B.; Miller, E. K.; Kamman, N. C.; Nacci, D.

2009-12-01

Mercury (Hg) concentrations in fish and aquatic wildlife are complex functions of atmospheric Hg deposition rate, terrestrial and aquatic watershed characteristics that influence Hg methylation and export, and food chain characteristics determining Hg bioaccumulation. Because of the complexity and incomplete understanding of these processes, regional-scale models of fish tissue Hg concentration are necessarily empirical in nature, typically constructed through regression analysis of fish tissue Hg concentration data from many sampling locations on a set of potential explanatory variables. Unless the data sets are unusually long and show clear time trends, the empirical basis for model building must be based solely on spatial correlation. Predictive regional scale models are highly useful for improving understanding of the relevant biogeochemical processes, as well as for practical fish and wildlife management and human health protection. Mechanistically, the logical arrangement of explanatory variables is to multiply each of the individual Hg source terms (e.g. dry, wet, and gaseous deposition rates, and residual watershed Hg) for a given fish sampling location by source-specific terms pertaining to methylation, watershed transport, and biological uptake for that location (e.g. SO4 availability, hill slope, lake size). This mathematical form has the desirable property that predicted tissue concentration will approach zero as all individual source terms approach zero. One complication with this form, however, is that it is inconsistent with the standard linear multiple regression equation in which all terms (including those for sources and physical conditions) are additive. An important practical disadvantage of a model in which the Hg source terms are additive (rather than multiplicative) with their modifying factors is that predicted concentration is not zero when all sources are zero, making it unreliable for predicting the effects of large future reductions in Hg deposition. In this paper we compare the results of using several different linear and non-linear models in an analysis of watershed and fish Hg data for 450 New England lakes. The differences in model results pertain to both their utility in interpreting methylation and export processes as well as in fisheries management.

Determination of physical height from crown dimensions of deciduous tooth: A dental morphometric study.

PubMed

Ramanna, C; Kamath, Venkatesh V; Sharada, C; Srikanth, N

2016-01-01

Dental morphometrics is a subject of great significance in forensic odontology in identification of an individual. Use of teeth to represent a physical profile is valuable for identification of an individual. The present study aims to assess the clinical crown length (CL) of erupted deciduous teeth and height of the child. A correlation of these parameters was attempted to arrive at a mathematical equation which would formulate a ratio of tooth CL to individual height that would support in estimating the probable height of the child. About 60 children (30 males and 30 females) of age ranged from 3-6 years were included in this study. Clinical vertical CLs of the deciduous dentition (tooth numbers 51, 52, 53, 54, and 55) were calculated using digital Vernier calipers (Aerospace Ltd., Bengaluru, Karnataka, India) on the cast models. Child height was measured using a standard measuring tape. Ratios of deciduous CL to height of the child were recorded. Linear stepwise forward regression analysis was applied to predict the probability of CL of a tooth most likely to support in prediction of physical height of the child. Tabulated results showed a probable correlation between tooth CL and height of the child. Tooth CLs of deciduous upper right second molar (55) among the males, lateral incisor (52) among females, and canine (53) using the combined male and female data were statistically significant, and they approximately predicted the child height with minimal variations. Mathematically derived equations based on linear stepwise forward regression analysis using sixty children data are height prediction (derived from combined data of male and female children) = 400.558 + 90.264 (53 CL), male child height prediction (derived from data of male children) = 660.290 + 72.970 (55 CL), and female child height prediction (derived from data of female children) = -187.942 + 194.818 (52 CL). In conclusion, clinical vertical CL is an important parameter in prediction of individual height and possible identification of the individual. An extension of the similar technique to all the deciduous dentition using a larger group of children would probably give us the best options available among vertical CLs for prediction of the child height.

Intensity level for exercise training in fibromyalgia by using mathematical models.

PubMed

Lemos, Maria Carolina D; Valim, Valéria; Zandonade, Eliana; Natour, Jamil

2010-03-22

It has not been assessed before whether mathematical models described in the literature for prescriptions of exercise can be used for fibromyalgia syndrome patients. The objective of this paper was to determine how age-predicted heart rate formulas can be used with fibromyalgia syndrome populations as well as to find out which mathematical models are more accurate to control exercise intensity. A total of 60 women aged 18-65 years with fibromyalgia syndrome were included; 32 were randomized to walking training at anaerobic threshold. Age-predicted formulas to maximum heart rate ("220 minus age" and "208 minus 0.7 x age") were correlated with achieved maximum heart rate (HRMax) obtained by spiroergometry. Subsequently, six mathematical models using heart rate reserve (HRR) and age-predicted HRMax formulas were studied to estimate the intensity level of exercise training corresponding to heart rate at anaerobic threshold (HRAT) obtained by spiroergometry. Linear and nonlinear regression models were used for correlations and residues analysis for the adequacy of the models. Age-predicted HRMax and HRAT formulas had a good correlation with achieved heart rate obtained in spiroergometry (r = 0.642; p < 0.05). For exercise prescription in the anaerobic threshold intensity, the percentages were 52.2-60.6% HRR and 75.5-80.9% HRMax. Formulas using HRR and the achieved HRMax showed better correlation. Furthermore, the percentages of HRMax and HRR were significantly higher for the trained individuals (p < 0.05). Age-predicted formulas can be used for estimating HRMax and for exercise prescriptions in women with fibromyalgia syndrome. Karnoven's formula using heart rate achieved in ergometric test showed a better correlation. For the prescription of exercises in the threshold intensity, 52% to 60% HRR or 75% to 80% HRMax must be used in sedentary women with fibromyalgia syndrome and these values are higher and must be corrected for trained patients.

Intensity level for exercise training in fibromyalgia by using mathematical models

PubMed Central

2010-01-01

Background It has not been assessed before whether mathematical models described in the literature for prescriptions of exercise can be used for fibromyalgia syndrome patients. The objective of this paper was to determine how age-predicted heart rate formulas can be used with fibromyalgia syndrome populations as well as to find out which mathematical models are more accurate to control exercise intensity. Methods A total of 60 women aged 18-65 years with fibromyalgia syndrome were included; 32 were randomized to walking training at anaerobic threshold. Age-predicted formulas to maximum heart rate ("220 minus age" and "208 minus 0.7 × age") were correlated with achieved maximum heart rate (HRMax) obtained by spiroergometry. Subsequently, six mathematical models using heart rate reserve (HRR) and age-predicted HRMax formulas were studied to estimate the intensity level of exercise training corresponding to heart rate at anaerobic threshold (HRAT) obtained by spiroergometry. Linear and nonlinear regression models were used for correlations and residues analysis for the adequacy of the models. Results Age-predicted HRMax and HRAT formulas had a good correlation with achieved heart rate obtained in spiroergometry (r = 0.642; p < 0.05). For exercise prescription in the anaerobic threshold intensity, the percentages were 52.2-60.6% HRR and 75.5-80.9% HRMax. Formulas using HRR and the achieved HRMax showed better correlation. Furthermore, the percentages of HRMax and HRR were significantly higher for the trained individuals (p < 0.05). Conclusion Age-predicted formulas can be used for estimating HRMax and for exercise prescriptions in women with fibromyalgia syndrome. Karnoven's formula using heart rate achieved in ergometric test showed a better correlation. For the prescription of exercises in the threshold intensity, 52% to 60% HRR or 75% to 80% HRMax must be used in sedentary women with fibromyalgia syndrome and these values are higher and must be corrected for trained patients. PMID:20307323

Performance of a recoverable tug for planetary missions including use of perigee propulsion and corrections for nodal regression

NASA Technical Reports Server (NTRS)

Borsody, J.

1976-01-01

Mathematical equations are derived by using the Maximum Principle to obtain the maximum payload capability of a reusable tug for planetary missions. The mathematical formulation includes correction for nodal precession of the space shuttle orbit. The tug performs this nodal correction in returning to this precessed orbit. The sample case analyzed represents an inner planet mission as defined by the declination (fixed) and right ascension of the outgoing asymptote and the mission energy. Payload capability is derived for a typical cryogenic tug and the sample case with and without perigee propulsion. Optimal trajectory profiles and some important orbital elements are also discussed.

An Analysis of Final Course Grades in Two Different Entry Level Mathematics Courses between and among First Year College Students with Different Levels of High School Mathematics Preparation

ERIC Educational Resources Information Center

Muir, Carrie

2012-01-01

The purpose of this study was to compare the performance of first year college students with similar high school mathematics backgrounds in two introductory level college mathematics courses, "Fundamentals and Techniques of College Algebra and Quantitative Reasoning and Mathematical Skills," and to compare the performance of students…

Universal Beliefs and Specific Practices: Students' Math Self-Efficacy and Related Factors in the United States and China

ERIC Educational Resources Information Center

Wu, Yin

2016-01-01

This study intends to compare and contrast student and school factors that are associated with students' mathematics self-efficacy in the United States and China. Using hierarchical linear regressions to analyze the Programme for International Student Assessment (PISA) 2012 data, this study compares math self-efficacy, achievement, and variables…

The Impact of Selected Academic and Demographic Variables on Mathematics College Readiness Predicted by ACT

ERIC Educational Resources Information Center

Smith, Marcia

2013-01-01

The purpose of the study was to determine the degree to which academic and demographic variables affected the ACT results used in determining college readiness. This quantitative research study followed a non-experimental correlational design. A multiple regression was used to analyze archival data to determine the impact the combined Arkansas…

Is It the Intervention or the Students? Using Linear Regression to Control for Student Characteristics in Undergraduate STEM Education Research

ERIC Educational Resources Information Center

Theobald, Roddy; Freeman, Scott

2014-01-01

Although researchers in undergraduate science, technology, engineering, and mathematics education are currently using several methods to analyze learning gains from pre- and posttest data, the most commonly used approaches have significant shortcomings. Chief among these is the inability to distinguish whether differences in learning gains are due…

Examining the Variability of Mathematics Performance and Its Correlates Using Data from TIMSS '95 and TIMSS '99

ERIC Educational Resources Information Center

O'Dwyer, Laura M.

2005-01-01

International studies in education provide researchers with opportunities to examine how students with both similar and dissimilar formal education systems perform on a single test and provide rich information about the relationships among student outcomes and the factors that affect them. Using hierarchical linear regression techniques and TIMSS…

Neural network modeling for surgical decisions on traumatic brain injury patients.

PubMed

Li, Y C; Liu, L; Chiu, W T; Jian, W S

2000-01-01

Computerized medical decision support systems have been a major research topic in recent years. Intelligent computer programs were implemented to aid physicians and other medical professionals in making difficult medical decisions. This report compares three different mathematical models for building a traumatic brain injury (TBI) medical decision support system (MDSS). These models were developed based on a large TBI patient database. This MDSS accepts a set of patient data such as the types of skull fracture, Glasgow Coma Scale (GCS), episode of convulsion and return the chance that a neurosurgeon would recommend an open-skull surgery for this patient. The three mathematical models described in this report including a logistic regression model, a multi-layer perceptron (MLP) neural network and a radial-basis-function (RBF) neural network. From the 12,640 patients selected from the database. A randomly drawn 9480 cases were used as the training group to develop/train our models. The other 3160 cases were in the validation group which we used to evaluate the performance of these models. We used sensitivity, specificity, areas under receiver-operating characteristics (ROC) curve and calibration curves as the indicator of how accurate these models are in predicting a neurosurgeon's decision on open-skull surgery. The results showed that, assuming equal importance of sensitivity and specificity, the logistic regression model had a (sensitivity, specificity) of (73%, 68%), compared to (80%, 80%) from the RBF model and (88%, 80%) from the MLP model. The resultant areas under ROC curve for logistic regression, RBF and MLP neural networks are 0.761, 0.880 and 0.897, respectively (P < 0.05). Among these models, the logistic regression has noticeably poorer calibration. This study demonstrated the feasibility of applying neural networks as the mechanism for TBI decision support systems based on clinical databases. The results also suggest that neural networks may be a better solution for complex, non-linear medical decision support systems than conventional statistical techniques such as logistic regression.

Perceptions of Support, Induction, and Intentions by Secondary Science and Mathematics Teachers on Job Retention

NASA Astrophysics Data System (ADS)

Bond, Sharon C.

This study was designed to examine the teacher characteristics, workplace factors, and type of induction supports that contribute to the retention of secondary science and mathematics teachers. Using the sample of secondary science and mathematics teachers extracted from the National Center for Educational Statistics (NCES) 2007--2008 Schools and Staffing Survey (SASS), research was conducted to analyze teachers' responses relative to induction and support by looking at what teachers valued, what they actually received, and what impacted their decision to remain in the teaching profession. In addition to predisposing characteristics that have been shown to influence retention, the research conceptualized the type of induction to include mentoring, professional development, and administrative supports, and employed logistic regression to estimate the individual and collective effects of these factors on teachers' decisions to stay in the profession. Consistent with many areas of education, the fields of science and mathematics in North Carolina remain predominantly White (81%) with Blacks holding 14%, while Asians and Native Americans represent less than 5%. The examination of the Schools and Staffing Survey 2007--2008 showed that the primary supports received by beginning teachers were seminars or classes, common planning, mentoring, and communication with principals. Controlling for certain teacher characteristics, research indicated that science and mathematics teachers in North Carolina rated positively many variables related to support, climate, and classroom practices. Primarily, secondary science and mathematics teachers indicated satisfaction in the areas of mentoring, working conditions, and administrative support, and remained in teaching.

Clinical and Cognitive Characteristics Associated with Mathematics Problem Solving in Adolescents with Autism Spectrum Disorder.

PubMed

Oswald, Tasha M; Beck, Jonathan S; Iosif, Ana-Maria; McCauley, James B; Gilhooly, Leslie J; Matter, John C; Solomon, Marjorie

2016-04-01

Mathematics achievement in autism spectrum disorder (ASD) has been understudied. However, the ability to solve applied math problems is associated with academic achievement, everyday problem-solving abilities, and vocational outcomes. The paucity of research on math achievement in ASD may be partly explained by the widely-held belief that most individuals with ASD are mathematically gifted, despite emerging evidence to the contrary. The purpose of the study was twofold: to assess the relative proportions of youth with ASD who demonstrate giftedness versus disability on applied math problems, and to examine which cognitive (i.e., perceptual reasoning, verbal ability, working memory) and clinical (i.e., test anxiety) characteristics best predict achievement on applied math problems in ASD relative to typically developing peers. Twenty-seven high-functioning adolescents with ASD and 27 age- and Full Scale IQ-matched typically developing controls were assessed on standardized measures of math problem solving, perceptual reasoning, verbal ability, and test anxiety. Results indicated that 22% of the ASD sample evidenced a mathematics learning disability, while only 4% exhibited mathematical giftedness. The parsimonious linear regression model revealed that the strongest predictor of math problem solving was perceptual reasoning, followed by verbal ability and test anxiety, then diagnosis of ASD. These results inform our theories of math ability in ASD and highlight possible targets of intervention for students with ASD struggling with mathematics. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Reduction of shock induced noise in imperfectly expanded supersonic jets using convex optimization

NASA Astrophysics Data System (ADS)

Adhikari, Sam

2007-11-01

Imperfectly expanded jets generate screech noise. The imbalance between the backpressure and the exit pressure of the imperfectly expanded jets produce shock cells and expansion or compression waves from the nozzle. The instability waves and the shock cells interact to generate the screech sound. The mathematical model consists of cylindrical coordinate based full Navier-Stokes equations and large-eddy-simulation turbulence modeling. Analytical and computational analysis of the three-dimensional helical effects provide a model that relates several parameters with shock cell patterns, screech frequency and distribution of shock generation locations. Convex optimization techniques minimize the shock cell patterns and the instability waves. The objective functions are (convex) quadratic and the constraint functions are affine. In the quadratic optimization programs, minimization of the quadratic functions over a set of polyhedrons provides the optimal result. Various industry standard methods like regression analysis, distance between polyhedra, bounding variance, Markowitz optimization, and second order cone programming is used for Quadratic Optimization.

A non-linear data mining parameter selection algorithm for continuous variables

PubMed Central

Razavi, Marianne; Brady, Sean

2017-01-01

In this article, we propose a new data mining algorithm, by which one can both capture the non-linearity in data and also find the best subset model. To produce an enhanced subset of the original variables, a preferred selection method should have the potential of adding a supplementary level of regression analysis that would capture complex relationships in the data via mathematical transformation of the predictors and exploration of synergistic effects of combined variables. The method that we present here has the potential to produce an optimal subset of variables, rendering the overall process of model selection more efficient. This algorithm introduces interpretable parameters by transforming the original inputs and also a faithful fit to the data. The core objective of this paper is to introduce a new estimation technique for the classical least square regression framework. This new automatic variable transformation and model selection method could offer an optimal and stable model that minimizes the mean square error and variability, while combining all possible subset selection methodology with the inclusion variable transformations and interactions. Moreover, this method controls multicollinearity, leading to an optimal set of explanatory variables. PMID:29131829

Empirical and semi-analytical models for predicting peak outflows caused by embankment dam failures

NASA Astrophysics Data System (ADS)

Wang, Bo; Chen, Yunliang; Wu, Chao; Peng, Yong; Song, Jiajun; Liu, Wenjun; Liu, Xin

2018-07-01

Prediction of peak discharge of floods has attracted great attention for researchers and engineers. In present study, nine typical nonlinear mathematical models are established based on database of 40 historical dam failures. The first eight models that were developed with a series of regression analyses are purely empirical, while the last one is a semi-analytical approach that was derived from an analytical solution of dam-break floods in a trapezoidal channel. Water depth above breach invert (Hw), volume of water stored above breach invert (Vw), embankment length (El), and average embankment width (Ew) are used as independent variables to develop empirical formulas of estimating the peak outflow from breached embankment dams. It is indicated from the multiple regression analysis that a function using the former two variables (i.e., Hw and Vw) produce considerably more accurate results than that using latter two variables (i.e., El and Ew). It is shown that the semi-analytical approach works best in terms of both prediction accuracy and uncertainty, and the established empirical models produce considerably reasonable results except the model only using El. Moreover, present models have been compared with other models available in literature for estimating peak discharge.

Mathematical Models for Doppler Measurements

NASA Technical Reports Server (NTRS)

Lear, William M.

1987-01-01

Error analysis increases precision of navigation. Report presents improved mathematical models of analysis of Doppler measurements and measurement errors of spacecraft navigation. To take advantage of potential navigational accuracy of Doppler measurements, precise equations relate measured cycle count to position and velocity. Drifts and random variations in transmitter and receiver oscillator frequencies taken into account. Mathematical models also adapted to aircraft navigation, radar, sonar, lidar, and interferometry.

Year 12 Students' Mathematical Performance on the 1980 and 1981 External Examinations. Mathematics Education Centre Report No. 25.

ERIC Educational Resources Information Center

Clarkson, P. C.

Descriptions of Papua New Guinea's national high schools, grade 12 major/minor mathematics courses, and an analysis of the 1980 and 1981 major/minor course examination results are presented. The analysis is intended for use by post year 12 lecturers/instructors planning their courses. Findings indicate that topic scores were far too low for these…

Mathematics Low Achievement in Greece: A Multilevel Analysis of the Programme for International Student Assessment (PISA) 2012 Data

ERIC Educational Resources Information Center

Karakolidis, Anastasios; Pitsia, Vasiliki; Emvalotis, Anastassios

2016-01-01

The main aim of the present study was to carry out an in-depth examination of mathematics underperformance in Greece. By applying a binary multilevel model to the PISA 2012 data, this study investigated the factors which were linked to low achievement in mathematics. The multilevel analysis revealed that students' gender, immigration status,…

77 FR 69541 - Technical Report Evaluating the Effectiveness of Tire Pressure Monitoring Systems (TPMS) in...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-19

... personal information provided. FOR FURTHER INFORMATION CONTACT: Bob Sivinski, Mathematical Statistician, Mathematical Analysis Division, NVS-421, National Center for Statistics and Analysis, National Highway Traffic...

Robert Leland - Associate Lab Director, Scientific Computing and Energy

Science.gov Websites

, applied mathematics, visualization, data, and analysis of energy systems, technologies, policies and Energy Analysis directorate. Leland earned his Ph.D. in mathematics from Oxford University in 1989

Judging complex movement performances for excellence: a principal components analysis-based technique applied to competitive diving.

PubMed

Young, Cole; Reinkensmeyer, David J

2014-08-01

Athletes rely on subjective assessment of complex movements from coaches and judges to improve their motor skills. In some sports, such as diving, snowboard half pipe, gymnastics, and figure skating, subjective scoring forms the basis for competition. It is currently unclear whether this scoring process can be mathematically modeled; doing so could provide insight into what motor skill is. Principal components analysis has been proposed as a motion analysis method for identifying fundamental units of coordination. We used PCA to analyze movement quality of dives taken from USA Diving's 2009 World Team Selection Camp, first identifying eigenpostures associated with dives, and then using the eigenpostures and their temporal weighting coefficients, as well as elements commonly assumed to affect scoring - gross body path, splash area, and board tip motion - to identify eigendives. Within this eigendive space we predicted actual judges' scores using linear regression. This technique rated dives with accuracy comparable to the human judges. The temporal weighting of the eigenpostures, body center path, splash area, and board tip motion affected the score, but not the eigenpostures themselves. These results illustrate that (1) subjective scoring in a competitive diving event can be mathematically modeled; (2) the elements commonly assumed to affect dive scoring actually do affect scoring (3) skill in elite diving is more associated with the gross body path and the effect of the movement on the board and water than the units of coordination that PCA extracts, which might reflect the high level of technique these divers had achieved. We also illustrate how eigendives can be used to produce dive animations that an observer can distort continuously from poor to excellent, which is a novel approach to performance visualization. Copyright © 2014 Elsevier B.V. All rights reserved.

DIVERGT screening procedure predicts general cognitive functioning in adult long-term survivors of pediatric acute lymphoblastic leukemia: A PETALE study.

PubMed

Boulet-Craig, Aubree; Robaey, Philippe; Laniel, Julie; Bertout, Laurence; Drouin, Simon; Krajinovic, Maja; Laverdière, Caroline; Sinnett, Daniel; Sultan, Serge; Lippé, Sarah

2018-05-24

Acute lymphoblastic leukemia (ALL) is the most common cancer in children. Because of major improvements in treatment protocols, the survival rate now exceeds 80%. However, ALL treatments can cause long-term neurocognitive sequelae, which negatively impact academic achievement and quality of life. Therefore, cognitive sequelae need to be carefully evaluated. The DIVERGT is a battery of tests proposed as a screening tool, sensitive to executive function impairments in children and adolescent cancer survivors. Our study aimed at verifying the predictive value of the DIVERGT on general cognitive functioning in adult long-term survivors of ALL. ALL survivors completed the DIVERGT 13.4 years, on average, after remission (N = 247). In addition, 49 of these survivors (equally selected amongst those with low, average, and high DIVERGT scores) as well as 29 controls completed a more comprehensive neuropsychological evaluation within a 3-year period from DIVERGT administration. Multivariate regression analysis was used to assess the predictive value of the DIVERGT on general intelligence, mathematics, verbal memory, and working memory. As a follow-up analysis, three performance groups were created based on the DIVERGT results. Multivariate analysis of variance (MANOVA) assessed neuropsychological differences between groups. The DIVERGT accurately predicted General Ability Index (GAI) (P < 0.0001), mathematics (P < 0.0001) and verbal memory (P = 0.045). Moreover, the low-performance group consistently had poorer performance than the high-performance and control groups on the neuropsychological tests. The DIVERGT is a useful, time-effective screening battery for broader neurocognitive impairments identification in long-term adult ALL survivors. It could be implemented as routine examination in cancer follow-up clinics. © 2018 Wiley Periodicals, Inc.

Development of Contextual Mathematics teaching Material integrated related sciences and realistic for students grade xi senior high school

NASA Astrophysics Data System (ADS)

Helma, H.; Mirna, M.; Edizon, E.

2018-04-01

Mathematics is often applied in physics, chemistry, economics, engineering, and others. Besides that, mathematics is also used in everyday life. Learning mathematics in school should be associated with other sciences and everyday life. In this way, the learning of mathematics is more realstic, interesting, and meaningful. Needs analysis shows that required contextual mathematics teaching materials integrated related sciences and realistic on learning mathematics. The purpose of research is to produce a valid and practical contextual mathematics teaching material integrated related sciences and realistic. This research is development research. The result of this research is a valid and practical contextual mathematics teaching material integrated related sciences and realistic produced

Intersectional Analysis in Critical Mathematics Education Research: A Response to Figure Hiding

ERIC Educational Resources Information Center

Bullock, Erika C.

2018-01-01

In this chapter, I use figure hiding as a metaphor representing the processes of exclusion and suppression that critical mathematics education (CME) seeks to address. Figure hiding renders identities and modes of thought in mathematics education and mathematics education research invisible. CME has a commitment to addressing figure hiding by…

Connections between Secondary Mathematics Teachers' Beliefs and Their Selection of Tasks for English Language Learners

ERIC Educational Resources Information Center

de Araujo, Zandra

2017-01-01

The tasks teachers select impact students' opportunities to learn mathematics and teachers' beliefs influence their choice of tasks. Through the qualitative analysis of surveys, interviews and classroom artefacts from three secondary mathematics teachers, this study examined teachers' selection of mathematics tasks for English language learners…

Problem Solving in Swedish Mathematics Textbooks for Upper Secondary School

ERIC Educational Resources Information Center

Brehmer, Daniel; Ryve, Andreas; Van Steenbrugge, Hendrik

2016-01-01

The aim of this study is to analyse how mathematical problem solving is represented in mathematical textbooks for Swedish upper secondary school. The analysis comprises dominating Swedish textbook series, and relates to uncovering (a) the quantity of tasks that are actually mathematical problems, (b) their location in the chapter, (c) their…

The Role of Ethnomathematics in Curricular Leadership in Mathematics Education

ERIC Educational Resources Information Center

D'Ambrosio, Ubiratan; D'Ambrosio, Beatriz Silva

2013-01-01

In this paper we share our reflections regarding the role of ethnomathematics in providing direction for leadership in mathematics education. Our arguments are grounded in an analysis of the world today, characterized by inequities and injustices, clamoring for a new social order. We contemplate the role of mathematics and mathematics education in…

An Analysis of Instruments that Measure the Quality of Mathematics Teaching in Early Childhood

ERIC Educational Resources Information Center

Kilday, Carolyn R.; Kinzie, Mable B.

2009-01-01

The evaluation of teaching quality in mathematics has become increasingly important following research reports indicating that preschoolers are developmentally able to engage in mathematic thought and that child performance in mathematics at this level is a strong predictor of later school achievement. As attention turns to early mathematics…

An Analysis of the Reasoning Skills of Pre-Service Teachers in the Context of Mathematical Thinking

ERIC Educational Resources Information Center

Yavuz Mumcu, Hayal; Aktürk, Tolga

2017-01-01

The aim of this study is to address and analyse pre-service teachers' mathematical reasoning skills in relation to mathematical thinking processes. For these purposes, pre-service teachers' mathematical reasoning skills namely generalising/abstraction/modelling, ratiocination, development and creative thinking skills and the relationships among…

Pedagogical Applications from Real Analysis for Secondary Mathematics Teachers

ERIC Educational Resources Information Center

Wasserman, Nicholas; Weber, Keith

2017-01-01

In this article, we consider the potential influences of the study of proofs in advanced mathematics on secondary mathematics teaching. Thus far, the literature has highlighted the benefits of applying the conclusions of particular proofs to secondary content and of developing a more general sense of disciplinary practices in mathematics in…

The Multimedia Case as a Tool for Professional Development: An Analysis of Online and Face-to-Face Interaction among Mathematics Pre-Service Teachers, In-Service Teachers, Mathematicians, and Mathematics Teacher Educators

ERIC Educational Resources Information Center

McGraw, Rebecca; Lynch, Kathleen; Koc, Yusuf; Budak, Ayfer; Brown, Catherine A.

2007-01-01

In this study, we consider the potential of multimedia cases as tools for teacher professional development. Specifically, we examined online and face-to-face discussions that occurred within groups composed of pre-service mathematics teachers, in-service mathematics teachers, mathematicians, and mathematics teacher educators. Discussions within…

Mathematics achievement and attitudes of senior secondary-school students in Transkei, South Africa.

PubMed

Kulubya, M M; Glencross, M J

1997-06-01

In a study of mathematics achievement and attitudes toward mathematics, a sample of 266 Standard 10 (Grade 12) students (98 boys and 168 girls) from 10 senior secondary schools in the Umtata district of Transkei, South Africa, were administered a mathematics achievement test and an attitude questionnaire. Contrary to other studies analysis showed no significant relationship between students' scores on measures of mathematics achievement and attitudes.

Envisioning migration: Mathematics in both experimental analysis and modeling of cell behavior

PubMed Central

Zhang, Elizabeth R.; Wu, Lani F.; Altschuler, Steven J.

2013-01-01

The complex nature of cell migration highlights the power and challenges of applying mathematics to biological studies. Mathematics may be used to create model equations that recapitulate migration, which can predict phenomena not easily uncovered by experiments or intuition alone. Alternatively, mathematics may be applied to interpreting complex data sets with better resolution—potentially empowering scientists to discern subtle patterns amid the noise and heterogeneity typical of migrating cells. Iteration between these two methods is necessary in order to reveal connections within the cell migration signaling network, as well as to understand the behavior that arises from those connections. Here, we review recent quantitative analysis and mathematical modeling approaches to the cell migration problem. PMID:23660413

Envisioning migration: mathematics in both experimental analysis and modeling of cell behavior.

PubMed

Zhang, Elizabeth R; Wu, Lani F; Altschuler, Steven J

2013-10-01

The complex nature of cell migration highlights the power and challenges of applying mathematics to biological studies. Mathematics may be used to create model equations that recapitulate migration, which can predict phenomena not easily uncovered by experiments or intuition alone. Alternatively, mathematics may be applied to interpreting complex data sets with better resolution--potentially empowering scientists to discern subtle patterns amid the noise and heterogeneity typical of migrating cells. Iteration between these two methods is necessary in order to reveal connections within the cell migration signaling network, as well as to understand the behavior that arises from those connections. Here, we review recent quantitative analysis and mathematical modeling approaches to the cell migration problem. Copyright © 2013 Elsevier Ltd. All rights reserved.

Genomic similarity and kernel methods I: advancements by building on mathematical and statistical foundations.

PubMed

Schaid, Daniel J

2010-01-01

Measures of genomic similarity are the basis of many statistical analytic methods. We review the mathematical and statistical basis of similarity methods, particularly based on kernel methods. A kernel function converts information for a pair of subjects to a quantitative value representing either similarity (larger values meaning more similar) or distance (smaller values meaning more similar), with the requirement that it must create a positive semidefinite matrix when applied to all pairs of subjects. This review emphasizes the wide range of statistical methods and software that can be used when similarity is based on kernel methods, such as nonparametric regression, linear mixed models and generalized linear mixed models, hierarchical models, score statistics, and support vector machines. The mathematical rigor for these methods is summarized, as is the mathematical framework for making kernels. This review provides a framework to move from intuitive and heuristic approaches to define genomic similarities to more rigorous methods that can take advantage of powerful statistical modeling and existing software. A companion paper reviews novel approaches to creating kernels that might be useful for genomic analyses, providing insights with examples [1]. Copyright © 2010 S. Karger AG, Basel.

Respiratory protective device design using control system techniques

NASA Technical Reports Server (NTRS)

Burgess, W. A.; Yankovich, D.

1972-01-01

The feasibility of a control system analysis approach to provide a design base for respiratory protective devices is considered. A system design approach requires that all functions and components of the system be mathematically identified in a model of the RPD. The mathematical notations describe the operation of the components as closely as possible. The individual component mathematical descriptions are then combined to describe the complete RPD. Finally, analysis of the mathematical notation by control system theory is used to derive compensating component values that force the system to operate in a stable and predictable manner.

A Limit Theorem on the Cores of Large Standard Exchange Economies

PubMed Central

Brown, Donald J.; Robinson, Abraham

1972-01-01

This note introduces a new mathematical tool, nonstandard analysis, for the analysis of an important class of problems in mathematical economics—the relation between bargaining and the competitive price system. PMID:16591988

Mathematical modeling of drying of pretreated and untreated pumpkin.

PubMed

Tunde-Akintunde, T Y; Ogunlakin, G O

2013-08-01

In this study, drying characteristics of pretreated and untreated pumpkin were examined in a hot-air dryer at air temperatures within a range of 40-80 °C and a constant air velocity of 1.5 m/s. The drying was observed to be in the falling-rate drying period and thus liquid diffusion is the main mechanism of moisture movement from the internal regions to the product surface. The experimental drying data for the pumpkin fruits were used to fit Exponential, General exponential, Logarithmic, Page, Midilli-Kucuk and Parabolic model and the statistical validity of models tested were determined by non-linear regression analysis. The Parabolic model had the highest R(2) and lowest χ(2) and RMSE values. This indicates that the Parabolic model is appropriate to describe the dehydration behavior for the pumpkin.

Rheoencephalographic and electroencephalographic measures of cognitive workload: analytical procedures.

PubMed

Montgomery, L D; Montgomery, R W; Guisado, R

1995-05-01

This investigation demonstrates the feasibility of mental workload assessment by rheoencephalographic (REG) and multichannel electroencephalographic (EEG) monitoring. During the performance of this research, unique testing, analytical and display procedures were developed for REG and EEG monitoring that extend the current state of the art and provide valuable tools for the study of cerebral circulatory and neural activity during cognition. REG records are analyzed to provide indices of the right and left hemisphere hemodynamic changes that take place during each test sequence. The EEG data are modeled using regression techniques and mathematically transformed to provide energy-density distributions of the scalp electrostatic field. These procedures permit concurrent REG/EEG cognitive testing not possible with current techniques. The introduction of a system for recording and analysis of cognitive REG/EEG test sequences facilitates the study of learning and memory disorders, dementia and other encephalopathies.

Rheoencephalographic and electroencephalographic measures of cognitive workload: analytical procedures

NASA Technical Reports Server (NTRS)

Montgomery, L. D.; Montgomery, R. W.; Guisado, R.

1995-01-01

This investigation demonstrates the feasibility of mental workload assessment by rheoencephalographic (REG) and multichannel electroencephalographic (EEG) monitoring. During the performance of this research, unique testing, analytical and display procedures were developed for REG and EEG monitoring that extend the current state of the art and provide valuable tools for the study of cerebral circulatory and neural activity during cognition. REG records are analyzed to provide indices of the right and left hemisphere hemodynamic changes that take place during each test sequence. The EEG data are modeled using regression techniques and mathematically transformed to provide energy-density distributions of the scalp electrostatic field. These procedures permit concurrent REG/EEG cognitive testing not possible with current techniques. The introduction of a system for recording and analysis of cognitive REG/EEG test sequences facilitates the study of learning and memory disorders, dementia and other encephalopathies.

Using Group Explorer in teaching abstract algebra

NASA Astrophysics Data System (ADS)

Schubert, Claus; Gfeller, Mary; Donohue, Christopher

2013-04-01

This study explores the use of Group Explorer in an undergraduate mathematics course in abstract algebra. The visual nature of Group Explorer in representing concepts in group theory is an attractive incentive to use this software in the classroom. However, little is known about students' perceptions on this technology in learning concepts in abstract algebra. A total of 26 participants in an undergraduate course studying group theory were surveyed regarding their experiences using Group Explorer. Findings indicate that all participants believed that the software was beneficial to their learning and described their attitudes regarding the software in terms of using the technology and its helpfulness in learning concepts. A multiple regression analysis reveals that representational fluency of concepts with the software correlated significantly with participants' understanding of group concepts yet, participants' attitudes about Group Explorer and technology in general were not significant factors.

Single-parent households and children's educational achievement: A state-level analysis.

PubMed

Amato, Paul R; Patterson, Sarah; Beattie, Brett

2015-09-01

Although many studies have examined associations between family structure and children's educational achievement at the individual level, few studies have considered how the increase in single-parent households may have affected children's educational achievement at the population level. We examined changes in the percentage of children living with single parents between 1990 and 2011 and state mathematics and reading scores on the National Assessment of Educational Progress. Regression models with state and year fixed effects revealed that changes in the percentage of children living with single parents were not associated with test scores. Increases in maternal education, however, were associated with improvements in children's test scores during this period. These results do not support the notion that increases in single parenthood have had serious consequences for U.S. children's school achievement. Copyright © 2015 Elsevier Inc. All rights reserved.

Determining the Pressure Shift of Helium I Lines Using White Dwarf Stars

NASA Astrophysics Data System (ADS)

Camarota, Lawrence

This dissertation explores the non-Doppler shifting of Helium lines in the high pressure conditions of a white dwarf photosphere. In particular, this dissertation seeks to mathematically quantify the shift in a way that is simple to reproduce and account for in future studies without requiring prior knowledge of the star's bulk properties (mass, radius, temperature, etc.). Two main methods will be used in this analysis. First, the spectral line will be quantified with a continuous wavelet transformation, and the components will be used in a chi2 minimizing linear regression to predict the shift. Second, the position of the lines will be calculated using a best-fit Levy-alpha line function. These techniques stand in contrast to traditional methods of quantifying the center of often broad spectral lines, which usually assume symmetry on the parts of the lines.

Evaluation of generalized degrees of freedom for sparse estimation by replica method

NASA Astrophysics Data System (ADS)

Sakata, A.

2016-12-01

We develop a method to evaluate the generalized degrees of freedom (GDF) for linear regression with sparse regularization. The GDF is a key factor in model selection, and thus its evaluation is useful in many modelling applications. An analytical expression for the GDF is derived using the replica method in the large-system-size limit with random Gaussian predictors. The resulting formula has a universal form that is independent of the type of regularization, providing us with a simple interpretation. Within the framework of replica symmetric (RS) analysis, GDF has a physical meaning as the effective fraction of non-zero components. The validity of our method in the RS phase is supported by the consistency of our results with previous mathematical results. The analytical results in the RS phase are calculated numerically using the belief propagation algorithm.

Selecting and Creating Mathematical Tasks: From Research To Practice.

ERIC Educational Resources Information Center

Smith, Margaret Schwan; Stein, Mary Kay

1998-01-01

Focuses on the selection and creation of mathematical tasks, drawing on QUASAR's research on mathematical tasks and experiences with teachers and teacher educators. Presents examples of task analysis and issues that teachers should reflect on. (ASK)

An operational GLS model for hydrologic regression

USGS Publications Warehouse

Tasker, Gary D.; Stedinger, J.R.

1989-01-01

Recent Monte Carlo studies have documented the value of generalized least squares (GLS) procedures to estimate empirical relationships between streamflow statistics and physiographic basin characteristics. This paper presents a number of extensions of the GLS method that deal with realities and complexities of regional hydrologic data sets that were not addressed in the simulation studies. These extensions include: (1) a more realistic model of the underlying model errors; (2) smoothed estimates of cross correlation of flows; (3) procedures for including historical flow data; (4) diagnostic statistics describing leverage and influence for GLS regression; and (5) the formulation of a mathematical program for evaluating future gaging activities. ?? 1989.

Intra-mathematical connections made by high school students in performing Calculus tasks

NASA Astrophysics Data System (ADS)

García-García, Javier; Dolores-Flores, Crisólogo

2018-02-01

In this article, we report the results of research that explores the intra-mathematical connections that high school students make when they solve Calculus tasks, in particular those involving the derivative and the integral. We consider mathematical connections as a cognitive process through which a person relates or associates two or more ideas, concepts, definitions, theorems, procedures, representations and meanings among themselves, with other disciplines or with real life. Task-based interviews were used to collect data and thematic analysis was used to analyze them. Through the analysis of the productions of the 25 participants, we identified 223 intra-mathematical connections. The data allowed us to establish a mathematical connections system which contributes to the understanding of higher concepts, in our case, the Fundamental Theorem of Calculus. We found mathematical connections of the types: different representations, procedural, features, reversibility and meaning as a connection.