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Sample records for probability learning

  1. Learning a Probability Distribution Efficiently and Reliably

    NASA Technical Reports Server (NTRS)

    Laird, Philip; Gamble, Evan

    1988-01-01

    A new algorithm, called the CDF-Inversion Algorithm, is described. Using it, one can efficiently learn a probability distribution over a finite set to a specified accuracy and confidence. The algorithm can be extended to learn joint distributions over a vector space. Some implementation results are described.

  2. Rethinking the learning of belief network probabilities

    SciTech Connect

    Musick, R.

    1996-03-01

    Belief networks are a powerful tool for knowledge discovery that provide concise, understandable probabilistic models of data. There are methods grounded in probability theory to incrementally update the relationships described by the belief network when new information is seen, to perform complex inferences over any set of variables in the data, to incorporate domain expertise and prior knowledge into the model, and to automatically learn the model from data. This paper concentrates on part of the belief network induction problem, that of learning the quantitative structure (the conditional probabilities), given the qualitative structure. In particular, the current practice of rote learning the probabilities in belief networks can be significantly improved upon. We advance the idea of applying any learning algorithm to the task of conditional probability learning in belief networks, discuss potential benefits, and show results of applying neural networks and other algorithms to a medium sized car insurance belief network. The results demonstrate from 10 to 100% improvements in model error rates over the current approaches.

  3. Probability density function learning by unsupervised neurons.

    PubMed

    Fiori, S

    2001-10-01

    In a recent work, we introduced the concept of pseudo-polynomial adaptive activation function neuron (FAN) and presented an unsupervised information-theoretic learning theory for such structure. The learning model is based on entropy optimization and provides a way of learning probability distributions from incomplete data. The aim of the present paper is to illustrate some theoretical features of the FAN neuron, to extend its learning theory to asymmetrical density function approximation, and to provide an analytical and numerical comparison with other known density function estimation methods, with special emphasis to the universal approximation ability. The paper also provides a survey of PDF learning from incomplete data, as well as results of several experiments performed on real-world problems and signals. PMID:11709808

  4. Dynamic probability estimator for machine learning.

    PubMed

    Starzyk, Janusz A; Wang, Feng

    2004-03-01

    An efficient algorithm for dynamic estimation of probabilities without division on unlimited number of input data is presented. The method estimates probabilities of the sampled data from the raw sample count, while keeping the total count value constant. Accuracy of the estimate depends on the counter size, rather than on the total number of data points. Estimator follows variations of the incoming data probability within a fixed window size, without explicit implementation of the windowing technique. Total design area is very small and all probabilities are estimated concurrently. Dynamic probability estimator was implemented using a programmable gate array from Xilinx. The performance of this implementation is evaluated in terms of the area efficiency and execution time. This method is suitable for the highly integrated design of artificial neural networks where a large number of dynamic probability estimators can work concurrently. PMID:15384523

  5. Probability & Statistics: Modular Learning Exercises. Student Edition

    ERIC Educational Resources Information Center

    Actuarial Foundation, 2012

    2012-01-01

    The purpose of these modules is to provide an introduction to the world of probability and statistics to accelerated mathematics students at the high school level. The materials are centered on the fictional town of Happy Shores, a coastal community which is at risk for hurricanes. Actuaries at an insurance company figure out the risks and…

  6. Probability & Statistics: Modular Learning Exercises. Teacher Edition

    ERIC Educational Resources Information Center

    Actuarial Foundation, 2012

    2012-01-01

    The purpose of these modules is to provide an introduction to the world of probability and statistics to accelerated mathematics students at the high school level. The modules also introduce students to real world math concepts and problems that property and casualty actuaries come across in their work. They are designed to be used by teachers and…

  7. Choice Strategies in Multiple-Cue Probability Learning

    ERIC Educational Resources Information Center

    White, Chris M.; Koehler, Derek J.

    2007-01-01

    Choice strategies for selecting among outcomes in multiple-cue probability learning were investigated using a simulated medical diagnosis task. Expected choice probabilities (the proportion of times each outcome was selected given each cue pattern) under alternative choice strategies were constructed from corresponding observed judged…

  8. Fostering Positive Attitude in Probability Learning Using Graphing Calculator

    ERIC Educational Resources Information Center

    Tan, Choo-Kim; Harji, Madhubala Bava; Lau, Siong-Hoe

    2011-01-01

    Although a plethora of research evidence highlights positive and significant outcomes of the incorporation of the Graphing Calculator (GC) in mathematics education, its use in the teaching and learning process appears to be limited. The obvious need to revisit the teaching and learning of Probability has resulted in this study, i.e. to incorporate…

  9. Learning about Posterior Probability: Do Diagrams and Elaborative Interrogation Help?

    ERIC Educational Resources Information Center

    Clinton, Virginia; Alibali, Martha W.; Nathan, Mitchell J.

    2016-01-01

    To learn from a text, students must make meaningful connections among related ideas in that text. This study examined the effectiveness of two methods of improving connections--elaborative interrogation and diagrams--in written lessons about posterior probability. Undergraduate students (N = 198) read a lesson in one of three questioning…

  10. Computational Modelling and Simulation Fostering New Approaches in Learning Probability

    ERIC Educational Resources Information Center

    Kuhn, Markus; Hoppe, Ulrich; Lingnau, Andreas; Wichmann, Astrid

    2006-01-01

    Discovery learning in mathematics in the domain of probability based on hands-on experiments is normally limited because of the difficulty in providing sufficient materials and data volume in terms of repetitions of the experiments. Our cooperative, computational modelling and simulation environment engages students and teachers in composing and…

  11. Dual-Processes in Learning and Judgment: Evidence from the Multiple Cue Probability Learning Paradigm

    ERIC Educational Resources Information Center

    Rolison, Jonathan J.; Evans, Jonathan St. B. T.; Dennis, Ian; Walsh, Clare R.

    2012-01-01

    Multiple cue probability learning (MCPL) involves learning to predict a criterion based on a set of novel cues when feedback is provided in response to each judgment made. But to what extent does MCPL require controlled attention and explicit hypothesis testing? The results of two experiments show that this depends on cue polarity. Learning about…

  12. Supervised learning of probability distributions by neural networks

    NASA Technical Reports Server (NTRS)

    Baum, Eric B.; Wilczek, Frank

    1988-01-01

    Supervised learning algorithms for feedforward neural networks are investigated analytically. The back-propagation algorithm described by Werbos (1974), Parker (1985), and Rumelhart et al. (1986) is generalized by redefining the values of the input and output neurons as probabilities. The synaptic weights are then varied to follow gradients in the logarithm of likelihood rather than in the error. This modification is shown to provide a more rigorous theoretical basis for the algorithm and to permit more accurate predictions. A typical application involving a medical-diagnosis expert system is discussed.

  13. Judgments of learning index relative confidence, not subjective probability.

    PubMed

    Zawadzka, Katarzyna; Higham, Philip A

    2015-11-01

    The underconfidence-with-practice (UWP) effect is a common finding in calibration studies concerned with judgments of learning (JOLs) elicited on a percentage scale. The UWP pattern is present when, in a procedure consisting of multiple study-test cycles, the mean scale JOLs underestimate the mean recall performance on Cycle 2 and beyond. Although this pattern is present both for items recalled and unrecalled on the preceding cycle, to date research has concentrated mostly on the sources of UWP for the latter type of items. In the present study, we aimed to bridge this gap. In three experiments, we examined calibration on the third of three cycles. The results of Experiment 1 demonstrated the typical pattern of higher recall and scale JOLs for previously recalled items than for unrecalled ones. More importantly, they also revealed that even though the UWP effect was found for items previously recalled both once and twice, its magnitude was greater for the former class of items. Experiments 2 and 3, which employed a binary betting task and a binary 0 %/100 % JOL task, respectively, demonstrated that people can accurately predict future recall for previously recalled items with binary decisions. In both experiments, the UWP effect was absent for both items recalled once and twice. We suggest that the sensitivity of scale JOLs, but not binary judgments, to the number of previous recall successes strengthens the claim of Hanczakowski, Zawadzka, Pasek, and Higham (Journal of Memory and Language 69:429-444, 2013) that scale JOLs reflect confidence in, rather than the subjective probability of, future recall. PMID:26111879

  14. A Mathematical Microworld for Students to Learn Introductory Probability.

    ERIC Educational Resources Information Center

    Jiang, Zhonghong; Potter, Walter D.

    1993-01-01

    Describes the Microworld Chance, a simulation-oriented computer environment that allows students to explore probability concepts in five subenvironments: coins, dice, spinners, thumbtacks, and marbles. Results of a teaching experiment to examine the effectiveness of the microworld in changing students' misconceptions about probability are…

  15. Paradoxes and counterexamples in teaching and learning of probability at university

    NASA Astrophysics Data System (ADS)

    Klymchuk, Sergiy; Kachapova, Farida

    2012-09-01

    This article is devoted to practical aspects of teaching and learning of probability at university. It presents the difficulties and attitudes of first-year university science and engineering students towards using paradoxes and counterexamples as a pedagogical strategy in teaching and learning of probability. It also presents a student's point of view on the effectiveness of this pedagogical strategy.

  16. Paradoxes and Counterexamples in Teaching and Learning of Probability at University

    ERIC Educational Resources Information Center

    Klymchuk, Sergiy; Kachapova, Farida

    2012-01-01

    This article is devoted to practical aspects of teaching and learning of probability at university. It presents the difficulties and attitudes of first-year university science and engineering students towards using paradoxes and counterexamples as a pedagogical strategy in teaching and learning of probability. It also presents a student's point of…

  17. The Effects of Memory and Abstractive Integration on Children's Probability Learning.

    ERIC Educational Resources Information Center

    Kreitler, Shulamith; And Others

    1983-01-01

    Examines the relation between children's (1) probability learning performance and a measure of their memory for items presented in a sequence and (2) probability learning and performance on a test of abstractive integration. Participating were 80 six- and seven-year-old boys and girls from both low and middle socioeconomic classes. (Author/RH)

  18. The Effect of Simulation-Based Learning on Prospective Teachers' Inference Skills in Teaching Probability

    ERIC Educational Resources Information Center

    Koparan, Timur; Yilmaz, Gül Kaleli

    2015-01-01

    The effect of simulation-based probability teaching on the prospective teachers' inference skills has been examined with this research. In line with this purpose, it has been aimed to examine the design, implementation and efficiency of a learning environment for experimental probability. Activities were built on modeling, simulation and the…

  19. Sequence Learning in Infancy: The Independent Contributions of Conditional Probability and Pair Frequency Information

    ERIC Educational Resources Information Center

    Marcovitch, Stuart; Lewkowicz, David J.

    2009-01-01

    The ability to perceive sequences is fundamental to cognition. Previous studies have shown that infants can learn visual sequences as early as 2 months of age and it has been suggested that this ability is mediated by sensitivity to conditional probability information. Typically, conditional probability information has covaried with frequency…

  20. Illustrating Probability in Genetics with Hands-On Learning: Making the Math Real

    ERIC Educational Resources Information Center

    Pierce, Benjamin A.; Honeycutt, Brenda B.

    2007-01-01

    Probability is an essential tool for understanding heredity and modern genetics, yet many students have difficulty with this topic due to the abstract and quantitative nature of the subject. To facilitate student learning of probability in genetics, we have developed a set of hands-on, cooperative activities that allow students to determine…

  1. Learning Probabilities in Computer Engineering by Using a Competency- and Problem-Based Approach

    ERIC Educational Resources Information Center

    Khoumsi, Ahmed; Hadjou, Brahim

    2005-01-01

    Our department has redesigned its electrical and computer engineering programs by adopting a learning methodology based on competence development, problem solving, and the realization of design projects. In this article, we show how this pedagogical approach has been successfully used for learning probabilities and their application to computer…

  2. Word Learning by Preschoolers with SLI: Effect of Phonotactic Probability and Object Familiarity

    ERIC Educational Resources Information Center

    Gray, Shelley; Brinkley, Shara; Svetina, Dubravka

    2012-01-01

    Purpose: In this study, the authors investigated whether previous findings of a low phonotactic probability/unfamiliar object word-learning advantage in preschoolers could be replicated, whether this advantage would be apparent at different "stages" of word learning, and whether findings would differ for preschoolers with specific language…

  3. Probability and Statistics in Astronomical Machine Learning and Data Minin

    NASA Astrophysics Data System (ADS)

    Scargle, Jeffrey

    2012-03-01

    Statistical issues peculiar to astronomy have implications for machine learning and data mining. It should be obvious that statistics lies at the heart of machine learning and data mining. Further it should be no surprise that the passive observational nature of astronomy, the concomitant lack of sampling control, and the uniqueness of its realm (the whole universe!) lead to some special statistical issues and problems. As described in the Introduction to this volume, data analysis technology is largely keeping up with major advances in astrophysics and cosmology, even driving many of them. And I realize that there are many scientists with good statistical knowledge and instincts, especially in the modern era I like to call the Age of Digital Astronomy. Nevertheless, old impediments still lurk, and the aim of this chapter is to elucidate some of them. Many experiences with smart people doing not-so-smart things (cf. the anecdotes collected in the Appendix here) have convinced me that the cautions given here need to be emphasized. Consider these four points: 1. Data analysis often involves searches of many cases, for example, outcomes of a repeated experiment, for a feature of the data. 2. The feature comprising the goal of such searches may not be defined unambiguously until the search is carried out, or perhaps vaguely even then. 3. The human visual system is very good at recognizing patterns in noisy contexts. 4. People are much easier to convince of something they want to believe, or already believe, as opposed to unpleasant or surprising facts. One can argue that all four are good things during the initial, exploratory phases of most data analysis. They represent the curiosity and creativity of the scientific process, especially during the exploration of data collections from new observational programs such as all-sky surveys in wavelengths not accessed before or sets of images of a planetary surface not yet explored. On the other hand, confirmatory scientific

  4. The change probability effect: incidental learning, adaptability, and shared visual working memory resources.

    PubMed

    van Lamsweerde, Amanda E; Beck, Melissa R

    2011-12-01

    Statistical properties in the visual environment can be used to improve performance on visual working memory (VWM) tasks. The current study examined the ability to incidentally learn that a change is more likely to occur to a particular feature dimension (shape, color, or location) and use this information to improve change detection performance for that dimension (the change probability effect). Participants completed a change detection task in which one change type was more probable than others. Change probability effects were found for color and shape changes, but not location changes, and intentional strategies did not improve the effect. Furthermore, the change probability effect developed and adapted to new probability information quickly. Finally, in some conditions, an improvement in change detection performance for a probable change led to an impairment in change detection for improbable changes. PMID:21963330

  5. Incidental learning of probability information is differentially affected by the type of visual working memory representation.

    PubMed

    van Lamsweerde, Amanda E; Beck, Melissa R

    2015-12-01

    In this study, we investigated whether the ability to learn probability information is affected by the type of representation held in visual working memory. Across 4 experiments, participants detected changes to displays of coloured shapes. While participants detected changes in 1 dimension (e.g., colour), a feature from a second, nonchanging dimension (e.g., shape) predicted which object was most likely to change. In Experiments 1 and 3, items could be grouped by similarity in the changing dimension across items (e.g., colours and shapes were repeated in the display), while in Experiments 2 and 4 items could not be grouped by similarity (all features were unique). Probability information from the predictive dimension was learned and used to increase performance, but only when all of the features within a display were unique (Experiments 2 and 4). When it was possible to group by feature similarity in the changing dimension (e.g., 2 blue objects appeared within an array), participants were unable to learn probability information and use it to improve performance (Experiments 1 and 3). The results suggest that probability information can be learned in a dimension that is not explicitly task-relevant, but only when the probability information is represented with the changing dimension in visual working memory. PMID:26010021

  6. A Cross-Sectional Comparison of the Effects of Phonotactic Probability and Neighborhood Density on Word Learning by Preschool Children

    ERIC Educational Resources Information Center

    Hoover, Jill R.; Storkel, Holly L.; Hogan, Tiffany P.

    2010-01-01

    Two experiments examined the effects of phonotactic probability and neighborhood density on word learning by 3-, 4-, and 5-year-old children. Nonwords orthogonally varying in probability and density were taught with learning and retention measured via picture naming. Experiment 1 used a within story probability/across story density exposure…

  7. Influence of phonotactic probability/neighbourhood density on lexical learning in late talkers

    PubMed Central

    MacRoy-Higgins, Michelle; Schwartz, Richard G.; Shafer, Valerie L.; Marton, Klara

    2013-01-01

    Background Toddlers who are late talkers demonstrate delays in phonological and lexical skills. However, the influence of phonological factors on lexical acquisition in toddlers who are late talkers has not been examined directly. Aims To examine the influence of phonotactic probability/neighbourhood density on word learning in toddlers who were late talkers using comprehension, production and word recognition tasks. Methods & Procedures Two-year-olds who were late talkers (n = 12) and typically developing toddlers (n = 12) were exposed to 12 novel pseudo-words for unfamiliar objects in ten training sessions. Pseudo-words contained high or low phonotactic probability English sound sequences. The toddlers’ comprehension, speech production and detection of mispronunciation of the newly learned words were examined using a preferential looking paradigm. Outcomes & Results Late talkers showed poorer performance than toddlers with typical language development in all three tasks: comprehension, production and detection of mispronunciations. The toddlers with typical language development showed better speech production and more sensitivity to mispronunciations for high than low phonotactic probability/neighbourhood density sequences. Phonotactic probability/neighbourhood density did not influence the late talkers’ speech production or sensitivity to mispronunciations; they performed similarly for pseudo-words with high and low phonotactic probability/neighbourhood density sound sequences. Conclusions & Implications The results indicate that some late talkers do not recognize statistical properties of their language, which may contribute to their slower lexical learning. PMID:23472958

  8. Blind Students' Learning of Probability through the Use of a Tactile Model

    ERIC Educational Resources Information Center

    Vita, Aida Carvalho; Kataoka, Verônica Yumi

    2014-01-01

    The objective of this paper is to discuss how blind students learn basic concepts of probability using the tactile model proposed by Vita (2012). Among the activities were part of the teaching sequence "Jefferson's Random Walk", in which students built a tree diagram (using plastic trays, foam cards, and toys), and pictograms in 3D…

  9. Effects of Multiple Simulation Presentation among Students of Different Anxiety Levels in the Learning of Probability

    ERIC Educational Resources Information Center

    Fong, Soon Fook; Por, Fei Ping; Tang, Ai Ling

    2012-01-01

    The purpose of this study was to investigate the effects of multiple simulation presentation in interactive multimedia are on the achievement of students with different levels of anxiety in the learning of Probability. The interactive multimedia courseware was developed in two different modes, which were Multiple Simulation Presentation (MSP) and…

  10. The Influence of Phonotactic Probability and Neighborhood Density on Children's Production of Newly Learned Words

    ERIC Educational Resources Information Center

    Heisler, Lori; Goffman, Lisa

    2016-01-01

    A word learning paradigm was used to teach children novel words that varied in phonotactic probability and neighborhood density. The effects of frequency and density on speech production were examined when phonetic forms were nonreferential (i.e., when no referent was attached) and when phonetic forms were referential (i.e., when a referent was…

  11. Influence of Phonotactic Probability/Neighbourhood Density on Lexical Learning in Late Talkers

    ERIC Educational Resources Information Center

    MacRoy-Higgins, Michelle; Schwartz, Richard G.; Shafer, Valerie L.; Marton, Klara

    2013-01-01

    Background: Toddlers who are late talkers demonstrate delays in phonological and lexical skills. However, the influence of phonological factors on lexical acquisition in toddlers who are late talkers has not been examined directly. Aims: To examine the influence of phonotactic probability/neighbourhood density on word learning in toddlers who were…

  12. Splitting the variance of statistical learning performance: A parametric investigation of exposure duration and transitional probabilities.

    PubMed

    Bogaerts, Louisa; Siegelman, Noam; Frost, Ram

    2016-08-01

    What determines individuals' efficacy in detecting regularities in visual statistical learning? Our theoretical starting point assumes that the variance in performance of statistical learning (SL) can be split into the variance related to efficiency in encoding representations within a modality and the variance related to the relative computational efficiency of detecting the distributional properties of the encoded representations. Using a novel methodology, we dissociated encoding from higher-order learning factors, by independently manipulating exposure duration and transitional probabilities in a stream of visual shapes. Our results show that the encoding of shapes and the retrieving of their transitional probabilities are not independent and additive processes, but interact to jointly determine SL performance. The theoretical implications of these findings for a mechanistic explanation of SL are discussed. PMID:26743060

  13. Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets.

    PubMed

    Gruber, Susan; Logan, Roger W; Jarrín, Inmaculada; Monge, Susana; Hernán, Miguel A

    2015-01-15

    Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However, a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predictions from multiple algorithms, ensemble learning offers an alternative to logistic regression modeling to further reduce bias in estimated marginal structural model parameters. We describe the application of two ensemble learning approaches to estimating stabilized weights: super learning (SL), an ensemble machine learning approach that relies on V-fold cross validation, and an ensemble learner (EL) that creates a single partition of the data into training and validation sets. Longitudinal data from two multicenter cohort studies in Spain (CoRIS and CoRIS-MD) were analyzed to estimate the mortality hazard ratio for initiation versus no initiation of combined antiretroviral therapy among HIV positive subjects. Both ensemble approaches produced hazard ratio estimates further away from the null, and with tighter confidence intervals, than logistic regression modeling. Computation time for EL was less than half that of SL. We conclude that ensemble learning using a library of diverse candidate algorithms offers an alternative to parametric modeling of inverse probability weights when fitting marginal structural models. With large datasets, EL provides a rich search over the solution space in less time than SL with comparable results. PMID:25316152

  14. Ensemble learning of inverse probability weights for marginal structural modeling in large observational datasets

    PubMed Central

    Gruber, Susan; Logan, Roger W.; Jarrín, Inmaculada; Monge, Susana; Hernán, Miguel A.

    2014-01-01

    Inverse probability weights used to fit marginal structural models are typically estimated using logistic regression. However a data-adaptive procedure may be able to better exploit information available in measured covariates. By combining predictions from multiple algorithms, ensemble learning offers an alternative to logistic regression modeling to further reduce bias in estimated marginal structural model parameters. We describe the application of two ensemble learning approaches to estimating stabilized weights: super learning (SL), an ensemble machine learning approach that relies on V -fold cross validation, and an ensemble learner (EL) that creates a single partition of the data into training and validation sets. Longitudinal data from two multicenter cohort studies in Spain (CoRIS and CoRIS-MD) were analyzed to estimate the mortality hazard ratio for initiation versus no initiation of combined antiretroviral therapy among HIV positive subjects. Both ensemble approaches produced hazard ratio estimates further away from the null, and with tighter confidence intervals, than logistic regression modeling. Computation time for EL was less than half that of SL. We conclude that ensemble learning using a library of diverse candidate algorithms offers an alternative to parametric modeling of inverse probability weights when fitting marginal structural models. With large datasets, EL provides a rich search over the solution space in less time than SL with comparable results. PMID:25316152

  15. Computational Modeling of Statistical Learning: Effects of Transitional Probability versus Frequency and Links to Word Learning

    ERIC Educational Resources Information Center

    Mirman, Daniel; Estes, Katharine Graf; Magnuson, James S.

    2010-01-01

    Statistical learning mechanisms play an important role in theories of language acquisition and processing. Recurrent neural network models have provided important insights into how these mechanisms might operate. We examined whether such networks capture two key findings in human statistical learning. In Simulation 1, a simple recurrent network…

  16. More than words: Adults learn probabilities over categories and relationships between them

    PubMed Central

    Hudson Kam, Carla L.

    2009-01-01

    This study examines whether human learners can acquire statistics over abstract categories and their relationships to each other. Adult learners were exposed to miniature artificial languages containing variation in the ordering of the Subject, Object, and Verb constituents. Different orders (e.g. SOV, VSO) occurred in the input with different frequencies, but the occurrence of one order versus another was not predictable. Importantly, the language was constructed such that participants could only match the overall input probabilities if they were tracking statistics over abstract categories, not over individual words. At test, participants reproduced the probabilities present in the input with a high degree of accuracy. Closer examination revealed that learner’s were matching the probabilities associated with individual verbs rather than the category as a whole. However, individual nouns had no impact on word orders produced. Thus, participants learned the probabilities of a particular ordering of the abstract grammatical categories Subject and Object associated with each verb. Results suggest that statistical learning mechanisms are capable of tracking relationships between abstract linguistic categories in addition to individual items. PMID:20161375

  17. Impact of Statistical Learning Methods on the Predictive Power of Multivariate Normal Tissue Complication Probability Models

    SciTech Connect

    Xu Chengjian; Schaaf, Arjen van der; Schilstra, Cornelis; Langendijk, Johannes A.; Veld, Aart A. van't

    2012-03-15

    Purpose: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. Methods and Materials: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. Results: It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. Conclusions: The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended.

  18. Learning to Teach Probability: Relationships among Preservice Teachers' Beliefs and Orientations, Content Knowledge, and Pedagogical Content Knowledge of Probability

    ERIC Educational Resources Information Center

    Ives, Sarah Elizabeth

    2009-01-01

    The purposes of this study were to investigate preservice mathematics teachers' orientations, content knowledge, and pedagogical content knowledge of probability; the relationships among these three aspects; and the usefulness of tasks with respect to examining these aspects of knowledge. The design of the study was a multi-case study of five…

  19. Probability estimation with machine learning methods for dichotomous and multicategory outcome: applications.

    PubMed

    Kruppa, Jochen; Liu, Yufeng; Diener, Hans-Christian; Holste, Theresa; Weimar, Christian; König, Inke R; Ziegler, Andreas

    2014-07-01

    Machine learning methods are applied to three different large datasets, all dealing with probability estimation problems for dichotomous or multicategory data. Specifically, we investigate k-nearest neighbors, bagged nearest neighbors, random forests for probability estimation trees, and support vector machines with the kernels of Bessel, linear, Laplacian, and radial basis type. Comparisons are made with logistic regression. The dataset from the German Stroke Study Collaboration with dichotomous and three-category outcome variables allows, in particular, for temporal and external validation. The other two datasets are freely available from the UCI learning repository and provide dichotomous outcome variables. One of them, the Cleveland Clinic Foundation Heart Disease dataset, uses data from one clinic for training and from three clinics for external validation, while the other, the thyroid disease dataset, allows for temporal validation by separating data into training and test data by date of recruitment into study. For dichotomous outcome variables, we use receiver operating characteristics, areas under the curve values with bootstrapped 95% confidence intervals, and Hosmer-Lemeshow-type figures as comparison criteria. For dichotomous and multicategory outcomes, we calculated bootstrap Brier scores with 95% confidence intervals and also compared them through bootstrapping. In a supplement, we provide R code for performing the analyses and for random forest analyses in Random Jungle, version 2.1.0. The learning machines show promising performance over all constructed models. They are simple to apply and serve as an alternative approach to logistic or multinomial logistic regression analysis. PMID:24989843

  20. Under the hood of statistical learning: A statistical MMN reflects the magnitude of transitional probabilities in auditory sequences

    PubMed Central

    Koelsch, Stefan; Busch, Tobias; Jentschke, Sebastian; Rohrmeier, Martin

    2016-01-01

    Within the framework of statistical learning, many behavioural studies investigated the processing of unpredicted events. However, surprisingly few neurophysiological studies are available on this topic, and no statistical learning experiment has investigated electroencephalographic (EEG) correlates of processing events with different transition probabilities. We carried out an EEG study with a novel variant of the established statistical learning paradigm. Timbres were presented in isochronous sequences of triplets. The first two sounds of all triplets were equiprobable, while the third sound occurred with either low (10%), intermediate (30%), or high (60%) probability. Thus, the occurrence probability of the third item of each triplet (given the first two items) was varied. Compared to high-probability triplet endings, endings with low and intermediate probability elicited an early anterior negativity that had an onset around 100 ms and was maximal at around 180 ms. This effect was larger for events with low than for events with intermediate probability. Our results reveal that, when predictions are based on statistical learning, events that do not match a prediction evoke an early anterior negativity, with the amplitude of this mismatch response being inversely related to the probability of such events. Thus, we report a statistical mismatch negativity (sMMN) that reflects statistical learning of transitional probability distributions that go beyond auditory sensory memory capabilities. PMID:26830652

  1. The effect of incremental changes in phonotactic probability and neighborhood density on word learning by preschool children

    PubMed Central

    Storkel, Holly L.; Bontempo, Daniel E.; Aschenbrenner, Andrew J.; Maekawa, Junko; Lee, Su-Yeon

    2013-01-01

    Purpose Phonotactic probability or neighborhood density have predominately been defined using gross distinctions (i.e., low vs. high). The current studies examined the influence of finer changes in probability (Experiment 1) and density (Experiment 2) on word learning. Method The full range of probability or density was examined by sampling five nonwords from each of four quartiles. Three- and 5-year-old children received training on nonword-nonobject pairs. Learning was measured in a picture-naming task immediately following training and 1-week after training. Results were analyzed using multi-level modeling. Results A linear spline model best captured nonlinearities in phonotactic probability. Specifically word learning improved as probability increased in the lowest quartile, worsened as probability increased in the midlow quartile, and then remained stable and poor in the two highest quartiles. An ordinary linear model sufficiently described neighborhood density. Here, word learning improved as density increased across all quartiles. Conclusion Given these different patterns, phonotactic probability and neighborhood density appear to influence different word learning processes. Specifically, phonotactic probability may affect recognition that a sound sequence is an acceptable word in the language and is a novel word for the child, whereas neighborhood density may influence creation of a new representation in long-term memory. PMID:23882005

  2. The Effect of Incremental Changes in Phonotactic Probability and Neighborhood Density on Word Learning by Preschool Children

    ERIC Educational Resources Information Center

    Storkel, Holly L.; Bontempo, Daniel E.; Aschenbrenner, Andrew J.; Maekawa, Junko; Lee, Su-Yeon

    2013-01-01

    Purpose: Phonotactic probability or neighborhood density has predominately been defined through the use of gross distinctions (i.e., low vs. high). In the current studies, the authors examined the influence of finer changes in probability (Experiment 1) and density (Experiment 2) on word learning. Method: The authors examined the full range of…

  3. Triggering word learning in children with Language Impairment: the effect of phonotactic probability and neighbourhood density.

    PubMed

    McKean, Cristina; Letts, Carolyn; Howard, David

    2014-11-01

    The effect of phonotactic probability (PP) and neighbourhood density (ND) on triggering word learning was examined in children with Language Impairment (3;04-6;09) and compared to Typically Developing children. Nonwords, varying PP and ND orthogonally, were presented in a story context and their learning tested using a referent identification task. Group comparisons with receptive vocabulary as a covariate found no group differences in overall scores or in the influence of PP or ND. Therefore, there was no evidence of atypical lexical or phonological processing. 'Convergent' PP/ND (High PP/High ND; Low PP/Low ND) was optimal for word learning in both groups. This bias interacted with vocabulary knowledge. 'Divergent' PP/ND word scores (High PP/Low ND; Low PP/High ND) were positively correlated with vocabulary so the 'divergence disadvantage' reduced as vocabulary knowledge grew; an interaction hypothesized to represent developmental changes in lexical-phonological processing linked to the emergence of phonological representations. PMID:24191951

  4. The Distracting Effect of Material Reward: An Alternative Explanation for the Superior Performance of Reward Groups in Probability Learning

    ERIC Educational Resources Information Center

    McGraw, Kenneth O.; McCullers, John C.

    1974-01-01

    To determine whether the distraction effect associated with material rewards in discrimination learning can account for the superior performance of reward groups in probability learning, the performance of 144 school children (preschool, second, and fifth grades) on a two-choice successive discrimination task was compared under three reinforcement…

  5. ANNz2 - Photometric redshift and probability density function estimation using machine-learning

    NASA Astrophysics Data System (ADS)

    Sadeh, Iftach

    2014-05-01

    Large photometric galaxy surveys allow the study of questions at the forefront of science, such as the nature of dark energy. The success of such surveys depends on the ability to measure the photometric redshifts of objects (photo-zs), based on limited spectral data. A new major version of the public photo-z estimation software, ANNz , is presented here. The new code incorporates several machine-learning methods, such as artificial neural networks and boosted decision/regression trees, which are all used in concert. The objective of the algorithm is to dynamically optimize the performance of the photo-z estimation, and to properly derive the associated uncertainties. In addition to single-value solutions, the new code also generates full probability density functions in two independent ways.

  6. Learning concepts of fractals and probability by “doing science”

    NASA Astrophysics Data System (ADS)

    Stanley, H. Eugene

    1989-09-01

    Very recent advances in computer technology provide the power of mainframe systems in relatively compact and inexpensive personal computers; soon the computing power of even a supercomputer will be available on a desktop at a price comparable to today's personal computers. Over the next decade this tremendous computing power can and probably will become available in schools throughout the world. Here we discuss the possibility of harnessing this new technological resource as a teaching tool for specific topics in mathematics and science, focusing on random processes in nature and their deep connection to concepts in probability and fractal geometry. Such natural phenomena as the growth of snowflakes via random aggregation and the disordered geometric configurations of polymer chains demonstrate that fundamentally random microscopic processes can give rise to predictable macroscopic behaviors. They also give rise to random fractal structures of inherent interest and great beauty. Because it is impossible to view the underlying processes directly, computer simulation and visualization is an indispensable tool for understanding and studying these phenomena. In the process of “doing science” with both hands-on experiments and computer simulations, students would learn abstract mathematical concepts in a context which is at once concrete and inherently motivating. Furthermore, the techniques they could employ would mirror in most respects those in current use by researchers, thus forging an unprecedented link between this curriculum and the professional worlds of science and mathematics.

  7. Activity in Inferior Parietal and Medial Prefrontal Cortex Signals the Accumulation of Evidence in a Probability Learning Task

    PubMed Central

    d'Acremont, Mathieu; Fornari, Eleonora; Bossaerts, Peter

    2013-01-01

    In an uncertain environment, probabilities are key to predicting future events and making adaptive choices. However, little is known about how humans learn such probabilities and where and how they are encoded in the brain, especially when they concern more than two outcomes. During functional magnetic resonance imaging (fMRI), young adults learned the probabilities of uncertain stimuli through repetitive sampling. Stimuli represented payoffs and participants had to predict their occurrence to maximize their earnings. Choices indicated loss and risk aversion but unbiased estimation of probabilities. BOLD response in medial prefrontal cortex and angular gyri increased linearly with the probability of the currently observed stimulus, untainted by its value. Connectivity analyses during rest and task revealed that these regions belonged to the default mode network. The activation of past outcomes in memory is evoked as a possible mechanism to explain the engagement of the default mode network in probability learning. A BOLD response relating to value was detected only at decision time, mainly in striatum. It is concluded that activity in inferior parietal and medial prefrontal cortex reflects the amount of evidence accumulated in favor of competing and uncertain outcomes. PMID:23401673

  8. Computer-Based Graphical Displays for Enhancing Mental Animation and Improving Reasoning in Novice Learning of Probability

    ERIC Educational Resources Information Center

    Kaplan, Danielle E.; Wu, Erin Chia-ling

    2006-01-01

    Our research suggests static and animated graphics can lead to more animated thinking and more correct problem solving in computer-based probability learning. Pilot software modules were developed for graduate online statistics courses and representation research. A study with novice graduate student statisticians compared problem solving in five…

  9. Using Rasch Analysis to Explore What Students Learn about Probability Concepts

    ERIC Educational Resources Information Center

    Mahmud, Zamalia; Porter, Anne

    2015-01-01

    Students' understanding of probability concepts have been investigated from various different perspectives. This study was set out to investigate perceived understanding of probability concepts of forty-four students from the STAT131 Understanding Uncertainty and Variation course at the University of Wollongong, NSW. Rasch measurement which is…

  10. Calibrating perceived understanding and competency in probability concepts: A diagnosis of learning difficulties based on Rasch probabilistic model

    NASA Astrophysics Data System (ADS)

    Mahmud, Zamalia; Porter, Anne; Salikin, Masniyati; Ghani, Nor Azura Md

    2015-12-01

    Students' understanding of probability concepts have been investigated from various different perspectives. Competency on the other hand is often measured separately in the form of test structure. This study was set out to show that perceived understanding and competency can be calibrated and assessed together using Rasch measurement tools. Forty-four students from the STAT131 Understanding Uncertainty and Variation course at the University of Wollongong, NSW have volunteered to participate in the study. Rasch measurement which is based on a probabilistic model is used to calibrate the responses from two survey instruments and investigate the interactions between them. Data were captured from the e-learning platform Moodle where students provided their responses through an online quiz. The study shows that majority of the students perceived little understanding about conditional and independent events prior to learning about it but tend to demonstrate a slightly higher competency level afterward. Based on the Rasch map, there is indication of some increase in learning and knowledge about some probability concepts at the end of the two weeks lessons on probability concepts.

  11. Value and probability coding in a feedback-based learning task utilizing food rewards

    PubMed Central

    Lempert, Karolina M.

    2014-01-01

    For the consequences of our actions to guide behavior, the brain must represent different types of outcome-related information. For example, an outcome can be construed as negative because an expected reward was not delivered or because an outcome of low value was delivered. Thus behavioral consequences can differ in terms of the information they provide about outcome probability and value. We investigated the role of the striatum in processing probability-based and value-based negative feedback by training participants to associate cues with food rewards and then employing a selective satiety procedure to devalue one food outcome. Using functional magnetic resonance imaging, we examined brain activity related to receipt of expected rewards, receipt of devalued outcomes, omission of expected rewards, omission of devalued outcomes, and expected omissions of an outcome. Nucleus accumbens activation was greater for rewarding outcomes than devalued outcomes, but activity in this region did not correlate with the probability of reward receipt. Activation of the right caudate and putamen, however, was largest in response to rewarding outcomes relative to expected omissions of reward. The dorsal striatum (caudate and putamen) at the time of feedback also showed a parametric increase correlating with the trialwise probability of reward receipt. Our results suggest that the ventral striatum is sensitive to the motivational relevance, or subjective value, of the outcome, while the dorsal striatum codes for a more complex signal that incorporates reward probability. Value and probability information may be integrated in the dorsal striatum, to facilitate action planning and allocation of effort. PMID:25339705

  12. Learning in reverse: 8-month-old infants track backward transitional probabilities

    PubMed Central

    Pelucchi, Bruna; Hay, Jessica F.; Saffran, Jenny R.

    2009-01-01

    Numerous recent studies suggest that human learners, including both infants and adults, readily track sequential statistics computed between adjacent elements. One such statistic, transitional probability, is typically calculated as the likelihood that one element predicts another. However, little is known about whether listeners are sensitive to the directionality of this computation. To address this issue, we tested 8-month-old infants in a word segmentation task, using fluent speech drawn from an unfamiliar natural language. Critically, test items were distinguished solely by their backward transitional probabilities. The results provide the first evidence that infants track backward statistics in fluent speech. PMID:19717144

  13. We Can Still Learn About Probability by Rolling Dice and Tossing Coins

    ERIC Educational Resources Information Center

    Dunn, Peter K.

    2005-01-01

    Rolling dice and tossing coins can still be used to teach probability even if students know (or think they know) what happens in these experiments. This article considers many simple variations of these experiments which are interesting, potentially enjoyable and challenging. Using these variations can cause students (and teachers) to think again…

  14. Learning probability distributions from smooth observables and the maximum entropy principle: some remarks

    NASA Astrophysics Data System (ADS)

    Obuchi, Tomoyuki; Monasson, Rémi

    2015-09-01

    The maximum entropy principle (MEP) is a very useful working hypothesis in a wide variety of inference problems, ranging from biological to engineering tasks. To better understand the reasons of the success of MEP, we propose a statistical-mechanical formulation to treat the space of probability distributions constrained by the measures of (experimental) observables. In this paper we first review the results of a detailed analysis of the simplest case of randomly chosen observables. In addition, we investigate by numerical and analytical means the case of smooth observables, which is of practical relevance. Our preliminary results are presented and discussed with respect to the efficiency of the MEP.

  15. Unification of field theory and maximum entropy methods for learning probability densities

    NASA Astrophysics Data System (ADS)

    Kinney, Justin B.

    2015-09-01

    The need to estimate smooth probability distributions (a.k.a. probability densities) from finite sampled data is ubiquitous in science. Many approaches to this problem have been described, but none is yet regarded as providing a definitive solution. Maximum entropy estimation and Bayesian field theory are two such approaches. Both have origins in statistical physics, but the relationship between them has remained unclear. Here I unify these two methods by showing that every maximum entropy density estimate can be recovered in the infinite smoothness limit of an appropriate Bayesian field theory. I also show that Bayesian field theory estimation can be performed without imposing any boundary conditions on candidate densities, and that the infinite smoothness limit of these theories recovers the most common types of maximum entropy estimates. Bayesian field theory thus provides a natural test of the maximum entropy null hypothesis and, furthermore, returns an alternative (lower entropy) density estimate when the maximum entropy hypothesis is falsified. The computations necessary for this approach can be performed rapidly for one-dimensional data, and software for doing this is provided.

  16. The Influence of Part-Word Phonotactic Probability/Neighborhood Density on Word Learning by Preschool Children Varying in Expressive Vocabulary

    ERIC Educational Resources Information Center

    Storkel, Holly L.; Hoover, Jill R.

    2011-01-01

    The goal of this study was to examine the influence of part-word phonotactic probability/neighborhood density on word learning by preschool children with normal vocabularies that varied in size. Ninety-eight children (age 2 ; 11-6 ; 0) were taught consonant-vowel-consonant (CVC) nonwords orthogonally varying in the probability/density of the CV…

  17. A Study of Students' Learning Styles, Discipline Attitudes and Knowledge Acquisition in Technology-Enhanced Probability and Statistics Education.

    PubMed

    Christou, Nicolas; Dinov, Ivo D

    2010-09-01

    Many modern technological advances have direct impact on the format, style and efficacy of delivery and consumption of educational content. For example, various novel communication and information technology tools and resources enable efficient, timely, interactive and graphical demonstrations of diverse scientific concepts. In this manuscript, we report on a meta-study of 3 controlled experiments of using the Statistics Online Computational Resources in probability and statistics courses. Web-accessible SOCR applets, demonstrations, simulations and virtual experiments were used in different courses as treatment and compared to matched control classes utilizing traditional pedagogical approaches. Qualitative and quantitative data we collected for all courses included Felder-Silverman-Soloman index of learning styles, background assessment, pre and post surveys of attitude towards the subject, end-point satisfaction survey, and varieties of quiz, laboratory and test scores. Our findings indicate that students' learning styles and attitudes towards a discipline may be important confounds of their final quantitative performance. The observed positive effects of integrating information technology with established pedagogical techniques may be valid across disciplines within the broader spectrum courses in the science education curriculum. The two critical components of improving science education via blended instruction include instructor training, and development of appropriate activities, simulations and interactive resources. PMID:21603097

  18. Effect of Phonotactic Probability and Neighborhood Density on Word-Learning Configuration by Preschoolers with Typical Development and Specific Language Impairment

    ERIC Educational Resources Information Center

    Gray, Shelley; Pittman, Andrea; Weinhold, Juliet

    2014-01-01

    Purpose: In this study, the authors assessed the effects of phonotactic probability and neighborhood density on word-learning configuration by preschoolers with specific language impairment (SLI) and typical language development (TD). Method: One hundred thirty-one children participated: 48 with SLI, 44 with TD matched on age and gender, and 39…

  19. Prediction of seizure incidence probability in PTZ model of kindling through spatial learning ability in male and female rats.

    PubMed

    Haeri, Narges-Al-Sadat; Palizvan, Mohammad Reza; Sadegh, Mehdi; Aghaei, Zohre; Rafiei, Mohammad

    2016-07-01

    Epilepsy is a common neurological disease characterized by periodic seizures. Cognitive deficits and impairments in learning and memory are also associated with epilepsy. Neuronal changes and synaptic modifications in kindling model of epilepsy are similar to those occur during the learning procedure and memory formation. Herein we investigated whether seizure susceptibility in pentylenetetrazol (PTZ) model of kindling is predictable based on the learning ability in the Morris water maze (MWM) task in male and female rats. Allocentric learning was tested using MWM in present of light while egocentric learning was evaluated by MWM in dark room. The results indicated no significant differences in allocentric learning abilities between male and female rats. However, male rats were able to memorize the location of the platform more effectively compared to females in egocentric test. In addition, a statistically significant negative correlation between learning abilities (working memory) and seizure susceptibility in male rats was found while this correlation was positive in female rats. On the other hand, although there was no significant correlation between retrieval (reference memory) of spatial memories and seizure parameters in male rats, female rats showed a significant negative correlation. These findings may provide some evidences for prediction of seizure susceptibility according to learning ability and memory retention. PMID:27098273

  20. Why Probability?

    ERIC Educational Resources Information Center

    Weatherly, Myra S.

    1984-01-01

    Instruction in mathematical probability to enhance higher levels of critical and creative thinking with gifted students is described. Among thinking skills developed by such an approach are analysis, synthesis, evaluation, fluency, and complexity. (CL)

  1. Probability workshop to be better in probability topic

    NASA Astrophysics Data System (ADS)

    Asmat, Aszila; Ujang, Suriyati; Wahid, Sharifah Norhuda Syed

    2015-02-01

    The purpose of the present study was to examine whether statistics anxiety and attitudes towards probability topic among students in higher education level have an effect on their performance. 62 fourth semester science students were given statistics anxiety questionnaires about their perception towards probability topic. Result indicated that students' performance in probability topic is not related to anxiety level, which means that the higher level in statistics anxiety will not cause lower score in probability topic performance. The study also revealed that motivated students gained from probability workshop ensure that their performance in probability topic shows a positive improvement compared before the workshop. In addition there exists a significance difference in students' performance between genders with better achievement among female students compared to male students. Thus, more initiatives in learning programs with different teaching approaches is needed to provide useful information in improving student learning outcome in higher learning institution.

  2. Uncertainty quantification and integration of machine learning techniques for predicting acid rock drainage chemistry: a probability bounds approach.

    PubMed

    Betrie, Getnet D; Sadiq, Rehan; Morin, Kevin A; Tesfamariam, Solomon

    2014-08-15

    Acid rock drainage (ARD) is a major pollution problem globally that has adversely impacted the environment. Identification and quantification of uncertainties are integral parts of ARD assessment and risk mitigation, however previous studies on predicting ARD drainage chemistry have not fully addressed issues of uncertainties. In this study, artificial neural networks (ANN) and support vector machine (SVM) are used for the prediction of ARD drainage chemistry and their predictive uncertainties are quantified using probability bounds analysis. Furthermore, the predictions of ANN and SVM are integrated using four aggregation methods to improve their individual predictions. The results of this study showed that ANN performed better than SVM in enveloping the observed concentrations. In addition, integrating the prediction of ANN and SVM using the aggregation methods improved the predictions of individual techniques. PMID:24852616

  3. Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting.

    PubMed

    Vock, David M; Wolfson, Julian; Bandyopadhyay, Sunayan; Adomavicius, Gediminas; Johnson, Paul E; Vazquez-Benitez, Gabriela; O'Connor, Patrick J

    2016-06-01

    Models for predicting the probability of experiencing various health outcomes or adverse events over a certain time frame (e.g., having a heart attack in the next 5years) based on individual patient characteristics are important tools for managing patient care. Electronic health data (EHD) are appealing sources of training data because they provide access to large amounts of rich individual-level data from present-day patient populations. However, because EHD are derived by extracting information from administrative and clinical databases, some fraction of subjects will not be under observation for the entire time frame over which one wants to make predictions; this loss to follow-up is often due to disenrollment from the health system. For subjects without complete follow-up, whether or not they experienced the adverse event is unknown, and in statistical terms the event time is said to be right-censored. Most machine learning approaches to the problem have been relatively ad hoc; for example, common approaches for handling observations in which the event status is unknown include (1) discarding those observations, (2) treating them as non-events, (3) splitting those observations into two observations: one where the event occurs and one where the event does not. In this paper, we present a general-purpose approach to account for right-censored outcomes using inverse probability of censoring weighting (IPCW). We illustrate how IPCW can easily be incorporated into a number of existing machine learning algorithms used to mine big health care data including Bayesian networks, k-nearest neighbors, decision trees, and generalized additive models. We then show that our approach leads to better calibrated predictions than the three ad hoc approaches when applied to predicting the 5-year risk of experiencing a cardiovascular adverse event, using EHD from a large U.S. Midwestern healthcare system. PMID:26992568

  4. Evaluation of the probability of arrester failure in a high-voltage transmission line using a Q learning artificial neural network model

    NASA Astrophysics Data System (ADS)

    Ekonomou, L.; Karampelas, P.; Vita, V.; Chatzarakis, G. E.

    2011-04-01

    One of the most popular methods of protecting high voltage transmission lines against lightning strikes and internal overvoltages is the use of arresters. The installation of arresters in high voltage transmission lines can prevent or even reduce the lines' failure rate. Several studies based on simulation tools have been presented in order to estimate the critical currents that exceed the arresters' rated energy stress and to specify the arresters' installation interval. In this work artificial intelligence, and more specifically a Q-learning artificial neural network (ANN) model, is addressed for evaluating the arresters' failure probability. The aims of the paper are to describe in detail the developed Q-learning ANN model and to compare the results obtained by its application in operating 150 kV Greek transmission lines with those produced using a simulation tool. The satisfactory and accurate results of the proposed ANN model can make it a valuable tool for designers of electrical power systems seeking more effective lightning protection, reducing operational costs and better continuity of service.

  5. Probability 1/e

    ERIC Educational Resources Information Center

    Koo, Reginald; Jones, Martin L.

    2011-01-01

    Quite a number of interesting problems in probability feature an event with probability equal to 1/e. This article discusses three such problems and attempts to explain why this probability occurs with such frequency.

  6. On Probability Domains III

    NASA Astrophysics Data System (ADS)

    Frič, Roman; Papčo, Martin

    2015-12-01

    Domains of generalized probability have been introduced in order to provide a general construction of random events, observables and states. It is based on the notion of a cogenerator and the properties of product. We continue our previous study and show how some other quantum structures fit our categorical approach. We discuss how various epireflections implicitly used in the classical probability theory are related to the transition to fuzzy probability theory and describe the latter probability theory as a genuine categorical extension of the former. We show that the IF-probability can be studied via the fuzzy probability theory. We outline a "tensor modification" of the fuzzy probability theory.

  7. The Role of Cooperative Learning Type Team Assisted Individualization to Improve the Students' Mathematics Communication Ability in the Subject of Probability Theory

    ERIC Educational Resources Information Center

    Tinungki, Georgina Maria

    2015-01-01

    The importance of learning mathematics can not be separated from its role in all aspects of life. Communicating ideas by using mathematics language is even more practical, systematic, and efficient. In order to overcome the difficulties of students who have insufficient understanding of mathematics material, good communications should be built in…

  8. Experience matters: information acquisition optimizes probability gain.

    PubMed

    Nelson, Jonathan D; McKenzie, Craig R M; Cottrell, Garrison W; Sejnowski, Terrence J

    2010-07-01

    Deciding which piece of information to acquire or attend to is fundamental to perception, categorization, medical diagnosis, and scientific inference. Four statistical theories of the value of information-information gain, Kullback-Liebler distance, probability gain (error minimization), and impact-are equally consistent with extant data on human information acquisition. Three experiments, designed via computer optimization to be maximally informative, tested which of these theories best describes human information search. Experiment 1, which used natural sampling and experience-based learning to convey environmental probabilities, found that probability gain explained subjects' information search better than the other statistical theories or the probability-of-certainty heuristic. Experiments 1 and 2 found that subjects behaved differently when the standard method of verbally presented summary statistics (rather than experience-based learning) was used to convey environmental probabilities. Experiment 3 found that subjects' preference for probability gain is robust, suggesting that the other models contribute little to subjects' search behavior. PMID:20525915

  9. Experience Matters: Information Acquisition Optimizes Probability Gain

    PubMed Central

    Nelson, Jonathan D.; McKenzie, Craig R.M.; Cottrell, Garrison W.; Sejnowski, Terrence J.

    2010-01-01

    Deciding which piece of information to acquire or attend to is fundamental to perception, categorization, medical diagnosis, and scientific inference. Four statistical theories of the value of information—information gain, Kullback-Liebler distance, probability gain (error minimization), and impact—are equally consistent with extant data on human information acquisition. Three experiments, designed via computer optimization to be maximally informative, tested which of these theories best describes human information search. Experiment 1, which used natural sampling and experience-based learning to convey environmental probabilities, found that probability gain explained subjects’ information search better than the other statistical theories or the probability-of-certainty heuristic. Experiments 1 and 2 found that subjects behaved differently when the standard method of verbally presented summary statistics (rather than experience-based learning) was used to convey environmental probabilities. Experiment 3 found that subjects’ preference for probability gain is robust, suggesting that the other models contribute little to subjects’ search behavior. PMID:20525915

  10. Probability and Relative Frequency

    NASA Astrophysics Data System (ADS)

    Drieschner, Michael

    2016-01-01

    The concept of probability seems to have been inexplicable since its invention in the seventeenth century. In its use in science, probability is closely related with relative frequency. So the task seems to be interpreting that relation. In this paper, we start with predicted relative frequency and show that its structure is the same as that of probability. I propose to call that the `prediction interpretation' of probability. The consequences of that definition are discussed. The "ladder"-structure of the probability calculus is analyzed. The expectation of the relative frequency is shown to be equal to the predicted relative frequency. Probability is shown to be the most general empirically testable prediction.

  11. BIODEGRADATION PROBABILITY PROGRAM (BIODEG)

    EPA Science Inventory

    The Biodegradation Probability Program (BIODEG) calculates the probability that a chemical under aerobic conditions with mixed cultures of microorganisms will biodegrade rapidly or slowly. It uses fragment constants developed using multiple linear and non-linear regressions and d...

  12. Evolution and Probability.

    ERIC Educational Resources Information Center

    Bailey, David H.

    2000-01-01

    Some of the most impressive-sounding criticisms of the conventional theory of biological evolution involve probability. Presents a few examples of how probability should and should not be used in discussing evolution. (ASK)

  13. Probability on a Budget.

    ERIC Educational Resources Information Center

    Ewbank, William A.; Ginther, John L.

    2002-01-01

    Describes how to use common dice numbered 1-6 for simple mathematical situations including probability. Presents a lesson using regular dice and specially marked dice to explore some of the concepts of probability. (KHR)

  14. Spatial Probability Cuing and Right Hemisphere Damage

    ERIC Educational Resources Information Center

    Shaqiri, Albulena; Anderson, Britt

    2012-01-01

    In this experiment we studied statistical learning, inter-trial priming, and visual attention. We assessed healthy controls and right brain damaged (RBD) patients with and without neglect, on a simple visual discrimination task designed to measure priming effects and probability learning. All participants showed a preserved priming effect for item…

  15. Dependent Probability Spaces

    ERIC Educational Resources Information Center

    Edwards, William F.; Shiflett, Ray C.; Shultz, Harris

    2008-01-01

    The mathematical model used to describe independence between two events in probability has a non-intuitive consequence called dependent spaces. The paper begins with a very brief history of the development of probability, then defines dependent spaces, and reviews what is known about finite spaces with uniform probability. The study of finite…

  16. Searching with probabilities

    SciTech Connect

    Palay, A.J.

    1985-01-01

    This book examines how probability distributions can be used as a knowledge representation technique. It presents a mechanism that can be used to guide a selective search algorithm to solve a variety of tactical chess problems. Topics covered include probabilities and searching the B algorithm and chess probabilities - in practice, examples, results, and future work.

  17. In All Probability, Probability is not All

    ERIC Educational Resources Information Center

    Helman, Danny

    2004-01-01

    The national lottery is often portrayed as a game of pure chance with no room for strategy. This misperception seems to stem from the application of probability instead of expectancy considerations, and can be utilized to introduce the statistical concept of expectation.

  18. Predicting accurate probabilities with a ranking loss

    PubMed Central

    Menon, Aditya Krishna; Jiang, Xiaoqian J; Vembu, Shankar; Elkan, Charles; Ohno-Machado, Lucila

    2013-01-01

    In many real-world applications of machine learning classifiers, it is essential to predict the probability of an example belonging to a particular class. This paper proposes a simple technique for predicting probabilities based on optimizing a ranking loss, followed by isotonic regression. This semi-parametric technique offers both good ranking and regression performance, and models a richer set of probability distributions than statistical workhorses such as logistic regression. We provide experimental results that show the effectiveness of this technique on real-world applications of probability prediction. PMID:25285328

  19. A Posteriori Transit Probabilities

    NASA Astrophysics Data System (ADS)

    Stevens, Daniel J.; Gaudi, B. Scott

    2013-08-01

    Given the radial velocity (RV) detection of an unseen companion, it is often of interest to estimate the probability that the companion also transits the primary star. Typically, one assumes a uniform distribution for the cosine of the inclination angle i of the companion's orbit. This yields the familiar estimate for the prior transit probability of ~Rlowast/a, given the primary radius Rlowast and orbital semimajor axis a, and assuming small companions and a circular orbit. However, the posterior transit probability depends not only on the prior probability distribution of i but also on the prior probability distribution of the companion mass Mc, given a measurement of the product of the two (the minimum mass Mc sin i) from an RV signal. In general, the posterior can be larger or smaller than the prior transit probability. We derive analytic expressions for the posterior transit probability assuming a power-law form for the distribution of true masses, dΓ/dMcvpropMcα, for integer values -3 <= α <= 3. We show that for low transit probabilities, these probabilities reduce to a constant multiplicative factor fα of the corresponding prior transit probability, where fα in general depends on α and an assumed upper limit on the true mass. The prior and posterior probabilities are equal for α = -1. The posterior transit probability is ~1.5 times larger than the prior for α = -3 and is ~4/π times larger for α = -2, but is less than the prior for α>=0, and can be arbitrarily small for α > 1. We also calculate the posterior transit probability in different mass regimes for two physically-motivated mass distributions of companions around Sun-like stars. We find that for Jupiter-mass planets, the posterior transit probability is roughly equal to the prior probability, whereas the posterior is likely higher for Super-Earths and Neptunes (10 M⊕ - 30 M⊕) and Super-Jupiters (3 MJup - 10 MJup), owing to the predicted steep rise in the mass function toward smaller

  20. Normal tissue complication probability (NTCP) modelling using spatial dose metrics and machine learning methods for severe acute oral mucositis resulting from head and neck radiotherapy

    PubMed Central

    Dean, Jamie A; Wong, Kee H; Welsh, Liam C; Jones, Ann-Britt; Schick, Ulrike; Newbold, Kate L; Bhide, Shreerang A; Harrington, Kevin J; Nutting, Christopher M; Gulliford, Sarah L

    2016-01-01

    Background and Purpose Severe acute mucositis commonly results from head and neck (chemo)radiotherapy. A predictive model of mucositis could guide clinical decision-making and inform treatment planning. We aimed to generate such a model using spatial dose metrics and machine learning. Material and Methods Predictive models of severe acute mucositis were generated using radiotherapy dose (dose-volume and spatial dose metrics) and clinical data. Penalised logistic regression, support vector classification and random forest classification (RFC) models were generated and compared. Internal validation was performed (with 100-iteration cross-validation), using multiple metrics, including area under the receiver operating characteristic curve (AUC) and calibration slope, to assess performance. Associations between covariates and severe mucositis were explored using the models. Results The dose-volume-based models (standard) performed equally to those incorporating spatial information. Discrimination was similar between models, but the RFCstandard had the best calibration. The mean AUC and calibration slope for this model were 0.71 (s.d.=0.09) and 3.9 (s.d.=2.2), respectively. The volumes of oral cavity receiving intermediate and high doses were associated with severe mucositis. Conclusions The RFCstandard model performance is modest-to-good, but should be improved, and requires external validation. Reducing the volumes of oral cavity receiving intermediate and high doses may reduce mucositis incidence. PMID:27240717

  1. Probability, statistics, and computational science.

    PubMed

    Beerenwinkel, Niko; Siebourg, Juliane

    2012-01-01

    In this chapter, we review basic concepts from probability theory and computational statistics that are fundamental to evolutionary genomics. We provide a very basic introduction to statistical modeling and discuss general principles, including maximum likelihood and Bayesian inference. Markov chains, hidden Markov models, and Bayesian network models are introduced in more detail as they occur frequently and in many variations in genomics applications. In particular, we discuss efficient inference algorithms and methods for learning these models from partially observed data. Several simple examples are given throughout the text, some of which point to models that are discussed in more detail in subsequent chapters. PMID:22407706

  2. Estimation of State Transition Probabilities: A Neural Network Model

    NASA Astrophysics Data System (ADS)

    Saito, Hiroshi; Takiyama, Ken; Okada, Masato

    2015-12-01

    Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.

  3. A Comprehensive Probability Project for the Upper Division One-Semester Probability Course Using Yahtzee

    ERIC Educational Resources Information Center

    Wilson, Jason; Lawman, Joshua; Murphy, Rachael; Nelson, Marissa

    2011-01-01

    This article describes a probability project used in an upper division, one-semester probability course with third-semester calculus and linear algebra prerequisites. The student learning outcome focused on developing the skills necessary for approaching project-sized math/stat application problems. These skills include appropriately defining…

  4. Single-case probabilities

    NASA Astrophysics Data System (ADS)

    Miller, David

    1991-12-01

    The propensity interpretation of probability, bred by Popper in 1957 (K. R. Popper, in Observation and Interpretation in the Philosophy of Physics, S. Körner, ed. (Butterworth, London, 1957, and Dover, New York, 1962), p. 65; reprinted in Popper Selections, D. W. Miller, ed. (Princeton University Press, Princeton, 1985), p. 199) from pure frequency stock, is the only extant objectivist account that provides any proper understanding of single-case probabilities as well as of probabilities in ensembles and in the long run. In Sec. 1 of this paper I recall salient points of the frequency interpretations of von Mises and of Popper himself, and in Sec. 2 I filter out from Popper's numerous expositions of the propensity interpretation its most interesting and fertile strain. I then go on to assess it. First I defend it, in Sec. 3, against recent criticisms (P. Humphreys, Philos. Rev. 94, 557 (1985); P. Milne, Erkenntnis 25, 129 (1986)) to the effect that conditional [or relative] probabilities, unlike absolute probabilities, can only rarely be made sense of as propensities. I then challenge its predominance, in Sec. 4, by outlining a rival theory: an irreproachably objectivist theory of probability, fully applicable to the single case, that interprets physical probabilities as instantaneous frequencies.

  5. Probability with Roulette

    ERIC Educational Resources Information Center

    Marshall, Jennings B.

    2007-01-01

    This article describes how roulette can be used to teach basic concepts of probability. Various bets are used to illustrate the computation of expected value. A betting system shows variations in patterns that often appear in random events.

  6. Launch Collision Probability

    NASA Technical Reports Server (NTRS)

    Bollenbacher, Gary; Guptill, James D.

    1999-01-01

    This report analyzes the probability of a launch vehicle colliding with one of the nearly 10,000 tracked objects orbiting the Earth, given that an object on a near-collision course with the launch vehicle has been identified. Knowledge of the probability of collision throughout the launch window can be used to avoid launching at times when the probability of collision is unacceptably high. The analysis in this report assumes that the positions of the orbiting objects and the launch vehicle can be predicted as a function of time and therefore that any tracked object which comes close to the launch vehicle can be identified. The analysis further assumes that the position uncertainty of the launch vehicle and the approaching space object can be described with position covariance matrices. With these and some additional simplifying assumptions, a closed-form solution is developed using two approaches. The solution shows that the probability of collision is a function of position uncertainties, the size of the two potentially colliding objects, and the nominal separation distance at the point of closest approach. ne impact of the simplifying assumptions on the accuracy of the final result is assessed and the application of the results to the Cassini mission, launched in October 1997, is described. Other factors that affect the probability of collision are also discussed. Finally, the report offers alternative approaches that can be used to evaluate the probability of collision.

  7. Experimental Probability in Elementary School

    ERIC Educational Resources Information Center

    Andrew, Lane

    2009-01-01

    Concepts in probability can be more readily understood if students are first exposed to probability via experiment. Performing probability experiments encourages students to develop understandings of probability grounded in real events, as opposed to merely computing answers based on formulae.

  8. Acceptance, values, and probability.

    PubMed

    Steel, Daniel

    2015-10-01

    This essay makes a case for regarding personal probabilities used in Bayesian analyses of confirmation as objects of acceptance and rejection. That in turn entails that personal probabilities are subject to the argument from inductive risk, which aims to show non-epistemic values can legitimately influence scientific decisions about which hypotheses to accept. In a Bayesian context, the argument from inductive risk suggests that value judgments can influence decisions about which probability models to accept for likelihoods and priors. As a consequence, if the argument from inductive risk is sound, then non-epistemic values can affect not only the level of evidence deemed necessary to accept a hypothesis but also degrees of confirmation themselves. PMID:26386533

  9. Probability & Perception: The Representativeness Heuristic in Action

    ERIC Educational Resources Information Center

    Lu, Yun; Vasko, Francis J.; Drummond, Trevor J.; Vasko, Lisa E.

    2014-01-01

    If the prospective students of probability lack a background in mathematical proofs, hands-on classroom activities may work well to help them to learn to analyze problems correctly. For example, students may physically roll a die twice to count and compare the frequency of the sequences. Tools such as graphing calculators or Microsoft Excel®…

  10. Approximating Integrals Using Probability

    ERIC Educational Resources Information Center

    Maruszewski, Richard F., Jr.; Caudle, Kyle A.

    2005-01-01

    As part of a discussion on Monte Carlo methods, which outlines how to use probability expectations to approximate the value of a definite integral. The purpose of this paper is to elaborate on this technique and then to show several examples using visual basic as a programming tool. It is an interesting method because it combines two branches of…

  11. Varga: On Probability.

    ERIC Educational Resources Information Center

    Varga, Tamas

    This booklet resulted from a 1980 visit by the author, a Hungarian mathematics educator, to the Teachers' Center Project at Southern Illinois University at Edwardsville. Included are activities and problems that make probablility concepts accessible to young children. The topics considered are: two probability games; choosing two beads; matching…

  12. Application of Quantum Probability

    NASA Astrophysics Data System (ADS)

    Bohdalová, Mária; Kalina, Martin; Nánásiová, Ol'ga

    2009-03-01

    This is the first attempt to smooth time series using estimators with applying quantum probability with causality (non-commutative s-maps on an othomodular lattice). In this context it means that we use non-symmetric covariance matrix to construction of our estimator.

  13. Univariate Probability Distributions

    ERIC Educational Resources Information Center

    Leemis, Lawrence M.; Luckett, Daniel J.; Powell, Austin G.; Vermeer, Peter E.

    2012-01-01

    We describe a web-based interactive graphic that can be used as a resource in introductory classes in mathematical statistics. This interactive graphic presents 76 common univariate distributions and gives details on (a) various features of the distribution such as the functional form of the probability density function and cumulative distribution…

  14. Waste Package Misload Probability

    SciTech Connect

    J.K. Knudsen

    2001-11-20

    The objective of this calculation is to calculate the probability of occurrence for fuel assembly (FA) misloads (i.e., Fa placed in the wrong location) and FA damage during FA movements. The scope of this calculation is provided by the information obtained from the Framatome ANP 2001a report. The first step in this calculation is to categorize each fuel-handling events that occurred at nuclear power plants. The different categories are based on FAs being damaged or misloaded. The next step is to determine the total number of FAs involved in the event. Using the information, a probability of occurrence will be calculated for FA misload and FA damage events. This calculation is an expansion of preliminary work performed by Framatome ANP 2001a.

  15. Stimulus probability effects in absolute identification.

    PubMed

    Kent, Christopher; Lamberts, Koen

    2016-05-01

    This study investigated the effect of stimulus presentation probability on accuracy and response times in an absolute identification task. Three schedules of presentation were used to investigate the interaction between presentation probability and stimulus position within the set. Data from individual participants indicated strong effects of presentation probability on both proportion correct and response times. The effects were moderated by the ubiquitous stimulus position effect. The accuracy and response time data were predicted by an exemplar-based model of perceptual cognition (Kent & Lamberts, 2005). The bow in discriminability was also attenuated when presentation probability for middle items was relatively high, an effect that will constrain future model development. The study provides evidence for item-specific learning in absolute identification. Implications for other theories of absolute identification are discussed. (PsycINFO Database Record PMID:26478959

  16. Seismicity alert probabilities at Parkfield, California, revisited

    USGS Publications Warehouse

    Michael, A.J.; Jones, L.M.

    1998-01-01

    For a decade, the US Geological Survey has used the Parkfield Earthquake Prediction Experiment scenario document to estimate the probability that earthquakes observed on the San Andreas fault near Parkfield will turn out to be foreshocks followed by the expected magnitude six mainshock. During this time, we have learned much about the seismogenic process at Parkfield, about the long-term probability of the Parkfield mainshock, and about the estimation of these types of probabilities. The probabilities for potential foreshocks at Parkfield are reexamined and revised in light of these advances. As part of this process, we have confirmed both the rate of foreshocks before strike-slip earthquakes in the San Andreas physiographic province and the uniform distribution of foreshocks with magnitude proposed by earlier studies. Compared to the earlier assessment, these new estimates of the long-term probability of the Parkfield mainshock are lower, our estimate of the rate of background seismicity is higher, and we find that the assumption that foreshocks at Parkfield occur in a unique way is not statistically significant at the 95% confidence level. While the exact numbers vary depending on the assumptions that are made, the new alert probabilities are lower than previously estimated. Considering the various assumptions and the statistical uncertainties in the input parameters, we also compute a plausible range for the probabilities. The range is large, partly due to the extra knowledge that exists for the Parkfield segment, making us question the usefulness of these numbers.

  17. Probability mapping of contaminants

    SciTech Connect

    Rautman, C.A.; Kaplan, P.G.; McGraw, M.A.; Istok, J.D.; Sigda, J.M.

    1994-04-01

    Exhaustive characterization of a contaminated site is a physical and practical impossibility. Descriptions of the nature, extent, and level of contamination, as well as decisions regarding proposed remediation activities, must be made in a state of uncertainty based upon limited physical sampling. The probability mapping approach illustrated in this paper appears to offer site operators a reasonable, quantitative methodology for many environmental remediation decisions and allows evaluation of the risk associated with those decisions. For example, output from this approach can be used in quantitative, cost-based decision models for evaluating possible site characterization and/or remediation plans, resulting in selection of the risk-adjusted, least-cost alternative. The methodology is completely general, and the techniques are applicable to a wide variety of environmental restoration projects. The probability-mapping approach is illustrated by application to a contaminated site at the former DOE Feed Materials Production Center near Fernald, Ohio. Soil geochemical data, collected as part of the Uranium-in-Soils Integrated Demonstration Project, have been used to construct a number of geostatistical simulations of potential contamination for parcels approximately the size of a selective remediation unit (the 3-m width of a bulldozer blade). Each such simulation accurately reflects the actual measured sample values, and reproduces the univariate statistics and spatial character of the extant data. Post-processing of a large number of these equally likely statistically similar images produces maps directly showing the probability of exceeding specified levels of contamination (potential clean-up or personnel-hazard thresholds).

  18. Measurement Uncertainty and Probability

    NASA Astrophysics Data System (ADS)

    Willink, Robin

    2013-02-01

    Part I. Principles: 1. Introduction; 2. Foundational ideas in measurement; 3. Components of error or uncertainty; 4. Foundational ideas in probability and statistics; 5. The randomization of systematic errors; 6. Beyond the standard confidence interval; Part II. Evaluation of Uncertainty: 7. Final preparation; 8. Evaluation using the linear approximation; 9. Evaluation without the linear approximations; 10. Uncertainty information fit for purpose; Part III. Related Topics: 11. Measurement of vectors and functions; 12. Why take part in a measurement comparison?; 13. Other philosophies; 14. An assessment of objective Bayesian methods; 15. A guide to the expression of uncertainty in measurement; 16. Measurement near a limit - an insoluble problem?; References; Index.

  19. Emptiness Formation Probability

    NASA Astrophysics Data System (ADS)

    Crawford, Nicholas; Ng, Stephen; Starr, Shannon

    2016-08-01

    We present rigorous upper and lower bounds on the emptiness formation probability for the ground state of a spin-1/2 Heisenberg XXZ quantum spin system. For a d-dimensional system we find a rate of decay of the order {exp(-c L^{d+1})} where L is the sidelength of the box in which we ask for the emptiness formation event to occur. In the {d=1} case this confirms previous predictions made in the integrable systems community, though our bounds do not achieve the precision predicted by Bethe ansatz calculations. On the other hand, our bounds in the case {d ≥ 2} are new. The main tools we use are reflection positivity and a rigorous path integral expansion, which is a variation on those previously introduced by Toth, Aizenman-Nachtergaele and Ueltschi.

  20. Familiarity and preference for pitch probability profiles.

    PubMed

    Cui, Anja-Xiaoxing; Collett, Meghan J; Troje, Niko F; Cuddy, Lola L

    2015-05-01

    We investigated familiarity and preference judgments of participants toward a novel musical system. We exposed participants to tone sequences generated from a novel pitch probability profile. Afterward, we either asked participants to identify more familiar or we asked participants to identify preferred tone sequences in a two-alternative forced-choice task. The task paired a tone sequence generated from the pitch probability profile they had been exposed to and a tone sequence generated from another pitch probability profile at three levels of distinctiveness. We found that participants identified tone sequences as more familiar if they were generated from the same pitch probability profile which they had been exposed to. However, participants did not prefer these tone sequences. We interpret this relationship between familiarity and preference to be consistent with an inverted U-shaped relationship between knowledge and affect. The fact that participants identified tone sequences as even more familiar if they were generated from the more distinctive (caricatured) version of the pitch probability profile which they had been exposed to suggests that the statistical learning of the pitch probability profile is involved in gaining of musical knowledge. PMID:25838257

  1. Pointwise probability reinforcements for robust statistical inference.

    PubMed

    Frénay, Benoît; Verleysen, Michel

    2014-02-01

    Statistical inference using machine learning techniques may be difficult with small datasets because of abnormally frequent data (AFDs). AFDs are observations that are much more frequent in the training sample that they should be, with respect to their theoretical probability, and include e.g. outliers. Estimates of parameters tend to be biased towards models which support such data. This paper proposes to introduce pointwise probability reinforcements (PPRs): the probability of each observation is reinforced by a PPR and a regularisation allows controlling the amount of reinforcement which compensates for AFDs. The proposed solution is very generic, since it can be used to robustify any statistical inference method which can be formulated as a likelihood maximisation. Experiments show that PPRs can be easily used to tackle regression, classification and projection: models are freed from the influence of outliers. Moreover, outliers can be filtered manually since an abnormality degree is obtained for each observation. PMID:24300550

  2. A "Virtual Spin" on the Teaching of Probability

    ERIC Educational Resources Information Center

    Beck, Shari A.; Huse, Vanessa E.

    2007-01-01

    This article, which describes integrating virtual manipulatives with the teaching of probability at the elementary level, puts a "virtual spin" on the teaching of probability to provide more opportunities for students to experience successful learning. The traditional use of concrete manipulatives is enhanced with virtual coins and spinners from…

  3. Visualizing and Understanding Probability and Statistics: Graphical Simulations Using Excel

    ERIC Educational Resources Information Center

    Gordon, Sheldon P.; Gordon, Florence S.

    2009-01-01

    The authors describe a collection of dynamic interactive simulations for teaching and learning most of the important ideas and techniques of introductory statistics and probability. The modules cover such topics as randomness, simulations of probability experiments such as coin flipping, dice rolling and general binomial experiments, a simulation…

  4. A Tale of Two Probabilities

    ERIC Educational Resources Information Center

    Falk, Ruma; Kendig, Keith

    2013-01-01

    Two contestants debate the notorious probability problem of the sex of the second child. The conclusions boil down to explication of the underlying scenarios and assumptions. Basic principles of probability theory are highlighted.

  5. Laboratory-tutorial activities for teaching probability

    NASA Astrophysics Data System (ADS)

    Wittmann, Michael C.; Morgan, Jeffrey T.; Feeley, Roger E.

    2006-12-01

    We report on the development of students’ ideas of probability and probability density in a University of Maine laboratory-based general education physics course called Intuitive Quantum Physics. Students in the course are generally math phobic with unfavorable expectations about the nature of physics and their ability to do it. We describe a set of activities used to teach concepts of probability and probability density. Rudimentary knowledge of mechanics is needed for one activity, but otherwise the material requires no additional preparation. Extensions of the activities include relating probability density to potential energy graphs for certain “touchstone” examples. Students have difficulties learning the target concepts, such as comparing the ratio of time in a region to total time in all regions. Instead, they often focus on edge effects, pattern match to previously studied situations, reason about necessary but incomplete macroscopic elements of the system, use the gambler’s fallacy, and use expectations about ensemble results rather than expectation values to predict future events. We map the development of their thinking to provide examples of problems rather than evidence of a curriculum’s success.

  6. The Probability of Causal Conditionals

    ERIC Educational Resources Information Center

    Over, David E.; Hadjichristidis, Constantinos; Evans, Jonathan St. B. T.; Handley, Simon J.; Sloman, Steven A.

    2007-01-01

    Conditionals in natural language are central to reasoning and decision making. A theoretical proposal called the Ramsey test implies the conditional probability hypothesis: that the subjective probability of a natural language conditional, P(if p then q), is the conditional subjective probability, P(q [such that] p). We report three experiments on…

  7. Quantum probability and many worlds

    NASA Astrophysics Data System (ADS)

    Hemmo, Meir; Pitowsky, Itamar

    We discuss the meaning of probabilities in the many worlds interpretation of quantum mechanics. We start by presenting very briefly the many worlds theory, how the problem of probability arises, and some unsuccessful attempts to solve it in the past. Then we criticize a recent attempt by Deutsch to derive the quantum mechanical probabilities from the non-probabilistic parts of quantum mechanics and classical decision theory. We further argue that the Born probability does not make sense even as an additional probability rule in the many worlds theory. Our conclusion is that the many worlds theory fails to account for the probabilistic statements of standard (collapse) quantum mechanics.

  8. Unders and Overs: Using a Dice Game to Illustrate Basic Probability Concepts

    ERIC Educational Resources Information Center

    McPherson, Sandra Hanson

    2015-01-01

    In this paper, the dice game "Unders and Overs" is described and presented as an active learning exercise to introduce basic probability concepts. The implementation of the exercise is outlined and the resulting presentation of various probability concepts are described.

  9. Propensity, Probability, and Quantum Theory

    NASA Astrophysics Data System (ADS)

    Ballentine, Leslie E.

    2016-08-01

    Quantum mechanics and probability theory share one peculiarity. Both have well established mathematical formalisms, yet both are subject to controversy about the meaning and interpretation of their basic concepts. Since probability plays a fundamental role in QM, the conceptual problems of one theory can affect the other. We first classify the interpretations of probability into three major classes: (a) inferential probability, (b) ensemble probability, and (c) propensity. Class (a) is the basis of inductive logic; (b) deals with the frequencies of events in repeatable experiments; (c) describes a form of causality that is weaker than determinism. An important, but neglected, paper by P. Humphreys demonstrated that propensity must differ mathematically, as well as conceptually, from probability, but he did not develop a theory of propensity. Such a theory is developed in this paper. Propensity theory shares many, but not all, of the axioms of probability theory. As a consequence, propensity supports the Law of Large Numbers from probability theory, but does not support Bayes theorem. Although there are particular problems within QM to which any of the classes of probability may be applied, it is argued that the intrinsic quantum probabilities (calculated from a state vector or density matrix) are most naturally interpreted as quantum propensities. This does not alter the familiar statistical interpretation of QM. But the interpretation of quantum states as representing knowledge is untenable. Examples show that a density matrix fails to represent knowledge.

  10. Probability Surveys, Conditional Probability, and Ecological Risk Assessment

    EPA Science Inventory

    We show that probability-based environmental resource monitoring programs, such as the U.S. Environmental Protection Agency’s (U.S. EPA) Environmental Monitoring and Assessment Program, and conditional probability analysis can serve as a basis for estimating ecological risk over ...

  11. PROBABILITY SURVEYS, CONDITIONAL PROBABILITIES, AND ECOLOGICAL RISK ASSESSMENT

    EPA Science Inventory

    We show that probability-based environmental resource monitoring programs, such as U.S. Environmental Protection Agency's (U.S. EPA) Environmental Monitoring and Asscssment Program EMAP) can be analyzed with a conditional probability analysis (CPA) to conduct quantitative probabi...

  12. The relationship between species detection probability and local extinction probability

    USGS Publications Warehouse

    Alpizar-Jara, R.; Nichols, J.D.; Hines, J.E.; Sauer, J.R.; Pollock, K.H.; Rosenberry, C.S.

    2004-01-01

    In community-level ecological studies, generally not all species present in sampled areas are detected. Many authors have proposed the use of estimation methods that allow detection probabilities that are <1 and that are heterogeneous among species. These methods can also be used to estimate community-dynamic parameters such as species local extinction probability and turnover rates (Nichols et al. Ecol Appl 8:1213-1225; Conserv Biol 12:1390-1398). Here, we present an ad hoc approach to estimating community-level vital rates in the presence of joint heterogeneity of detection probabilities and vital rates. The method consists of partitioning the number of species into two groups using the detection frequencies and then estimating vital rates (e.g., local extinction probabilities) for each group. Estimators from each group are combined in a weighted estimator of vital rates that accounts for the effect of heterogeneity. Using data from the North American Breeding Bird Survey, we computed such estimates and tested the hypothesis that detection probabilities and local extinction probabilities were negatively related. Our analyses support the hypothesis that species detection probability covaries negatively with local probability of extinction and turnover rates. A simulation study was conducted to assess the performance of vital parameter estimators as well as other estimators relevant to questions about heterogeneity, such as coefficient of variation of detection probabilities and proportion of species in each group. Both the weighted estimator suggested in this paper and the original unweighted estimator for local extinction probability performed fairly well and provided no basis for preferring one to the other.

  13. Updating: Learning versus Supposing

    ERIC Educational Resources Information Center

    Zhao, Jiaying; Crupi, Vincenzo; Tentori, Katya; Fitelson, Branden; Osherson, Daniel

    2012-01-01

    Bayesian orthodoxy posits a tight relationship between conditional probability and updating. Namely, the probability of an event "A" after learning "B" should equal the conditional probability of "A" given "B" prior to learning "B". We examine whether ordinary judgment conforms to the orthodox view. In three experiments we found substantial…

  14. The Probabilities of Conditionals Revisited

    ERIC Educational Resources Information Center

    Douven, Igor; Verbrugge, Sara

    2013-01-01

    According to what is now commonly referred to as "the Equation" in the literature on indicative conditionals, the probability of any indicative conditional equals the probability of its consequent of the conditional given the antecedent of the conditional. Philosophers widely agree in their assessment that the triviality arguments of…

  15. Minimizing the probable maximum flood

    SciTech Connect

    Woodbury, M.S.; Pansic, N. ); Eberlein, D.T. )

    1994-06-01

    This article examines Wisconsin Electric Power Company's efforts to determine an economical way to comply with Federal Energy Regulatory Commission requirements at two hydroelectric developments on the Michigamme River. Their efforts included refinement of the area's probable maximum flood model based, in part, on a newly developed probable maximum precipitation estimate.

  16. Computation of Most Probable Numbers

    PubMed Central

    Russek, Estelle; Colwell, Rita R.

    1983-01-01

    A rapid computational method for maximum likelihood estimation of most-probable-number values, incorporating a modified Newton-Raphson method, is presented. The method offers a much greater reliability for the most-probable-number estimate of total viable bacteria, i.e., those capable of growth in laboratory media. PMID:6870242

  17. Probability of sea level rise

    SciTech Connect

    Titus, J.G.; Narayanan, V.K.

    1995-10-01

    The report develops probability-based projections that can be added to local tide-gage trends to estimate future sea level at particular locations. It uses the same models employed by previous assessments of sea level rise. The key coefficients in those models are based on subjective probability distributions supplied by a cross-section of climatologists, oceanographers, and glaciologists.

  18. Decision analysis with approximate probabilities

    NASA Technical Reports Server (NTRS)

    Whalen, Thomas

    1992-01-01

    This paper concerns decisions under uncertainty in which the probabilities of the states of nature are only approximately known. Decision problems involving three states of nature are studied. This is due to the fact that some key issues do not arise in two-state problems, while probability spaces with more than three states of nature are essentially impossible to graph. The primary focus is on two levels of probabilistic information. In one level, the three probabilities are separately rounded to the nearest tenth. This can lead to sets of rounded probabilities which add up to 0.9, 1.0, or 1.1. In the other level, probabilities are rounded to the nearest tenth in such a way that the rounded probabilities are forced to sum to 1.0. For comparison, six additional levels of probabilistic information, previously analyzed, were also included in the present analysis. A simulation experiment compared four criteria for decisionmaking using linearly constrained probabilities (Maximin, Midpoint, Standard Laplace, and Extended Laplace) under the eight different levels of information about probability. The Extended Laplace criterion, which uses a second order maximum entropy principle, performed best overall.

  19. VESPA: False positive probabilities calculator

    NASA Astrophysics Data System (ADS)

    Morton, Timothy D.

    2015-03-01

    Validation of Exoplanet Signals using a Probabilistic Algorithm (VESPA) calculates false positive probabilities and statistically validates transiting exoplanets. Written in Python, it uses isochrones [ascl:1503.010] and the package simpledist.

  20. Dinosaurs, Dinosaur Eggs, and Probability.

    ERIC Educational Resources Information Center

    Teppo, Anne R.; Hodgson, Ted

    2001-01-01

    Outlines several recommendations for teaching probability in the secondary school. Offers an activity that employs simulation by hand and using a programmable calculator in which geometry, analytical geometry, and discrete mathematics are explored. (KHR)

  1. The probabilities of unique events.

    PubMed

    Khemlani, Sangeet S; Lotstein, Max; Johnson-Laird, Phil

    2012-01-01

    Many theorists argue that the probabilities of unique events, even real possibilities such as President Obama's re-election, are meaningless. As a consequence, psychologists have seldom investigated them. We propose a new theory (implemented in a computer program) in which such estimates depend on an intuitive non-numerical system capable only of simple procedures, and a deliberative system that maps intuitions into numbers. The theory predicts that estimates of the probabilities of conjunctions should often tend to split the difference between the probabilities of the two conjuncts. We report two experiments showing that individuals commit such violations of the probability calculus, and corroborating other predictions of the theory, e.g., individuals err in the same way even when they make non-numerical verbal estimates, such as that an event is highly improbable. PMID:23056224

  2. The Probabilities of Unique Events

    PubMed Central

    Khemlani, Sangeet S.; Lotstein, Max; Johnson-Laird, Phil

    2012-01-01

    Many theorists argue that the probabilities of unique events, even real possibilities such as President Obama's re-election, are meaningless. As a consequence, psychologists have seldom investigated them. We propose a new theory (implemented in a computer program) in which such estimates depend on an intuitive non-numerical system capable only of simple procedures, and a deliberative system that maps intuitions into numbers. The theory predicts that estimates of the probabilities of conjunctions should often tend to split the difference between the probabilities of the two conjuncts. We report two experiments showing that individuals commit such violations of the probability calculus, and corroborating other predictions of the theory, e.g., individuals err in the same way even when they make non-numerical verbal estimates, such as that an event is highly improbable. PMID:23056224

  3. Transition probabilities of Br II

    NASA Technical Reports Server (NTRS)

    Bengtson, R. D.; Miller, M. H.

    1976-01-01

    Absolute transition probabilities of the three most prominent visible Br II lines are measured in emission. Results compare well with Coulomb approximations and with line strengths extrapolated from trends in homologous atoms.

  4. A Quantum Probability Model of Causal Reasoning

    PubMed Central

    Trueblood, Jennifer S.; Busemeyer, Jerome R.

    2012-01-01

    People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause) with diagnostic judgments (i.e., the conditional probability of a cause given an effect). The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment. PMID:22593747

  5. Joint probabilities and quantum cognition

    SciTech Connect

    Acacio de Barros, J.

    2012-12-18

    In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

  6. Evaluation of microbial release probabilities

    NASA Technical Reports Server (NTRS)

    1972-01-01

    Work undertaken to improve the estimation of the probability of release of microorganisms from unmanned Martian landing spacecraft is summarized. An analytical model is described for the development of numerical values for release parameters and release mechanisms applicable to flight missions are defined. Laboratory test data are used to evolve parameter values for use by flight projects in estimating numerical values for release probabilities. The analysis treats microbial burden located on spacecraft surfaces, between mated surfaces, and encapsulated within materials.

  7. Joint probabilities and quantum cognition

    NASA Astrophysics Data System (ADS)

    de Barros, J. Acacio

    2012-12-01

    In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

  8. Joint probability distributions for projection probabilities of random orthonormal states

    NASA Astrophysics Data System (ADS)

    Alonso, L.; Gorin, T.

    2016-04-01

    The quantum chaos conjecture applied to a finite dimensional quantum system implies that such a system has eigenstates that show similar statistical properties as the column vectors of random orthogonal or unitary matrices. Here, we consider the different probabilities for obtaining a specific outcome in a projective measurement, provided the system is in one of its eigenstates. We then give analytic expressions for the joint probability density for these probabilities, with respect to the ensemble of random matrices. In the case of the unitary group, our results can be applied, also, to the phenomenon of universal conductance fluctuations, where the same mathematical quantities describe partial conductances in a two-terminal mesoscopic scattering problem with a finite number of modes in each terminal.

  9. Can Personality Type Explain Heterogeneity in Probability Distortions?

    PubMed Central

    Capra, C. Monica; Jiang, Bing; Engelmann, Jan B.; Berns, Gregory S.

    2014-01-01

    There are two regularities we have learned from experimental studies of choice under risk. The first is that the majority of people weigh objective probabilities non-linearly. The second regularity, although less commonly acknowledged, is that there is a large amount of heterogeneity in how people distort probabilities. Despite of this, little effort has been made to identify the source of heterogeneity. In this paper, we explore the possibility that personality type is linked to probability distortions. Using validated psychological questionnaires, we clustered participants into distinct personality types: motivated, impulsive, and affective. We found that the motivated viewed gambling more attractive, whereas the impulsive were the most capable of discriminating non-extreme probabilities. Our results suggest that the observed heterogeneity in probability distortions may be explained by personality profiles, which can be elicited though standard psychological questionnaires. PMID:24639891

  10. Imprecise probabilities in engineering analyses

    NASA Astrophysics Data System (ADS)

    Beer, Michael; Ferson, Scott; Kreinovich, Vladik

    2013-05-01

    Probabilistic uncertainty and imprecision in structural parameters and in environmental conditions and loads are challenging phenomena in engineering analyses. They require appropriate mathematical modeling and quantification to obtain realistic results when predicting the behavior and reliability of engineering structures and systems. But the modeling and quantification is complicated by the characteristics of the available information, which involves, for example, sparse data, poor measurements and subjective information. This raises the question whether the available information is sufficient for probabilistic modeling or rather suggests a set-theoretical approach. The framework of imprecise probabilities provides a mathematical basis to deal with these problems which involve both probabilistic and non-probabilistic information. A common feature of the various concepts of imprecise probabilities is the consideration of an entire set of probabilistic models in one analysis. The theoretical differences between the concepts mainly concern the mathematical description of the set of probabilistic models and the connection to the probabilistic models involved. This paper provides an overview on developments which involve imprecise probabilities for the solution of engineering problems. Evidence theory, probability bounds analysis with p-boxes, and fuzzy probabilities are discussed with emphasis on their key features and on their relationships to one another. This paper was especially prepared for this special issue and reflects, in various ways, the thinking and presentation preferences of the authors, who are also the guest editors for this special issue.

  11. Measure and probability in cosmology

    NASA Astrophysics Data System (ADS)

    Schiffrin, Joshua S.; Wald, Robert M.

    2012-07-01

    General relativity has a Hamiltonian formulation, which formally provides a canonical (Liouville) measure on the space of solutions. In ordinary statistical physics, the Liouville measure is used to compute probabilities of macrostates, and it would seem natural to use the similar measure arising in general relativity to compute probabilities in cosmology, such as the probability that the Universe underwent an era of inflation. Indeed, a number of authors have used the restriction of this measure to the space of homogeneous and isotropic universes with scalar field matter (minisuperspace)—namely, the Gibbons-Hawking-Stewart measure—to make arguments about the likelihood of inflation. We argue here that there are at least four major difficulties with using the measure of general relativity to make probability arguments in cosmology: (1) Equilibration does not occur on cosmological length scales. (2) Even in the minisuperspace case, the measure of phase space is infinite and the computation of probabilities depends very strongly on how the infinity is regulated. (3) The inhomogeneous degrees of freedom must be taken into account (we illustrate how) even if one is interested only in universes that are very nearly homogeneous. The measure depends upon how the infinite number of degrees of freedom are truncated, and how one defines “nearly homogeneous.” (4) In a Universe where the second law of thermodynamics holds, one cannot make use of our knowledge of the present state of the Universe to retrodict the likelihood of past conditions.

  12. Flood hazard probability mapping method

    NASA Astrophysics Data System (ADS)

    Kalantari, Zahra; Lyon, Steve; Folkeson, Lennart

    2015-04-01

    In Sweden, spatially explicit approaches have been applied in various disciplines such as landslide modelling based on soil type data and flood risk modelling for large rivers. Regarding flood mapping, most previous studies have focused on complex hydrological modelling on a small scale whereas just a few studies have used a robust GIS-based approach integrating most physical catchment descriptor (PCD) aspects on a larger scale. The aim of the present study was to develop methodology for predicting the spatial probability of flooding on a general large scale. Factors such as topography, land use, soil data and other PCDs were analysed in terms of their relative importance for flood generation. The specific objective was to test the methodology using statistical methods to identify factors having a significant role on controlling flooding. A second objective was to generate an index quantifying flood probability value for each cell, based on different weighted factors, in order to provide a more accurate analysis of potential high flood hazards than can be obtained using just a single variable. The ability of indicator covariance to capture flooding probability was determined for different watersheds in central Sweden. Using data from this initial investigation, a method to subtract spatial data for multiple catchments and to produce soft data for statistical analysis was developed. It allowed flood probability to be predicted from spatially sparse data without compromising the significant hydrological features on the landscape. By using PCD data, realistic representations of high probability flood regions was made, despite the magnitude of rain events. This in turn allowed objective quantification of the probability of floods at the field scale for future model development and watershed management.

  13. Knowledge typology for imprecise probabilities.

    SciTech Connect

    Wilson, G. D.; Zucker, L. J.

    2002-01-01

    When characterizing the reliability of a complex system there are often gaps in the data available for specific subsystems or other factors influencing total system reliability. At Los Alamos National Laboratory we employ ethnographic methods to elicit expert knowledge when traditional data is scarce. Typically, we elicit expert knowledge in probabilistic terms. This paper will explore how we might approach elicitation if methods other than probability (i.e., Dempster-Shafer, or fuzzy sets) prove more useful for quantifying certain types of expert knowledge. Specifically, we will consider if experts have different types of knowledge that may be better characterized in ways other than standard probability theory.

  14. Probability as a Physical Motive

    NASA Astrophysics Data System (ADS)

    Martin, Peter

    2007-06-01

    Recent theoretical progress in nonequilibrium thermodynamics, linking thephysical principle of Maximum Entropy Production (“MEP”) to the information-theoretical“MaxEnt” principle of scientific inference, together with conjectures from theoreticalphysics that there may be no fundamental causal laws but only probabilities for physicalprocesses, and from evolutionary theory that biological systems expand “the adjacentpossible” as rapidly as possible, all lend credence to the proposition that probability shouldbe recognized as a fundamental physical motive. It is further proposed that spatial order andtemporal order are two aspects of the same thing, and that this is the essence of the secondlaw of thermodynamics.

  15. Interference of probabilities in dynamics

    SciTech Connect

    Zak, Michail

    2014-08-15

    A new class of dynamical systems with a preset type of interference of probabilities is introduced. It is obtained from the extension of the Madelung equation by replacing the quantum potential with a specially selected feedback from the Liouville equation. It has been proved that these systems are different from both Newtonian and quantum systems, but they can be useful for modeling spontaneous collective novelty phenomena when emerging outputs are qualitatively different from the weighted sum of individual inputs. Formation of language and fast decision-making process as potential applications of the probability interference is discussed.

  16. Teaching Probability with the Support of the R Statistical Software

    ERIC Educational Resources Information Center

    dos Santos Ferreira, Robson; Kataoka, Verônica Yumi; Karrer, Monica

    2014-01-01

    The objective of this paper is to discuss aspects of high school students' learning of probability in a context where they are supported by the statistical software R. We report on the application of a teaching experiment, constructed using the perspective of Gal's probabilistic literacy and Papert's constructionism. The results…

  17. Genetics as a Context for the Study of Probability.

    ERIC Educational Resources Information Center

    Brahier, Daniel J.

    1999-01-01

    Presents an activity in which students develop a handy strategy for exploring probability as applied in the life sciences by learning to use the Punnett square, an effective tool that helps students visualize sample spaces and determine the likelihood of events. (ASK)

  18. Probability Simulation in Middle School.

    ERIC Educational Resources Information Center

    Lappan, Glenda; Winter, M. J.

    1980-01-01

    Two simulations designed to teach probability to middle-school age pupils are presented. The first simulates the one-on-one foul shot simulation in basketball; the second deals with collecting a set of six cereal box prizes by buying boxes containing one toy each. (MP)

  19. Some Surprising Probabilities from Bingo.

    ERIC Educational Resources Information Center

    Mercer, Joseph O.

    1993-01-01

    Investigates the probability of winning the largest prize at Bingo through a series of five simpler problems. Investigations are conducted with the aid of either BASIC computer programs, spreadsheets, or a computer algebra system such as Mathematica. Provides sample data tables to illustrate findings. (MDH)

  20. GPS: Geometry, Probability, and Statistics

    ERIC Educational Resources Information Center

    Field, Mike

    2012-01-01

    It might be said that for most occupations there is now less of a need for mathematics than there was say fifty years ago. But, the author argues, geometry, probability, and statistics constitute essential knowledge for everyone. Maybe not the geometry of Euclid, but certainly geometrical ways of thinking that might enable us to describe the world…

  1. Conditional Independence in Applied Probability.

    ERIC Educational Resources Information Center

    Pfeiffer, Paul E.

    This material assumes the user has the background provided by a good undergraduate course in applied probability. It is felt that introductory courses in calculus, linear algebra, and perhaps some differential equations should provide the requisite experience and proficiency with mathematical concepts, notation, and argument. The document is…

  2. Stretching Probability Explorations with Geoboards

    ERIC Educational Resources Information Center

    Wheeler, Ann; Champion, Joe

    2016-01-01

    Students are faced with many transitions in their middle school mathematics classes. To build knowledge, skills, and confidence in the key areas of algebra and geometry, students often need to practice using numbers and polygons in a variety of contexts. Teachers also want students to explore ideas from probability and statistics. Teachers know…

  3. ESTIMATION OF AGE TRANSITION PROBABILITIES.

    ERIC Educational Resources Information Center

    ZINTER, JUDITH R.

    THIS NOTE DESCRIBES THE PROCEDURES USED IN DETERMINING DYNAMOD II AGE TRANSITION MATRICES. A SEPARATE MATRIX FOR EACH SEX-RACE GROUP IS DEVELOPED. THESE MATRICES WILL BE USED AS AN AID IN ESTIMATING THE TRANSITION PROBABILITIES IN THE LARGER DYNAMOD II MATRIX RELATING AGE TO OCCUPATIONAL CATEGORIES. THREE STEPS WERE USED IN THE PROCEDURE--(1)…

  4. Dynamic SEP event probability forecasts

    NASA Astrophysics Data System (ADS)

    Kahler, S. W.; Ling, A.

    2015-10-01

    The forecasting of solar energetic particle (SEP) event probabilities at Earth has been based primarily on the estimates of magnetic free energy in active regions and on the observations of peak fluxes and fluences of large (≥ M2) solar X-ray flares. These forecasts are typically issued for the next 24 h or with no definite expiration time, which can be deficient for time-critical operations when no SEP event appears following a large X-ray flare. It is therefore important to decrease the event probability forecast with time as a SEP event fails to appear. We use the NOAA listing of major (≥10 pfu) SEP events from 1976 to 2014 to plot the delay times from X-ray peaks to SEP threshold onsets as a function of solar source longitude. An algorithm is derived to decrease the SEP event probabilities with time when no event is observed to reach the 10 pfu threshold. In addition, we use known SEP event size distributions to modify probability forecasts when SEP intensity increases occur below the 10 pfu event threshold. An algorithm to provide a dynamic SEP event forecast, Pd, for both situations of SEP intensities following a large flare is derived.

  5. Probability, Information and Statistical Physics

    NASA Astrophysics Data System (ADS)

    Kuzemsky, A. L.

    2016-03-01

    In this short survey review we discuss foundational issues of the probabilistic approach to information theory and statistical mechanics from a unified standpoint. Emphasis is on the inter-relations between theories. The basic aim is tutorial, i.e. to carry out a basic introduction to the analysis and applications of probabilistic concepts to the description of various aspects of complexity and stochasticity. We consider probability as a foundational concept in statistical mechanics and review selected advances in the theoretical understanding of interrelation of the probability, information and statistical description with regard to basic notions of statistical mechanics of complex systems. It includes also a synthesis of past and present researches and a survey of methodology. The purpose of this terse overview is to discuss and partially describe those probabilistic methods and approaches that are used in statistical mechanics with the purpose of making these ideas easier to understanding and to apply.

  6. Probability densities in strong turbulence

    NASA Astrophysics Data System (ADS)

    Yakhot, Victor

    2006-03-01

    In this work we, using Mellin’s transform combined with the Gaussian large-scale boundary condition, calculate probability densities (PDFs) of velocity increments P(δu,r), velocity derivatives P(u,r) and the PDF of the fluctuating dissipation scales Q(η,Re), where Re is the large-scale Reynolds number. The resulting expressions strongly deviate from the Log-normal PDF P(δu,r) often quoted in the literature. It is shown that the probability density of the small-scale velocity fluctuations includes information about the large (integral) scale dynamics which is responsible for the deviation of P(δu,r) from P(δu,r). An expression for the function D(h) of the multifractal theory, free from spurious logarithms recently discussed in [U. Frisch, M. Martins Afonso, A. Mazzino, V. Yakhot, J. Fluid Mech. 542 (2005) 97] is also obtained.

  7. Probability for primordial black holes

    NASA Astrophysics Data System (ADS)

    Bousso, R.; Hawking, S. W.

    1995-11-01

    We consider two quantum cosmological models with a massive scalar field: an ordinary Friedmann universe and a universe containing primordial black holes. For both models we discuss the complex solutions to the Euclidean Einstein equations. Using the probability measure obtained from the Hartle-Hawking no-boundary proposal we find that the only unsuppressed black holes start at the Planck size but can grow with the horizon scale during the roll down of the scalar field to the minimum.

  8. Relative transition probabilities of cobalt

    NASA Technical Reports Server (NTRS)

    Roig, R. A.; Miller, M. H.

    1974-01-01

    Results of determinations of neutral-cobalt transition probabilities measured relative to Co I 4150.43 A and Co II 4145.15 A, using a gas-driven shock tube as the spectroscopic light source. Results are presented for 139 Co I lines in the range from 3940 to 6640 A and 11 Co II lines in the range from 3840 to 4730 A, which are estimated to have reliabilities ranging from 8 to 50%.

  9. A Lakatosian Encounter with Probability

    ERIC Educational Resources Information Center

    Chick, Helen

    2010-01-01

    There is much to be learned and pondered by reading "Proofs and Refutations" by Imre Lakatos (Lakatos, 1976). It highlights the importance of mathematical definitions, and how definitions evolve to capture the essence of the object they are defining. It also provides an exhilarating encounter with the ups and downs of the mathematical reasoning…

  10. Probability for Weather and Climate

    NASA Astrophysics Data System (ADS)

    Smith, L. A.

    2013-12-01

    Over the last 60 years, the availability of large-scale electronic computers has stimulated rapid and significant advances both in meteorology and in our understanding of the Earth System as a whole. The speed of these advances was due, in large part, to the sudden ability to explore nonlinear systems of equations. The computer allows the meteorologist to carry a physical argument to its conclusion; the time scales of weather phenomena then allow the refinement of physical theory, numerical approximation or both in light of new observations. Prior to this extension, as Charney noted, the practicing meteorologist could ignore the results of theory with good conscience. Today, neither the practicing meteorologist nor the practicing climatologist can do so, but to what extent, and in what contexts, should they place the insights of theory above quantitative simulation? And in what circumstances can one confidently estimate the probability of events in the world from model-based simulations? Despite solid advances of theory and insight made possible by the computer, the fidelity of our models of climate differs in kind from the fidelity of models of weather. While all prediction is extrapolation in time, weather resembles interpolation in state space, while climate change is fundamentally an extrapolation. The trichotomy of simulation, observation and theory which has proven essential in meteorology will remain incomplete in climate science. Operationally, the roles of probability, indeed the kinds of probability one has access too, are different in operational weather forecasting and climate services. Significant barriers to forming probability forecasts (which can be used rationally as probabilities) are identified. Monte Carlo ensembles can explore sensitivity, diversity, and (sometimes) the likely impact of measurement uncertainty and structural model error. The aims of different ensemble strategies, and fundamental differences in ensemble design to support of

  11. Probability of Detection Demonstration Transferability

    NASA Technical Reports Server (NTRS)

    Parker, Bradford H.

    2008-01-01

    The ongoing Mars Science Laboratory (MSL) Propellant Tank Penetrant Nondestructive Evaluation (NDE) Probability of Detection (POD) Assessment (NESC activity) has surfaced several issues associated with liquid penetrant POD demonstration testing. This presentation lists factors that may influence the transferability of POD demonstration tests. Initial testing will address the liquid penetrant inspection technique. Some of the factors to be considered in this task are crack aspect ratio, the extent of the crack opening, the material and the distance between the inspection surface and the inspector's eye.

  12. Lectures on probability and statistics

    SciTech Connect

    Yost, G.P.

    1984-09-01

    These notes are based on a set of statistics lectures delivered at Imperial College to the first-year postgraduate students in High Energy Physics. They are designed for the professional experimental scientist. We begin with the fundamentals of probability theory, in which one makes statements about the set of possible outcomes of an experiment, based upon a complete a priori understanding of the experiment. For example, in a roll of a set of (fair) dice, one understands a priori that any given side of each die is equally likely to turn up. From that, we can calculate the probability of any specified outcome. We finish with the inverse problem, statistics. Here, one begins with a set of actual data (e.g., the outcomes of a number of rolls of the dice), and attempts to make inferences about the state of nature which gave those data (e.g., the likelihood of seeing any given side of any given die turn up). This is a much more difficult problem, of course, and one's solutions often turn out to be unsatisfactory in one respect or another.

  13. Measure and Probability in Cosmology

    NASA Astrophysics Data System (ADS)

    Schiffrin, Joshua; Wald, Robert

    2012-03-01

    General relativity has a Hamiltonian formulation, which formally provides a canonical (Liouville) measure on the space of solutions. A number of authors have used the restriction of this measure to the space of homogeneous and isotropic universes with scalar field matter (minisuperspace)---namely, the Gibbons-Hawking-Stewart measure---to make arguments about the likelihood of inflation. We argue here that there are at least four major difficulties with using the measure of general relativity to make probability arguments in cosmology: (1) Equilibration does not occur on cosmological length scales. (2) Even in the minisuperspace case, the measure of phase space is infinite and the computation of probabilities depends very strongly on how the infinity is regulated. (3) The inhomogeneous degrees of freedom must be taken into account even if one is interested only in universes that are very nearly homogeneous. The measure depends upon how the infinite number of degrees of freedom are truncated, and how one defines ``nearly homogeneous''. (4) In a universe where the second law of thermodynamics holds, one cannot make use of our knowledge of the present state of the universe to ``retrodict'' the likelihood of past conditions.

  14. MSPI False Indication Probability Simulations

    SciTech Connect

    Dana Kelly; Kurt Vedros; Robert Youngblood

    2011-03-01

    This paper examines false indication probabilities in the context of the Mitigating System Performance Index (MSPI), in order to investigate the pros and cons of different approaches to resolving two coupled issues: (1) sensitivity to the prior distribution used in calculating the Bayesian-corrected unreliability contribution to the MSPI, and (2) whether (in a particular plant configuration) to model the fuel oil transfer pump (FOTP) as a separate component, or integrally to its emergency diesel generator (EDG). False indication probabilities were calculated for the following situations: (1) all component reliability parameters at their baseline values, so that the true indication is green, meaning that an indication of white or above would be false positive; (2) one or more components degraded to the extent that the true indication would be (mid) white, and “false” would be green (negative) or yellow (negative) or red (negative). In key respects, this was the approach taken in NUREG-1753. The prior distributions examined were the constrained noninformative (CNI) prior used currently by the MSPI, a mixture of conjugate priors, the Jeffreys noninformative prior, a nonconjugate log(istic)-normal prior, and the minimally informative prior investigated in (Kelly et al., 2010). The mid-white performance state was set at ?CDF = ?10 ? 10-6/yr. For each simulated time history, a check is made of whether the calculated ?CDF is above or below 10-6/yr. If the parameters were at their baseline values, and ?CDF > 10-6/yr, this is counted as a false positive. Conversely, if one or all of the parameters are set to values corresponding to ?CDF > 10-6/yr but that time history’s ?CDF < 10-6/yr, this is counted as a false negative indication. The false indication (positive or negative) probability is then estimated as the number of false positive or negative counts divided by the number of time histories (100,000). Results are presented for a set of base case parameter values

  15. Associativity and normative credal probability.

    PubMed

    Snow, P

    2002-01-01

    Cox's Theorem is a widely cited motivation for probabilistic models of uncertain belief. The theorem relates the associativity of the logical connectives to that of the arithmetic operations of probability. Recent questions about the correctness of Cox's Theorem have been resolved, but there are new questions about one functional equation used by Cox in 1946. This equation is missing from his later work. Advances in knowledge since 1946 and changes in Cox's research interests explain the equation's disappearance. Other associativity-based motivations avoid functional equations altogether, and so may be more transparently applied to finite domains and discrete beliefs. A discrete counterpart of Cox's Theorem can be assembled from results that have been in the literature since 1959. PMID:18238098

  16. Imprecise probability for non-commuting observables

    NASA Astrophysics Data System (ADS)

    Allahverdyan, Armen E.

    2015-08-01

    It is known that non-commuting observables in quantum mechanics do not have joint probability. This statement refers to the precise (additive) probability model. I show that the joint distribution of any non-commuting pair of variables can be quantified via upper and lower probabilities, i.e. the joint probability is described by an interval instead of a number (imprecise probability). I propose transparent axioms from which the upper and lower probability operators follow. The imprecise probability depend on the non-commuting observables, is linear over the state (density matrix) and reverts to the usual expression for commuting observables.

  17. Exploring Student Difficulties with Multiplicity and Probability in Statistical Physics

    NASA Astrophysics Data System (ADS)

    Mountcastle, Donald; Thompson, John; Smith, Trevor

    2010-03-01

    We continue our research program on the teaching and learning of concepts in upper-division thermal physics at the University of Maine. Typical statistical physics textbooks introduce entropy (S) and multiplicity (w) [S = k ln(w)] with binary events such as flipping coins N times. Inherent confusion with probability and statistics, macrostates and microstates, and their varying dependence on N leads to student conceptual difficulties that persist after textbook-centered activities. We developed and implemented a guided-inquiry tutorial on the binomial distribution with student use of computational software to produce calculations of multiplicities, outcome probabilities, and graphs of their distributions as functions of N. This allows convenient exploration of statistics over more than seven orders of magnitude in N. Comparing student answers to pre- and post-tutorial questions, we find some, but not all of the intended learning results are achieved.

  18. Fusion probability in heavy nuclei

    NASA Astrophysics Data System (ADS)

    Banerjee, Tathagata; Nath, S.; Pal, Santanu

    2015-03-01

    Background: Fusion between two massive nuclei is a very complex process and is characterized by three stages: (a) capture inside the potential barrier, (b) formation of an equilibrated compound nucleus (CN), and (c) statistical decay of the CN leading to a cold evaporation residue (ER) or fission. The second stage is the least understood of the three and is the most crucial in predicting yield of superheavy elements (SHE) formed in complete fusion reactions. Purpose: A systematic study of average fusion probability, , is undertaken to obtain a better understanding of its dependence on various reaction parameters. The study may also help to clearly demarcate onset of non-CN fission (NCNF), which causes fusion probability, PCN, to deviate from unity. Method: ER excitation functions for 52 reactions leading to CN in the mass region 170-220, which are available in the literature, have been compared with statistical model (SM) calculations. Capture cross sections have been obtained from a coupled-channels code. In the SM, shell corrections in both the level density and the fission barrier have been included. for these reactions has been extracted by comparing experimental and theoretical ER excitation functions in the energy range ˜5 %-35% above the potential barrier, where known effects of nuclear structure are insignificant. Results: has been shown to vary with entrance channel mass asymmetry, η (or charge product, ZpZt ), as well as with fissility of the CN, χCN. No parameter has been found to be adequate as a single scaling variable to determine . Approximate boundaries have been obtained from where starts deviating from unity. Conclusions: This study quite clearly reveals the limits of applicability of the SM in interpreting experimental observables from fusion reactions involving two massive nuclei. Deviation of from unity marks the beginning of the domain of dynamical models of fusion. Availability of precise ER cross

  19. Task specificity of attention training: the case of probability cuing

    PubMed Central

    Jiang, Yuhong V.; Swallow, Khena M.; Won, Bo-Yeong; Cistera, Julia D.; Rosenbaum, Gail M.

    2014-01-01

    Statistical regularities in our environment enhance perception and modulate the allocation of spatial attention. Surprisingly little is known about how learning-induced changes in spatial attention transfer across tasks. In this study, we investigated whether a spatial attentional bias learned in one task transfers to another. Most of the experiments began with a training phase in which a search target was more likely to be located in one quadrant of the screen than in the other quadrants. An attentional bias toward the high-probability quadrant developed during training (probability cuing). In a subsequent, testing phase, the target's location distribution became random. In addition, the training and testing phases were based on different tasks. Probability cuing did not transfer between visual search and a foraging-like task. However, it did transfer between various types of visual search tasks that differed in stimuli and difficulty. These data suggest that different visual search tasks share a common and transferrable learned attentional bias. However, this bias is not shared by high-level, decision-making tasks such as foraging. PMID:25113853

  20. Exploring the Overestimation of Conjunctive Probabilities

    PubMed Central

    Nilsson, Håkan; Rieskamp, Jörg; Jenny, Mirjam A.

    2013-01-01

    People often overestimate probabilities of conjunctive events. The authors explored whether the accuracy of conjunctive probability estimates can be improved by increased experience with relevant constituent events and by using memory aids. The first experiment showed that increased experience with constituent events increased the correlation between the estimated and the objective conjunctive probabilities, but that it did not reduce overestimation of conjunctive probabilities. The second experiment showed that reducing cognitive load with memory aids for the constituent probabilities led to improved estimates of the conjunctive probabilities and to decreased overestimation of conjunctive probabilities. To explain the cognitive process underlying people’s probability estimates, the configural weighted average model was tested against the normative multiplicative model. The configural weighted average model generates conjunctive probabilities that systematically overestimate objective probabilities although the generated probabilities still correlate strongly with the objective probabilities. For the majority of participants this model was better than the multiplicative model in predicting the probability estimates. However, when memory aids were provided, the predictive accuracy of the multiplicative model increased. In sum, memory tools can improve people’s conjunctive probability estimates. PMID:23460026

  1. Direct probability mapping of contaminants

    SciTech Connect

    Rautman, C.A.

    1993-09-17

    Exhaustive characterization of a contaminated site is a physical and practical impossibility. Descriptions of the nature, extent, and level of contamination, as well as decisions regarding proposed remediation activities, must be made in a state of uncertainty based upon limited physical sampling. Geostatistical simulation provides powerful tools for investigating contaminant levels, and in particular, for identifying and using the spatial interrelationships among a set of isolated sample values. This additional information can be used to assess the likelihood of encountering contamination at unsampled locations and to evaluate the risk associated with decisions to remediate or not to remediate specific regions within a site. Past operation of the DOE Feed Materials Production Center has contaminated a site near Fernald, Ohio, with natural uranium. Soil geochemical data have been collected as part of the Uranium-in-Soils Integrated Demonstration Project. These data have been used to construct a number of stochastic images of potential contamination for parcels approximately the size of a selective remediation unit. Each such image accurately reflects the actual measured sample values, and reproduces the univariate statistics and spatial character of the extant data. Post-processing of a large number of these equally likely, statistically similar images produces maps directly showing the probability of exceeding specified levels of contamination. Evaluation of the geostatistical simulations can yield maps representing the expected magnitude of the contamination for various regions and other information that may be important in determining a suitable remediation process or in sizing equipment to accomplish the restoration.

  2. Trajectory versus probability density entropy.

    PubMed

    Bologna, M; Grigolini, P; Karagiorgis, M; Rosa, A

    2001-07-01

    We show that the widely accepted conviction that a connection can be established between the probability density entropy and the Kolmogorov-Sinai (KS) entropy is questionable. We adopt the definition of density entropy as a functional of a distribution density whose time evolution is determined by a transport equation, conceived as the only prescription to use for the calculation. Although the transport equation is built up for the purpose of affording a picture equivalent to that stemming from trajectory dynamics, no direct use of trajectory time evolution is allowed, once the transport equation is defined. With this definition in mind we prove that the detection of a time regime of increase of the density entropy with a rate identical to the KS entropy is possible only in a limited number of cases. The proposals made by some authors to establish a connection between the two entropies in general, violate our definition of density entropy and imply the concept of trajectory, which is foreign to that of density entropy. PMID:11461383

  3. Trajectory versus probability density entropy

    NASA Astrophysics Data System (ADS)

    Bologna, Mauro; Grigolini, Paolo; Karagiorgis, Markos; Rosa, Angelo

    2001-07-01

    We show that the widely accepted conviction that a connection can be established between the probability density entropy and the Kolmogorov-Sinai (KS) entropy is questionable. We adopt the definition of density entropy as a functional of a distribution density whose time evolution is determined by a transport equation, conceived as the only prescription to use for the calculation. Although the transport equation is built up for the purpose of affording a picture equivalent to that stemming from trajectory dynamics, no direct use of trajectory time evolution is allowed, once the transport equation is defined. With this definition in mind we prove that the detection of a time regime of increase of the density entropy with a rate identical to the KS entropy is possible only in a limited number of cases. The proposals made by some authors to establish a connection between the two entropies in general, violate our definition of density entropy and imply the concept of trajectory, which is foreign to that of density entropy.

  4. Probability distributions of turbulent energy.

    PubMed

    Momeni, Mahdi; Müller, Wolf-Christian

    2008-05-01

    Probability density functions (PDFs) of scale-dependent energy fluctuations, P[deltaE(l)] , are studied in high-resolution direct numerical simulations of Navier-Stokes and incompressible magnetohydrodynamic (MHD) turbulence. MHD flows with and without a strong mean magnetic field are considered. For all three systems it is found that the PDFs of inertial range energy fluctuations exhibit self-similarity and monoscaling in agreement with recent solar-wind measurements [Hnat, Geophys. Res. Lett. 29, 86 (2002)]. Furthermore, the energy PDFs exhibit similarity over all scales of the turbulent system showing no substantial qualitative change of shape as the scale of the fluctuations varies. This is in contrast to the well-known behavior of PDFs of turbulent velocity fluctuations. In all three cases under consideration the P[deltaE(l)] resemble Lévy-type gamma distributions approximately Delta;{-1} exp(-|deltaE|/Delta)|deltaE|;{-gamma} The observed gamma distributions exhibit a scale-dependent width Delta(l) and a system-dependent gamma . The monoscaling property reflects the inertial-range scaling of the Elsässer-field fluctuations due to lacking Galilei invariance of deltaE . The appearance of Lévy distributions is made plausible by a simple model of energy transfer. PMID:18643170

  5. The Black Hole Formation Probability

    NASA Astrophysics Data System (ADS)

    Clausen, Drew; Piro, Anthony L.; Ott, Christian D.

    2015-02-01

    A longstanding question in stellar evolution is which massive stars produce black holes (BHs) rather than neutron stars (NSs) upon death. It has been common practice to assume that a given zero-age main sequence (ZAMS) mass star (and perhaps a given metallicity) simply produces either an NS or a BH, but this fails to account for a myriad of other variables that may effect this outcome, such as spin, binarity, or even stochastic differences in the stellar structure near core collapse. We argue that instead a probabilistic description of NS versus BH formation may be better suited to account for the current uncertainties in understanding how massive stars die. We present an initial exploration of the probability that a star will make a BH as a function of its ZAMS mass, P BH(M ZAMS). Although we find that it is difficult to derive a unique P BH(M ZAMS) using current measurements of both the BH mass distribution and the degree of chemical enrichment by massive stars, we demonstrate how P BH(M ZAMS) changes with these various observational and theoretical uncertainties. We anticipate that future studies of Galactic BHs and theoretical studies of core collapse will refine P BH(M ZAMS) and argue that this framework is an important new step toward better understanding BH formation. A probabilistic description of BH formation will be useful as input for future population synthesis studies that are interested in the formation of X-ray binaries, the nature and event rate of gravitational wave sources, and answering questions about chemical enrichment.

  6. THE BLACK HOLE FORMATION PROBABILITY

    SciTech Connect

    Clausen, Drew; Piro, Anthony L.; Ott, Christian D.

    2015-02-01

    A longstanding question in stellar evolution is which massive stars produce black holes (BHs) rather than neutron stars (NSs) upon death. It has been common practice to assume that a given zero-age main sequence (ZAMS) mass star (and perhaps a given metallicity) simply produces either an NS or a BH, but this fails to account for a myriad of other variables that may effect this outcome, such as spin, binarity, or even stochastic differences in the stellar structure near core collapse. We argue that instead a probabilistic description of NS versus BH formation may be better suited to account for the current uncertainties in understanding how massive stars die. We present an initial exploration of the probability that a star will make a BH as a function of its ZAMS mass, P {sub BH}(M {sub ZAMS}). Although we find that it is difficult to derive a unique P {sub BH}(M {sub ZAMS}) using current measurements of both the BH mass distribution and the degree of chemical enrichment by massive stars, we demonstrate how P {sub BH}(M {sub ZAMS}) changes with these various observational and theoretical uncertainties. We anticipate that future studies of Galactic BHs and theoretical studies of core collapse will refine P {sub BH}(M {sub ZAMS}) and argue that this framework is an important new step toward better understanding BH formation. A probabilistic description of BH formation will be useful as input for future population synthesis studies that are interested in the formation of X-ray binaries, the nature and event rate of gravitational wave sources, and answering questions about chemical enrichment.

  7. The Probability Distribution for a Biased Spinner

    ERIC Educational Resources Information Center

    Foster, Colin

    2012-01-01

    This article advocates biased spinners as an engaging context for statistics students. Calculating the probability of a biased spinner landing on a particular side makes valuable connections between probability and other areas of mathematics. (Contains 2 figures and 1 table.)

  8. Using Playing Cards to Differentiate Probability Interpretations

    ERIC Educational Resources Information Center

    López Puga, Jorge

    2014-01-01

    The aprioristic (classical, naïve and symmetric) and frequentist interpretations of probability are commonly known. Bayesian or subjective interpretation of probability is receiving increasing attention. This paper describes an activity to help students differentiate between the three types of probability interpretations.

  9. Illustrating Basic Probability Calculations Using "Craps"

    ERIC Educational Resources Information Center

    Johnson, Roger W.

    2006-01-01

    Instructors may use the gambling game of craps to illustrate the use of a number of fundamental probability identities. For the "pass-line" bet we focus on the chance of winning and the expected game length. To compute these, probabilities of unions of disjoint events, probabilities of intersections of independent events, conditional probabilities…

  10. Pre-Service Teachers' Conceptions of Probability

    ERIC Educational Resources Information Center

    Odafe, Victor U.

    2011-01-01

    Probability knowledge and skills are needed in science and in making daily decisions that are sometimes made under uncertain conditions. Hence, there is the need to ensure that the pre-service teachers of our children are well prepared to teach probability. Pre-service teachers' conceptions of probability are identified, and ways of helping them…

  11. Teaching Probabilities and Statistics to Preschool Children

    ERIC Educational Resources Information Center

    Pange, Jenny

    2003-01-01

    This study considers the teaching of probabilities and statistics to a group of preschool children using traditional classroom activities and Internet games. It was clear from this study that children can show a high level of understanding of probabilities and statistics, and demonstrate high performance in probability games. The use of Internet…

  12. Subjective and objective probabilities in quantum mechanics

    SciTech Connect

    Srednicki, Mark

    2005-05-15

    We discuss how the apparently objective probabilities predicted by quantum mechanics can be treated in the framework of Bayesian probability theory, in which all probabilities are subjective. Our results are in accord with earlier work by Caves, Fuchs, and Schack, but our approach and emphasis are different. We also discuss the problem of choosing a noninformative prior for a density matrix.

  13. The Cognitive Substrate of Subjective Probability

    ERIC Educational Resources Information Center

    Nilsson, Hakan; Olsson, Henrik; Juslin, Peter

    2005-01-01

    The prominent cognitive theories of probability judgment were primarily developed to explain cognitive biases rather than to account for the cognitive processes in probability judgment. In this article the authors compare 3 major theories of the processes and representations in probability judgment: the representativeness heuristic, implemented as…

  14. Dynamic Encoding of Speech Sequence Probability in Human Temporal Cortex

    PubMed Central

    Leonard, Matthew K.; Bouchard, Kristofer E.; Tang, Claire

    2015-01-01

    Sensory processing involves identification of stimulus features, but also integration with the surrounding sensory and cognitive context. Previous work in animals and humans has shown fine-scale sensitivity to context in the form of learned knowledge about the statistics of the sensory environment, including relative probabilities of discrete units in a stream of sequential auditory input. These statistics are a defining characteristic of one of the most important sequential signals humans encounter: speech. For speech, extensive exposure to a language tunes listeners to the statistics of sound sequences. To address how speech sequence statistics are neurally encoded, we used high-resolution direct cortical recordings from human lateral superior temporal cortex as subjects listened to words and nonwords with varying transition probabilities between sound segments. In addition to their sensitivity to acoustic features (including contextual features, such as coarticulation), we found that neural responses dynamically encoded the language-level probability of both preceding and upcoming speech sounds. Transition probability first negatively modulated neural responses, followed by positive modulation of neural responses, consistent with coordinated predictive and retrospective recognition processes, respectively. Furthermore, transition probability encoding was different for real English words compared with nonwords, providing evidence for online interactions with high-order linguistic knowledge. These results demonstrate that sensory processing of deeply learned stimuli involves integrating physical stimulus features with their contextual sequential structure. Despite not being consciously aware of phoneme sequence statistics, listeners use this information to process spoken input and to link low-level acoustic representations with linguistic information about word identity and meaning. PMID:25948269

  15. Datamining approaches for modeling tumor control probability

    PubMed Central

    Naqa, Issam El; Deasy, Joseph O.; Mu, Yi; Huang, Ellen; Hope, Andrew J.; Lindsay, Patricia E.; Apte, Aditya; Alaly, James; Bradley, Jeffrey D.

    2016-01-01

    Background Tumor control probability (TCP) to radiotherapy is determined by complex interactions between tumor biology, tumor microenvironment, radiation dosimetry, and patient-related variables. The complexity of these heterogeneous variable interactions constitutes a challenge for building predictive models for routine clinical practice. We describe a datamining framework that can unravel the higher order relationships among dosimetric dose-volume prognostic variables, interrogate various radiobiological processes, and generalize to unseen data before when applied prospectively. Material and methods Several datamining approaches are discussed that include dose-volume metrics, equivalent uniform dose, mechanistic Poisson model, and model building methods using statistical regression and machine learning techniques. Institutional datasets of non-small cell lung cancer (NSCLC) patients are used to demonstrate these methods. The performance of the different methods was evaluated using bivariate Spearman rank correlations (rs). Over-fitting was controlled via resampling methods. Results Using a dataset of 56 patients with primary NCSLC tumors and 23 candidate variables, we estimated GTV volume and V75 to be the best model parameters for predicting TCP using statistical resampling and a logistic model. Using these variables, the support vector machine (SVM) kernel method provided superior performance for TCP prediction with an rs = 0.68 on leave-one-out testing compared to logistic regression (rs = 0.4), Poisson-based TCP (rs = 0.33), and cell kill equivalent uniform dose model (rs = 0.17). Conclusions The prediction of treatment response can be improved by utilizing datamining approaches, which are able to unravel important non-linear complex interactions among model variables and have the capacity to predict on unseen data for prospective clinical applications. PMID:20192878

  16. Prior probabilities modulate cortical surprise responses: A study of event-related potentials.

    PubMed

    Seer, Caroline; Lange, Florian; Boos, Moritz; Dengler, Reinhard; Kopp, Bruno

    2016-07-01

    The human brain predicts events in its environment based on expectations, and unexpected events are surprising. When probabilistic contingencies in the environment are precisely instructed, the individual can form expectations based on quantitative probabilistic information ('inference-based learning'). In contrast, when probabilistic contingencies are imprecisely instructed, expectations are formed based on the individual's cumulative experience ('experience-based learning'). Here, we used the urn-ball paradigm to investigate how variations in prior probabilities and in the precision of information about these priors modulate choice behavior and event-related potential (ERP) correlates of surprise. In the urn-ball paradigm, participants are repeatedly forced to infer hidden states responsible for generating observable events, given small samples of factual observations. We manipulated prior probabilities of the states, and we rendered the priors calculable or incalculable, respectively. The analysis of choice behavior revealed that the tendency to consider prior probabilities when making decisions about hidden states was stronger when prior probabilities were calculable, at least in some of our participants. Surprise-related P3b amplitudes were observed in both the calculable and the incalculable prior probability condition. In contrast, calculability of prior probabilities modulated anteriorly distributed ERP amplitudes: when prior probabilities were calculable, surprising events elicited enhanced P3a amplitudes. However, when prior probabilities were incalculable, surprise was associated with enhanced N2 amplitudes. Furthermore, interindividual variability in reliance on prior probabilities was associated with attenuated P3b surprise responses under calculable in comparison to incalculable prior probabilities. Our results suggest two distinct neural systems for probabilistic learning that are recruited depending on contextual cues such as the precision of

  17. Bell Could Become the Copernicus of Probability

    NASA Astrophysics Data System (ADS)

    Khrennikov, Andrei

    2016-07-01

    Our aim is to emphasize the role of mathematical models in physics, especially models of geometry and probability. We briefly compare developments of geometry and probability by pointing to similarities and differences: from Euclid to Lobachevsky and from Kolmogorov to Bell. In probability, Bell could play the same role as Lobachevsky in geometry. In fact, violation of Bell’s inequality can be treated as implying the impossibility to apply the classical probability model of Kolmogorov (1933) to quantum phenomena. Thus the quantum probabilistic model (based on Born’s rule) can be considered as the concrete example of the non-Kolmogorovian model of probability, similarly to the Lobachevskian model — the first example of the non-Euclidean model of geometry. This is the “probability model” interpretation of the violation of Bell’s inequality. We also criticize the standard interpretation—an attempt to add to rigorous mathematical probability models additional elements such as (non)locality and (un)realism. Finally, we compare embeddings of non-Euclidean geometries into the Euclidean space with embeddings of the non-Kolmogorovian probabilities (in particular, quantum probability) into the Kolmogorov probability space. As an example, we consider the CHSH-test.

  18. Derivation of quantum probability from measurement

    NASA Astrophysics Data System (ADS)

    Herbut, Fedor

    2016-05-01

    To begin with, it is pointed out that the form of the quantum probability formula originates in the very initial state of the object system as seen when the state is expanded with the eigenprojectors of the measured observable. Making use of the probability reproducibility condition, which is a key concept in unitary measurement theory, one obtains the relevant coherent distribution of the complete-measurement results in the final unitary-measurement state in agreement with the mentioned probability formula. Treating the transition from the final unitary, or premeasurement, state, where all possible results are present, to one complete-measurement result sketchily in the usual way, the well-known probability formula is derived. In conclusion it is pointed out that the entire argument is only formal unless one makes it physical assuming that the quantum probability law is valid in the extreme case of probability-one (certain) events (projectors).

  19. Probability and Quantum Paradigms: the Interplay

    NASA Astrophysics Data System (ADS)

    Kracklauer, A. F.

    2007-12-01

    Since the introduction of Born's interpretation of quantum wave functions as yielding the probability density of presence, Quantum Theory and Probability have lived in a troubled symbiosis. Problems arise with this interpretation because quantum probabilities exhibit features alien to usual probabilities, namely non Boolean structure and non positive-definite phase space probability densities. This has inspired research into both elaborate formulations of Probability Theory and alternate interpretations for wave functions. Herein the latter tactic is taken and a suggested variant interpretation of wave functions based on photo detection physics proposed, and some empirical consequences are considered. Although incomplete in a few details, this variant is appealing in its reliance on well tested concepts and technology.

  20. Probability and Quantum Paradigms: the Interplay

    SciTech Connect

    Kracklauer, A. F.

    2007-12-03

    Since the introduction of Born's interpretation of quantum wave functions as yielding the probability density of presence, Quantum Theory and Probability have lived in a troubled symbiosis. Problems arise with this interpretation because quantum probabilities exhibit features alien to usual probabilities, namely non Boolean structure and non positive-definite phase space probability densities. This has inspired research into both elaborate formulations of Probability Theory and alternate interpretations for wave functions. Herein the latter tactic is taken and a suggested variant interpretation of wave functions based on photo detection physics proposed, and some empirical consequences are considered. Although incomplete in a few details, this variant is appealing in its reliance on well tested concepts and technology.

  1. Entropy analysis of systems exhibiting negative probabilities

    NASA Astrophysics Data System (ADS)

    Tenreiro Machado, J. A.

    2016-07-01

    This paper addresses the concept of negative probability and its impact upon entropy. An analogy between the probability generating functions, in the scope of quasiprobability distributions, and the Grünwald-Letnikov definition of fractional derivatives, is explored. Two distinct cases producing negative probabilities are formulated and their distinct meaning clarified. Numerical calculations using the Shannon entropy characterize further the characteristics of the two limit cases.

  2. Calculating the CEP (Circular Error Probable)

    NASA Technical Reports Server (NTRS)

    1987-01-01

    This report compares the probability contained in the Circular Error Probable associated with an Elliptical Error Probable to that of the EEP at a given confidence level. The levels examined are 50 percent and 95 percent. The CEP is found to be both more conservative and less conservative than the associated EEP, depending on the eccentricity of the ellipse. The formulas used are derived in the appendix.

  3. Neural Correlates of the Divergence of Instrumental Probability Distributions

    PubMed Central

    Wang, Shuo; Zhang, June; O'Doherty, John P.

    2013-01-01

    Flexible action selection requires knowledge about how alternative actions impact the environment: a “cognitive map” of instrumental contingencies. Reinforcement learning theories formalize this map as a set of stochastic relationships between actions and states, such that for any given action considered in a current state, a probability distribution is specified over possible outcome states. Here, we show that activity in the human inferior parietal lobule correlates with the divergence of such outcome distributions–a measure that reflects whether discrimination between alternative actions increases the controllability of the future–and, further, that this effect is dissociable from those of other information theoretic and motivational variables, such as outcome entropy, action values, and outcome utilities. Our results suggest that, although ultimately combined with reward estimates to generate action values, outcome probability distributions associated with alternative actions may be contrasted independently of valence computations, to narrow the scope of the action selection problem. PMID:23884955

  4. Neural correlates of the divergence of instrumental probability distributions.

    PubMed

    Liljeholm, Mimi; Wang, Shuo; Zhang, June; O'Doherty, John P

    2013-07-24

    Flexible action selection requires knowledge about how alternative actions impact the environment: a "cognitive map" of instrumental contingencies. Reinforcement learning theories formalize this map as a set of stochastic relationships between actions and states, such that for any given action considered in a current state, a probability distribution is specified over possible outcome states. Here, we show that activity in the human inferior parietal lobule correlates with the divergence of such outcome distributions-a measure that reflects whether discrimination between alternative actions increases the controllability of the future-and, further, that this effect is dissociable from those of other information theoretic and motivational variables, such as outcome entropy, action values, and outcome utilities. Our results suggest that, although ultimately combined with reward estimates to generate action values, outcome probability distributions associated with alternative actions may be contrasted independently of valence computations, to narrow the scope of the action selection problem. PMID:23884955

  5. Psychophysics of the probability weighting function

    NASA Astrophysics Data System (ADS)

    Takahashi, Taiki

    2011-03-01

    A probability weighting function w(p) for an objective probability p in decision under risk plays a pivotal role in Kahneman-Tversky prospect theory. Although recent studies in econophysics and neuroeconomics widely utilized probability weighting functions, psychophysical foundations of the probability weighting functions have been unknown. Notably, a behavioral economist Prelec (1998) [4] axiomatically derived the probability weighting function w(p)=exp(-() (0<α<1 and w(0)=1,w(1e)=1e,w(1)=1), which has extensively been studied in behavioral neuroeconomics. The present study utilizes psychophysical theory to derive Prelec's probability weighting function from psychophysical laws of perceived waiting time in probabilistic choices. Also, the relations between the parameters in the probability weighting function and the probability discounting function in behavioral psychology are derived. Future directions in the application of the psychophysical theory of the probability weighting function in econophysics and neuroeconomics are discussed.

  6. Executable Code Recognition in Network Flows Using Instruction Transition Probabilities

    NASA Astrophysics Data System (ADS)

    Kim, Ikkyun; Kang, Koohong; Choi, Yangseo; Kim, Daewon; Oh, Jintae; Jang, Jongsoo; Han, Kijun

    The ability to recognize quickly inside network flows to be executable is prerequisite for malware detection. For this purpose, we introduce an instruction transition probability matrix (ITPX) which is comprised of the IA-32 instruction sets and reveals the characteristics of executable code's instruction transition patterns. And then, we propose a simple algorithm to detect executable code inside network flows using a reference ITPX which is learned from the known Windows Portable Executable files. We have tested the algorithm with more than thousands of executable and non-executable codes. The results show that it is very promising enough to use in real world.

  7. Predetonation probability of a fission-bomb core

    NASA Astrophysics Data System (ADS)

    Reed, B. Cameron

    2010-08-01

    An undergraduate-level derivation of the probability that a uranium or plutonium fission bomb will suffer an uncontrolled predetonation due to neutrons liberated in spontaneous fissions in the fissile material is developed. Consistent with what was learned by Los Alamos bomb designers during World War II, it is shown why uncontrolled predetonation was not a problem for a U-235 bomb of the Little Boy "gun" design but necessitated development of implosion engineering for the Pu-239 Trinity and Fat Man bombs where the cores were contaminated with highly spontaneously fissile Pu-240.

  8. Lattice Duality: The Origin of Probability and Entropy

    NASA Technical Reports Server (NTRS)

    Knuth, Kevin H.

    2004-01-01

    Bayesian probability theory is an inference calculus, which originates from a generalization of inclusion on the Boolean lattice of logical assertions to a degree of inclusion represented by a real number. Dual to this lattice is the distributive lattice of questions constructed from the ordered set of down-sets of assertions, which forms the foundation of the calculus of inquiry-a generalization of information theory. In this paper we introduce this novel perspective on these spaces in which machine learning is performed and discuss the relationship between these results and several proposed generalizations of information theory in the literature.

  9. Probability: A Matter of Life and Death

    ERIC Educational Resources Information Center

    Hassani, Mehdi; Kippen, Rebecca; Mills, Terence

    2016-01-01

    Life tables are mathematical tables that document probabilities of dying and life expectancies at different ages in a society. Thus, the life table contains some essential features of the health of a population. Probability is often regarded as a difficult branch of mathematics. Life tables provide an interesting approach to introducing concepts…

  10. Stimulus Probability Effects in Absolute Identification

    ERIC Educational Resources Information Center

    Kent, Christopher; Lamberts, Koen

    2016-01-01

    This study investigated the effect of stimulus presentation probability on accuracy and response times in an absolute identification task. Three schedules of presentation were used to investigate the interaction between presentation probability and stimulus position within the set. Data from individual participants indicated strong effects of…

  11. Teaching Probability: A Socio-Constructivist Perspective

    ERIC Educational Resources Information Center

    Sharma, Sashi

    2015-01-01

    There is a considerable and rich literature on students' misconceptions in probability. However, less attention has been paid to the development of students' probabilistic thinking in the classroom. This paper offers a sequence, grounded in socio-constructivist perspective for teaching probability.

  12. Teaching Statistics and Probability: 1981 Yearbook.

    ERIC Educational Resources Information Center

    Shulte, Albert P., Ed.; Smart, James R., Ed.

    This 1981 yearbook of the National Council of Teachers of Mathematics (NCTM) offers classroom ideas for teaching statistics and probability, viewed as important topics in the school mathematics curriculum. Statistics and probability are seen as appropriate because they: (1) provide meaningful applications of mathematics at all levels; (2) provide…

  13. Phonotactic Probabilities in Young Children's Speech Production

    ERIC Educational Resources Information Center

    Zamuner, Tania S.; Gerken, Louann; Hammond, Michael

    2004-01-01

    This research explores the role of phonotactic probability in two-year-olds' production of coda consonants. Twenty-nine children were asked to repeat CVC non-words that were used as labels for pictures of imaginary animals. The CVC non-words were controlled for their phonotactic probabilities, neighbourhood densities, word-likelihood ratings, and…

  14. 47 CFR 1.1623 - Probability calculation.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 1 2010-10-01 2010-10-01 false Probability calculation. 1.1623 Section 1.1623 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1623 Probability calculation. (a) All calculations shall...

  15. Simulations of Probabilities for Quantum Computing

    NASA Technical Reports Server (NTRS)

    Zak, M.

    1996-01-01

    It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-LIpschitz dynamics, without utilization of any man-made devices (such as random number generators). Self-organizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed.

  16. Correlation as Probability of Common Descent.

    ERIC Educational Resources Information Center

    Falk, Ruma; Well, Arnold D.

    1996-01-01

    One interpretation of the Pearson product-moment correlation ("r"), correlation as the probability of originating from common descent, important to the genetic measurement of inbreeding, is examined. The conditions under which "r" can be interpreted as the probability of "identity by descent" are specified, and the possibility of generalizing this…

  17. 47 CFR 1.1623 - Probability calculation.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 1 2012-10-01 2012-10-01 false Probability calculation. 1.1623 Section 1.1623 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Grants by Random Selection Random Selection Procedures for Mass Media Services General Procedures § 1.1623 Probability calculation. (a)...

  18. Probability Simulations by Non-Lipschitz Chaos

    NASA Technical Reports Server (NTRS)

    Zak, Michail

    1996-01-01

    It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-Lipschitz dynamics, without utilization of any man-made devices. Self-organizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed.

  19. Laboratory-Tutorial Activities for Teaching Probability

    ERIC Educational Resources Information Center

    Wittmann, Michael C.; Morgan, Jeffrey T.; Feeley, Roger E.

    2006-01-01

    We report on the development of students' ideas of probability and probability density in a University of Maine laboratory-based general education physics course called "Intuitive Quantum Physics". Students in the course are generally math phobic with unfavorable expectations about the nature of physics and their ability to do it. We describe a…

  20. Probability Issues in without Replacement Sampling

    ERIC Educational Resources Information Center

    Joarder, A. H.; Al-Sabah, W. S.

    2007-01-01

    Sampling without replacement is an important aspect in teaching conditional probabilities in elementary statistics courses. Different methods proposed in different texts for calculating probabilities of events in this context are reviewed and their relative merits and limitations in applications are pinpointed. An alternative representation of…

  1. Average Transmission Probability of a Random Stack

    ERIC Educational Resources Information Center

    Lu, Yin; Miniatura, Christian; Englert, Berthold-Georg

    2010-01-01

    The transmission through a stack of identical slabs that are separated by gaps with random widths is usually treated by calculating the average of the logarithm of the transmission probability. We show how to calculate the average of the transmission probability itself with the aid of a recurrence relation and derive analytical upper and lower…

  2. 47 CFR 1.1623 - Probability calculation.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 1 2011-10-01 2011-10-01 false Probability calculation. 1.1623 Section 1.1623 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Random Selection Procedures for Mass Media Services General Procedures § 1.1623 Probability calculation. (a) All calculations shall...

  3. 47 CFR 1.1623 - Probability calculation.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... 47 Telecommunication 1 2014-10-01 2014-10-01 false Probability calculation. 1.1623 Section 1.1623 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Grants by Random Selection Random Selection Procedures for Mass Media Services General Procedures § 1.1623 Probability calculation. (a)...

  4. 47 CFR 1.1623 - Probability calculation.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... 47 Telecommunication 1 2013-10-01 2013-10-01 false Probability calculation. 1.1623 Section 1.1623 Telecommunication FEDERAL COMMUNICATIONS COMMISSION GENERAL PRACTICE AND PROCEDURE Grants by Random Selection Random Selection Procedures for Mass Media Services General Procedures § 1.1623 Probability calculation. (a)...

  5. Quantum probability assignment limited by relativistic causality.

    PubMed

    Han, Yeong Deok; Choi, Taeseung

    2016-01-01

    Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment. PMID:26971717

  6. Assessment of the probability of contaminating Mars

    NASA Technical Reports Server (NTRS)

    Judd, B. R.; North, D. W.; Pezier, J. P.

    1974-01-01

    New methodology is proposed to assess the probability that the planet Mars will by biologically contaminated by terrestrial microorganisms aboard a spacecraft. Present NASA methods are based on the Sagan-Coleman formula, which states that the probability of contamination is the product of the expected microbial release and a probability of growth. The proposed new methodology extends the Sagan-Coleman approach to permit utilization of detailed information on microbial characteristics, the lethality of release and transport mechanisms, and of other information about the Martian environment. Three different types of microbial release are distinguished in the model for assessing the probability of contamination. The number of viable microbes released by each mechanism depends on the bio-burden in various locations on the spacecraft and on whether the spacecraft landing is accomplished according to plan. For each of the three release mechanisms a probability of growth is computed, using a model for transport into an environment suited to microbial growth.

  7. Multinomial mixture model with heterogeneous classification probabilities

    USGS Publications Warehouse

    Holland, M.D.; Gray, B.R.

    2011-01-01

    Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.

  8. Quantum probability assignment limited by relativistic causality

    PubMed Central

    Han, Yeong Deok; Choi, Taeseung

    2016-01-01

    Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment. PMID:26971717

  9. Liquefaction probability curves for surficial geologic deposits

    USGS Publications Warehouse

    Holzer, Thomas L.; Noce, Thomas E.; Bennett, Michael J.

    2011-01-01

    Liquefaction probability curves that predict the probability of surface manifestations of earthquake-induced liquefaction are developed for 14 different types of surficial geologic units. The units consist of alluvial fan, beach ridge, river delta topset and foreset beds, eolian dune, point bar, flood basin, natural river and alluvial fan levees, abandoned river channel, deep-water lake, lagoonal, sandy artificial fill, and valley train deposits. Probability is conditioned on earthquake magnitude and peak ground acceleration. Curves are developed for water table depths of 1.5 and 5.0 m. Probabilities are derived from complementary cumulative frequency distributions of the liquefaction potential index (LPI) that were computed from 927 cone penetration tests. For natural deposits with a water table at 1.5 m and subjected to a M7.5 earthquake with peak ground acceleration (PGA)  =  0.25g, probabilities range from 0.5 for beach ridge, point bar, and deltaic deposits. The curves also were used to assign ranges of liquefaction probabilities to the susceptibility categories proposed previously for different geologic deposits. For the earthquake described here, probabilities for susceptibility categories have ranges of 0–0.08 for low, 0.09–0.30 for moderate, 0.31–0.62 for high, and 0.63–1.00 for very high. Retrospective predictions of liquefaction during historical earthquakes based on the curves compare favorably to observations.

  10. Survival probability in patients with liver trauma.

    PubMed

    Buci, Skender; Kukeli, Agim

    2016-08-01

    Purpose - The purpose of this paper is to assess the survival probability among patients with liver trauma injury using the anatomical and psychological scores of conditions, characteristics and treatment modes. Design/methodology/approach - A logistic model is used to estimate 173 patients' survival probability. Data are taken from patient records. Only emergency room patients admitted to University Hospital of Trauma (former Military Hospital) in Tirana are included. Data are recorded anonymously, preserving the patients' privacy. Findings - When correctly predicted, the logistic models show that survival probability varies from 70.5 percent up to 95.4 percent. The degree of trauma injury, trauma with liver and other organs, total days the patient was hospitalized, and treatment method (conservative vs intervention) are statistically important in explaining survival probability. Practical implications - The study gives patients, their relatives and physicians ample and sound information they can use to predict survival chances, the best treatment and resource management. Originality/value - This study, which has not been done previously, explores survival probability, success probability for conservative and non-conservative treatment, and success probability for single vs multiple injuries from liver trauma. PMID:27477933

  11. Semigroups of tomographic probabilities and quantum correlations

    NASA Astrophysics Data System (ADS)

    Man'ko, V. I.

    2008-08-01

    Semigroups of stochastic and bistochastic matrices constructed by means of spin tomograms or tomographic probabilities and their relations to the problem of Bell's inequalities and entanglement are reviewed. The probability determining the quantum state of spins and the probability densities determining the quantum states of particles with continuous variables are considered. Entropies for semigroups of stochastic and bisctochastic matrices are studied, in view of both the Shannon information entropy and its generalization like Rényi entropy. Qubit portraits of qudit states are discussed in the connection with the problem of Bell's inequality violation for entangled states.

  12. Probability distributions for a surjective unimodal map

    NASA Astrophysics Data System (ADS)

    Sun, Hongyan; Wang, Long

    1996-04-01

    In this paper we show that the probability distributions for a surjective unimodal map can be classified into three types, δ function, asymmetric and symmetric type; by identifying the binary structures of its initial values. The Borel's normal number theorem is equivalent or prior to the Frobenius-Perron operator in analyzing the probability distributions for this kind of maps, and in particular we can constitute a multifractal probability distribution from the surjective tent map by selecting a non- Borel's normal number as the initial value.

  13. Robust location and spread measures for nonparametric probability density function estimation.

    PubMed

    López-Rubio, Ezequiel

    2009-10-01

    Robustness against outliers is a desirable property of any unsupervised learning scheme. In particular, probability density estimators benefit from incorporating this feature. A possible strategy to achieve this goal is to substitute the sample mean and the sample covariance matrix by more robust location and spread estimators. Here we use the L1-median to develop a nonparametric probability density function (PDF) estimator. We prove its most relevant properties, and we show its performance in density estimation and classification applications. PMID:19885963

  14. Neutron initiation probability in fast burst reactor

    SciTech Connect

    Liu, X.; Du, J.; Xie, Q.; Fan, X.

    2012-07-01

    Based on the probability balance of neutron random events in multiply system, the four random process of neutron in prompt super-critical is described and then the equation of neutron initiation probability W(r,E,{Omega},t) is deduced. On the assumption of static, slightly prompt super-critical and the two factorial approximation, the formula of the average probability of 'one' neutron is derived which is the same with the result derived from the point model. The MC simulation using point model is applied in Godiva- II and CFBR-II, and the simulation result of one neutron initiation is well consistent with the theory that the initiation probability of Godiva- II inverted commas CFBR-II burst reactor are 0.00032, 0.00027 respectively on the ordinary burst operation. (authors)

  15. A Survey of Tables of Probability Distributions

    PubMed Central

    Kacker, Raghu; Olkin, Ingram

    2005-01-01

    This article is a survey of the tables of probability distributions published about or after the publication in 1964 of the Handbook of Mathematical Functions, edited by Abramowitz and Stegun PMID:27308104

  16. Characteristic length of the knotting probability revisited

    NASA Astrophysics Data System (ADS)

    Uehara, Erica; Deguchi, Tetsuo

    2015-09-01

    We present a self-avoiding polygon (SAP) model for circular DNA in which the radius of impermeable cylindrical segments corresponds to the screening length of double-stranded DNA surrounded by counter ions. For the model we evaluate the probability for a generated SAP with N segments having a given knot K through simulation. We call it the knotting probability of a knot K with N segments for the SAP model. We show that when N is large the most significant factor in the knotting probability is given by the exponentially decaying part exp(-N/NK), where the estimates of parameter NK are consistent with the same value for all the different knots we investigated. We thus call it the characteristic length of the knotting probability. We give formulae expressing the characteristic length as a function of the cylindrical radius rex, i.e. the screening length of double-stranded DNA.

  17. Inclusion probability with dropout: an operational formula.

    PubMed

    Milot, E; Courteau, J; Crispino, F; Mailly, F

    2015-05-01

    In forensic genetics, a mixture of two or more contributors to a DNA profile is often interpreted using the inclusion probabilities theory. In this paper, we present a general formula for estimating the probability of inclusion (PI, also known as the RMNE probability) from a subset of visible alleles when dropouts are possible. This one-locus formula can easily be extended to multiple loci using the cumulative probability of inclusion. We show that an exact formulation requires fixing the number of contributors, hence to slightly modify the classic interpretation of the PI. We discuss the implications of our results for the enduring debate over the use of PI vs likelihood ratio approaches within the context of low template amplifications. PMID:25559642

  18. Determining Probabilities by Examining Underlying Structure.

    ERIC Educational Resources Information Center

    Norton, Robert M.

    2001-01-01

    Discusses how dice games pose fairness issues that appeal to students and examines a structure for three games involving two dice in a way that leads directly to the theoretical probabilities for all possible outcomes. (YDS)

  19. Probability tree algorithm for general diffusion processes

    NASA Astrophysics Data System (ADS)

    Ingber, Lester; Chen, Colleen; Mondescu, Radu Paul; Muzzall, David; Renedo, Marco

    2001-11-01

    Motivated by path-integral numerical solutions of diffusion processes, PATHINT, we present a tree algorithm, PATHTREE, which permits extremely fast accurate computation of probability distributions of a large class of general nonlinear diffusion processes.

  20. Transition Probability and the ESR Experiment

    ERIC Educational Resources Information Center

    McBrierty, Vincent J.

    1974-01-01

    Discusses the use of a modified electron spin resonance apparatus to demonstrate some features of the expression for the transition probability per second between two energy levels. Applications to the third year laboratory program are suggested. (CC)

  1. On Convergent Probability of a Random Walk

    ERIC Educational Resources Information Center

    Lee, Y.-F.; Ching, W.-K.

    2006-01-01

    This note introduces an interesting random walk on a straight path with cards of random numbers. The method of recurrent relations is used to obtain the convergent probability of the random walk with different initial positions.

  2. Non-Gaussian Photon Probability Distribution

    NASA Astrophysics Data System (ADS)

    Solomon, Benjamin T.

    2010-01-01

    This paper investigates the axiom that the photon's probability distribution is a Gaussian distribution. The Airy disc empirical evidence shows that the best fit, if not exact, distribution is a modified Gamma mΓ distribution (whose parameters are α = r, βr/√u ) in the plane orthogonal to the motion of the photon. This modified Gamma distribution is then used to reconstruct the probability distributions along the hypotenuse from the pinhole, arc from the pinhole, and a line parallel to photon motion. This reconstruction shows that the photon's probability distribution is not a Gaussian function. However, under certain conditions, the distribution can appear to be Normal, thereby accounting for the success of quantum mechanics. This modified Gamma distribution changes with the shape of objects around it and thus explains how the observer alters the observation. This property therefore places additional constraints to quantum entanglement experiments. This paper shows that photon interaction is a multi-phenomena effect consisting of the probability to interact Pi, the probabilistic function and the ability to interact Ai, the electromagnetic function. Splitting the probability function Pi from the electromagnetic function Ai enables the investigation of the photon behavior from a purely probabilistic Pi perspective. The Probabilistic Interaction Hypothesis is proposed as a consistent method for handling the two different phenomena, the probability function Pi and the ability to interact Ai, thus redefining radiation shielding, stealth or cloaking, and invisibility as different effects of a single phenomenon Pi of the photon probability distribution. Sub wavelength photon behavior is successfully modeled as a multi-phenomena behavior. The Probabilistic Interaction Hypothesis provides a good fit to Otoshi's (1972) microwave shielding, Schurig et al. (2006) microwave cloaking, and Oulton et al. (2008) sub wavelength confinement; thereby providing a strong case that

  3. Robust satisficing and the probability of survival

    NASA Astrophysics Data System (ADS)

    Ben-Haim, Yakov

    2014-01-01

    Concepts of robustness are sometimes employed when decisions under uncertainty are made without probabilistic information. We present a theorem that establishes necessary and sufficient conditions for non-probabilistic robustness to be equivalent to the probability of satisfying the specified outcome requirements. When this holds, probability is enhanced (or maximised) by enhancing (or maximising) robustness. Two further theorems establish important special cases. These theorems have implications for success or survival under uncertainty. Applications to foraging and finance are discussed.

  4. The spline probability hypothesis density filter

    NASA Astrophysics Data System (ADS)

    Sithiravel, Rajiv; Tharmarasa, Ratnasingham; McDonald, Mike; Pelletier, Michel; Kirubarajan, Thiagalingam

    2012-06-01

    The Probability Hypothesis Density Filter (PHD) is a multitarget tracker for recursively estimating the number of targets and their state vectors from a set of observations. The PHD filter is capable of working well in scenarios with false alarms and missed detections. Two distinct PHD filter implementations are available in the literature: the Sequential Monte Carlo Probability Hypothesis Density (SMC-PHD) and the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filters. The SMC-PHD filter uses particles to provide target state estimates, which can lead to a high computational load, whereas the GM-PHD filter does not use particles, but restricts to linear Gaussian mixture models. The SMC-PHD filter technique provides only weighted samples at discrete points in the state space instead of a continuous estimate of the probability density function of the system state and thus suffers from the well-known degeneracy problem. This paper proposes a B-Spline based Probability Hypothesis Density (S-PHD) filter, which has the capability to model any arbitrary probability density function. The resulting algorithm can handle linear, non-linear, Gaussian, and non-Gaussian models and the S-PHD filter can also provide continuous estimates of the probability density function of the system state. In addition, by moving the knots dynamically, the S-PHD filter ensures that the splines cover only the region where the probability of the system state is significant, hence the high efficiency of the S-PHD filter is maintained at all times. Also, unlike the SMC-PHD filter, the S-PHD filter is immune to the degeneracy problem due to its continuous nature. The S-PHD filter derivations and simulations are provided in this paper.

  5. Infants Segment Continuous Events Using Transitional Probabilities

    ERIC Educational Resources Information Center

    Stahl, Aimee E.; Romberg, Alexa R.; Roseberry, Sarah; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

    2014-01-01

    Throughout their 1st year, infants adeptly detect statistical structure in their environment. However, little is known about whether statistical learning is a primary mechanism for event segmentation. This study directly tests whether statistical learning alone is sufficient to segment continuous events. Twenty-eight 7- to 9-month-old infants…

  6. Site occupancy models with heterogeneous detection probabilities

    USGS Publications Warehouse

    Royle, J. Andrew

    2006-01-01

    Models for estimating the probability of occurrence of a species in the presence of imperfect detection are important in many ecological disciplines. In these ?site occupancy? models, the possibility of heterogeneity in detection probabilities among sites must be considered because variation in abundance (and other factors) among sampled sites induces variation in detection probability (p). In this article, I develop occurrence probability models that allow for heterogeneous detection probabilities by considering several common classes of mixture distributions for p. For any mixing distribution, the likelihood has the general form of a zero-inflated binomial mixture for which inference based upon integrated likelihood is straightforward. A recent paper by Link (2003, Biometrics 59, 1123?1130) demonstrates that in closed population models used for estimating population size, different classes of mixture distributions are indistinguishable from data, yet can produce very different inferences about population size. I demonstrate that this problem can also arise in models for estimating site occupancy in the presence of heterogeneous detection probabilities. The implications of this are discussed in the context of an application to avian survey data and the development of animal monitoring programs.

  7. The cumulative reaction probability as eigenvalue problem

    NASA Astrophysics Data System (ADS)

    Manthe, Uwe; Miller, William H.

    1993-09-01

    It is shown that the cumulative reaction probability for a chemical reaction can be expressed (absolutely rigorously) as N(E)=∑kpk(E), where {pk} are the eigenvalues of a certain Hermitian matrix (or operator). The eigenvalues {pk} all lie between 0 and 1 and thus have the interpretation as probabilities, eigenreaction probabilities which may be thought of as the rigorous generalization of the transmission coefficients for the various states of the activated complex in transition state theory. The eigenreaction probabilities {pk} can be determined by diagonalizing a matrix that is directly available from the Hamiltonian matrix itself. It is also shown how a very efficient iterative method can be used to determine the eigenreaction probabilities for problems that are too large for a direct diagonalization to be possible. The number of iterations required is much smaller than that of previous methods, approximately the number of eigenreaction probabilities that are significantly different from zero. All of these new ideas are illustrated by application to three model problems—transmission through a one-dimensional (Eckart potential) barrier, the collinear H+H2→H2+H reaction, and the three-dimensional version of this reaction for total angular momentum J=0.

  8. The Estimation of Tree Posterior Probabilities Using Conditional Clade Probability Distributions

    PubMed Central

    Larget, Bret

    2013-01-01

    In this article I introduce the idea of conditional independence of separated subtrees as a principle by which to estimate the posterior probability of trees using conditional clade probability distributions rather than simple sample relative frequencies. I describe an algorithm for these calculations and software which implements these ideas. I show that these alternative calculations are very similar to simple sample relative frequencies for high probability trees but are substantially more accurate for relatively low probability trees. The method allows the posterior probability of unsampled trees to be calculated when these trees contain only clades that are in other sampled trees. Furthermore, the method can be used to estimate the total probability of the set of sampled trees which provides a measure of the thoroughness of a posterior sample. [Bayesian phylogenetics; conditional clade distributions; improved accuracy; posterior probabilities of trees.] PMID:23479066

  9. The Problem with Probability: Why rare hazards feel even rarer

    NASA Astrophysics Data System (ADS)

    Thompson, K. J.

    2013-12-01

    Even as scientists improve the accuracy of their forecasts for large-scale events like natural hazards and climate change, a gap remains between the confidence the scientific community has in those estimates, and the skepticism with which the lay public tends to view statements of uncertainty. Beyond the challenges of helping the public to understand probabilistic forecasts lies yet another barrier to effective communication: the fact that even when humans can estimate or state the correct probability of a rare event, we tend to distort that probability in our minds, acting as if the likelihood is higher or lower than we know it to be. A half century of empirical research in psychology and economics leaves us with a clear view of the ways that people interpret stated, or described probabilities--e.g., "There is a 6% chance of a Northridge-sized earthquake occurring in your area in the next 10 years." In the past decade, the focus of cognitive scientists has turned to the other method humans use to learn probabilities: intuitively estimating the chances of a rare event by assessing our personal experience with various outcomes. While it is well understood that described probabilities are over-weighted when they are small (e.g., a 5% chance might be treated more like a 10% or 12% chance), it appears that in many cases, experienced rare probabilities are in fact under-weighted. This distortion is not an under-estimation, and therefore cannot be prevented by reminding people of the described probability. This paper discusses the mechanisms and effects of this difference in the way probability is used when a number is provided, as opposed to when the frequency of a rare event is intuited. In addition to recommendations based on the current state of research on the way people appear to make decisions from experience, suggestions are made for how to present probabilistic information to best take advantage of people's tendencies to either amplify risk or ignore it, as well

  10. Minimal entropy probability paths between genome families.

    PubMed

    Ahlbrandt, Calvin; Benson, Gary; Casey, William

    2004-05-01

    We develop a metric for probability distributions with applications to biological sequence analysis. Our distance metric is obtained by minimizing a functional defined on the class of paths over probability measures on N categories. The underlying mathematical theory is connected to a constrained problem in the calculus of variations. The solution presented is a numerical solution, which approximates the true solution in a set of cases called rich paths where none of the components of the path is zero. The functional to be minimized is motivated by entropy considerations, reflecting the idea that nature might efficiently carry out mutations of genome sequences in such a way that the increase in entropy involved in transformation is as small as possible. We characterize sequences by frequency profiles or probability vectors, in the case of DNA where N is 4 and the components of the probability vector are the frequency of occurrence of each of the bases A, C, G and T. Given two probability vectors a and b, we define a distance function based as the infimum of path integrals of the entropy function H( p) over all admissible paths p(t), 0 < or = t< or =1, with p(t) a probability vector such that p(0)=a and p(1)=b. If the probability paths p(t) are parameterized as y(s) in terms of arc length s and the optimal path is smooth with arc length L, then smooth and "rich" optimal probability paths may be numerically estimated by a hybrid method of iterating Newton's method on solutions of a two point boundary value problem, with unknown distance L between the abscissas, for the Euler-Lagrange equations resulting from a multiplier rule for the constrained optimization problem together with linear regression to improve the arc length estimate L. Matlab code for these numerical methods is provided which works only for "rich" optimal probability vectors. These methods motivate a definition of an elementary distance function which is easier and faster to calculate, works on non

  11. Computing Earthquake Probabilities on Global Scales

    NASA Astrophysics Data System (ADS)

    Holliday, James R.; Graves, William R.; Rundle, John B.; Turcotte, Donald L.

    2016-03-01

    Large devastating events in systems such as earthquakes, typhoons, market crashes, electricity grid blackouts, floods, droughts, wars and conflicts, and landslides can be unexpected and devastating. Events in many of these systems display frequency-size statistics that are power laws. Previously, we presented a new method for calculating probabilities for large events in systems such as these. This method counts the number of small events since the last large event and then converts this count into a probability by using a Weibull probability law. We applied this method to the calculation of large earthquake probabilities in California-Nevada, USA. In that study, we considered a fixed geographic region and assumed that all earthquakes within that region, large magnitudes as well as small, were perfectly correlated. In the present article, we extend this model to systems in which the events have a finite correlation length. We modify our previous results by employing the correlation function for near mean field systems having long-range interactions, an example of which is earthquakes and elastic interactions. We then construct an application of the method and show examples of computed earthquake probabilities.

  12. The role of probabilities in physics.

    PubMed

    Le Bellac, Michel

    2012-09-01

    Although modern physics was born in the XVIIth century as a fully deterministic theory in the form of Newtonian mechanics, the use of probabilistic arguments turned out later on to be unavoidable. Three main situations can be distinguished. (1) When the number of degrees of freedom is very large, on the order of Avogadro's number, a detailed dynamical description is not possible, and in fact not useful: we do not care about the velocity of a particular molecule in a gas, all we need is the probability distribution of the velocities. This statistical description introduced by Maxwell and Boltzmann allows us to recover equilibrium thermodynamics, gives a microscopic interpretation of entropy and underlies our understanding of irreversibility. (2) Even when the number of degrees of freedom is small (but larger than three) sensitivity to initial conditions of chaotic dynamics makes determinism irrelevant in practice, because we cannot control the initial conditions with infinite accuracy. Although die tossing is in principle predictable, the approach to chaotic dynamics in some limit implies that our ignorance of initial conditions is translated into a probabilistic description: each face comes up with probability 1/6. (3) As is well-known, quantum mechanics is incompatible with determinism. However, quantum probabilities differ in an essential way from the probabilities introduced previously: it has been shown from the work of John Bell that quantum probabilities are intrinsic and cannot be given an ignorance interpretation based on a hypothetical deeper level of description. PMID:22609725

  13. Effects of Neutrino Decay on Oscillation Probabilities

    NASA Astrophysics Data System (ADS)

    Leonard, Kayla; de Gouvêa, André

    2016-01-01

    It is now well accepted that neutrinos oscillate as a quantum mechanical result of a misalignment between their mass-eigenstates and the flavor-eigenstates. We study neutrino decay—the idea that there may be new, light states that the three Standard Model flavors may be able to decay into. We consider what effects this neutrino decay would have on the observed oscillation probabilities.The Hamiltonian governs how the states change with time, so we use it to calculate an oscillation amplitude, and from that, the oscillation probability. We simplify the theoretical probabilities using results from experimental data, such as the neutrino mixing angles and mass differences. By exploring what values of the decay parameters are physically allowable, we can begin to understand just how large the decay parameters can be. We compare the probabilities in the case of no neutrino decay and in the case of maximum neutrino decay to determine how much of an effect neutrino decay could have on observations, and discuss the ability of future experiments to detect these differences.We also examine neutrino decay in the realm of CP invariance, and found that it is a new source of CP violation. Our work indicates that there is a difference in the oscillation probabilities between particle transitions and their corresponding antiparticle transitions. If neutrino decay were proven true, it could be an important factor in understanding leptogenesis and the particle-antiparticle asymmetry present in our Universe.

  14. Reconstructing the prior probabilities of allelic phylogenies.

    PubMed Central

    Golding, G Brian

    2002-01-01

    In general when a phylogeny is reconstructed from DNA or protein sequence data, it makes use only of the probabilities of obtaining some phylogeny given a collection of data. It is also possible to determine the prior probabilities of different phylogenies. This information can be of use in analyzing the biological causes for the observed divergence of sampled taxa. Unusually "rare" topologies for a given data set may be indicative of different biological forces acting. A recursive algorithm is presented that calculates the prior probabilities of a phylogeny for different allelic samples and for different phylogenies. This method is a straightforward extension of Ewens' sample distribution. The probability of obtaining each possible sample according to Ewens' distribution is further subdivided into each of the possible phylogenetic topologies. These probabilities depend not only on the identity of the alleles and on 4N(mu) (four times the effective population size times the neutral mutation rate) but also on the phylogenetic relationships among the alleles. Illustrations of the algorithm are given to demonstrate how different phylogenies are favored under different conditions. PMID:12072482

  15. Approximation of Failure Probability Using Conditional Sampling

    NASA Technical Reports Server (NTRS)

    Giesy. Daniel P.; Crespo, Luis G.; Kenney, Sean P.

    2008-01-01

    In analyzing systems which depend on uncertain parameters, one technique is to partition the uncertain parameter domain into a failure set and its complement, and judge the quality of the system by estimating the probability of failure. If this is done by a sampling technique such as Monte Carlo and the probability of failure is small, accurate approximation can require so many sample points that the computational expense is prohibitive. Previous work of the authors has shown how to bound the failure event by sets of such simple geometry that their probabilities can be calculated analytically. In this paper, it is shown how to make use of these failure bounding sets and conditional sampling within them to substantially reduce the computational burden of approximating failure probability. It is also shown how the use of these sampling techniques improves the confidence intervals for the failure probability estimate for a given number of sample points and how they reduce the number of sample point analyses needed to achieve a given level of confidence.

  16. Sampling Quantum Nonlocal Correlations with High Probability

    NASA Astrophysics Data System (ADS)

    González-Guillén, C. E.; Jiménez, C. H.; Palazuelos, C.; Villanueva, I.

    2016-05-01

    It is well known that quantum correlations for bipartite dichotomic measurements are those of the form {γ=(< u_i,v_jrangle)_{i,j=1}^n}, where the vectors u i and v j are in the unit ball of a real Hilbert space. In this work we study the probability of the nonlocal nature of these correlations as a function of {α=m/n}, where the previous vectors are sampled according to the Haar measure in the unit sphere of {R^m}. In particular, we prove the existence of an {α_0 > 0} such that if {α≤ α_0}, {γ} is nonlocal with probability tending to 1 as {n→ ∞}, while for {α > 2}, {γ} is local with probability tending to 1 as {n→ ∞}.

  17. Local Directed Percolation Probability in Two Dimensions

    NASA Astrophysics Data System (ADS)

    Inui, Norio; Konno, Norio; Komatsu, Genichi; Kameoka, Koichi

    1998-01-01

    Using the series expansion method and Monte Carlo simulation,we study the directed percolation probability on the square lattice Vn0=\\{ (x,y) \\in {Z}2:x+y=even, 0 ≤ y ≤ n, - y ≤ x ≤ y \\}.We calculate the local percolationprobability Pnl defined as the connection probability between theorigin and a site (0,n). The critical behavior of P∞lis clearly different from the global percolation probability P∞g characterized by a critical exponent βg.An analysis based on the Padé approximants shows βl=2βg.In addition, we find that the series expansion of P2nl can be expressed as a function of Png.

  18. Classical and Quantum Probability for Biologists - Introduction

    NASA Astrophysics Data System (ADS)

    Khrennikov, Andrei.

    2010-01-01

    The aim of this review (oriented to biologists looking for applications of QM) is to provide a detailed comparative analysis of classical (Kolmogorovian) and quantum (Dirac-von Neumann) models. We will stress differences in the definition of conditional probability and as a consequence in the structures of matrices of transition probabilities, especially the condition of double stochasticity which arises naturally in QM. One of the most fundamental differences between two models is deformation of the classical formula of total probability (FTP) which plays an important role in statistics and decision making. An additional term appears in the QM-version of FTP - so called interference term. Finally, we discuss Bell's inequality and show that the common viewpoint that its violation induces either nonlocality or "death of realism" has not been completely justified. For us it is merely a sign of non-Kolmogorovianity of probabilistic data collected in a few experiments with incompatible setups of measurement devices.

  19. Detection probability of EBPSK-MODEM system

    NASA Astrophysics Data System (ADS)

    Yao, Yu; Wu, Lenan

    2016-07-01

    Since the impacting filter-based receiver is able to transform phase modulation into amplitude peak, a simple threshold decision can detect the Extend-Binary Phase Shift Keying (EBPSK) modulated ranging signal in noise environment. In this paper, an analysis of the EBPSK-MODEM system output gives the probability density function for EBPSK modulated signals plus noise. The equation of detection probability (pd) for fluctuating and non-fluctuating targets has been deduced. Also, a comparison of the pd for the EBPSK-MODEM system and pulse radar receiver is made, and some results are plotted. Moreover, the probability curves of such system with several modulation parameters are analysed. When modulation parameter is not smaller than 6, the detection performance of EBPSK-MODEM system is more excellent than traditional radar system. In addition to theoretical considerations, computer simulations are provided for illustrating the performance.

  20. Explosion probability of unexploded ordnance: expert beliefs.

    PubMed

    MacDonald, Jacqueline Anne; Small, Mitchell J; Morgan, M G

    2008-08-01

    This article reports on a study to quantify expert beliefs about the explosion probability of unexploded ordnance (UXO). Some 1,976 sites at closed military bases in the United States are contaminated with UXO and are slated for cleanup, at an estimated cost of $15-140 billion. Because no available technology can guarantee 100% removal of UXO, information about explosion probability is needed to assess the residual risks of civilian reuse of closed military bases and to make decisions about how much to invest in cleanup. This study elicited probability distributions for the chance of UXO explosion from 25 experts in explosive ordnance disposal, all of whom have had field experience in UXO identification and deactivation. The study considered six different scenarios: three different types of UXO handled in two different ways (one involving children and the other involving construction workers). We also asked the experts to rank by sensitivity to explosion 20 different kinds of UXO found at a case study site at Fort Ord, California. We found that the experts do not agree about the probability of UXO explosion, with significant differences among experts in their mean estimates of explosion probabilities and in the amount of uncertainty that they express in their estimates. In three of the six scenarios, the divergence was so great that the average of all the expert probability distributions was statistically indistinguishable from a uniform (0, 1) distribution-suggesting that the sum of expert opinion provides no information at all about the explosion risk. The experts' opinions on the relative sensitivity to explosion of the 20 UXO items also diverged. The average correlation between rankings of any pair of experts was 0.41, which, statistically, is barely significant (p= 0.049) at the 95% confidence level. Thus, one expert's rankings provide little predictive information about another's rankings. The lack of consensus among experts suggests that empirical studies

  1. Monte Carlo simulation of scenario probability distributions

    SciTech Connect

    Glaser, R.

    1996-10-23

    Suppose a scenario of interest can be represented as a series of events. A final result R may be viewed then as the intersection of three events, A, B, and C. The probability of the result P(R) in this case is the product P(R) = P(A) P(B {vert_bar} A) P(C {vert_bar} A {intersection} B). An expert may be reluctant to estimate P(R) as a whole yet agree to supply his notions of the component probabilities in the form of prior distributions. Each component prior distribution may be viewed as the stochastic characterization of the expert`s uncertainty regarding the true value of the component probability. Mathematically, the component probabilities are treated as independent random variables and P(R) as their product; the induced prior distribution for P(R) is determined which characterizes the expert`s uncertainty regarding P(R). It may be both convenient and adequate to approximate the desired distribution by Monte Carlo simulation. Software has been written for this task that allows a variety of component priors that experts with good engineering judgment might feel comfortable with. The priors are mostly based on so-called likelihood classes. The software permits an expert to choose for a given component event probability one of six types of prior distributions, and the expert specifies the parameter value(s) for that prior. Each prior is unimodal. The expert essentially decides where the mode is, how the probability is distributed in the vicinity of the mode, and how rapidly it attenuates away. Limiting and degenerate applications allow the expert to be vague or precise.

  2. Quantum probability and quantum decision-making.

    PubMed

    Yukalov, V I; Sornette, D

    2016-01-13

    A rigorous general definition of quantum probability is given, which is valid not only for elementary events but also for composite events, for operationally testable measurements as well as for inconclusive measurements, and also for non-commuting observables in addition to commutative observables. Our proposed definition of quantum probability makes it possible to describe quantum measurements and quantum decision-making on the same common mathematical footing. Conditions are formulated for the case when quantum decision theory reduces to its classical counterpart and for the situation where the use of quantum decision theory is necessary. PMID:26621989

  3. Steering in spin tomographic probability representation

    NASA Astrophysics Data System (ADS)

    Man'ko, V. I.; Markovich, L. A.

    2016-09-01

    The steering property known for two-qubit state in terms of specific inequalities for the correlation function is translated for the state of qudit with the spin j = 3 / 2. Since most steering detection inequalities are based on the correlation functions we introduce analogs of such functions for the single qudit systems. The tomographic probability representation for the qudit states is applied. The connection between the correlation function in the two-qubit system and the single qudit is presented in an integral form with an intertwining kernel calculated explicitly in tomographic probability terms.

  4. Practical algorithmic probability: an image inpainting example

    NASA Astrophysics Data System (ADS)

    Potapov, Alexey; Scherbakov, Oleg; Zhdanov, Innokentii

    2013-12-01

    Possibility of practical application of algorithmic probability is analyzed on an example of image inpainting problem that precisely corresponds to the prediction problem. Such consideration is fruitful both for the theory of universal prediction and practical image inpaiting methods. Efficient application of algorithmic probability implies that its computation is essentially optimized for some specific data representation. In this paper, we considered one image representation, namely spectral representation, for which an image inpainting algorithm is proposed based on the spectrum entropy criterion. This algorithm showed promising results in spite of very simple representation. The same approach can be used for introducing ALP-based criterion for more powerful image representations.

  5. Flood frequency: expected and unexpected probabilities

    USGS Publications Warehouse

    Thomas, D.M.

    1976-01-01

    Flood-frequency curves may be defined either with or without an ' expeced probability ' adustment; and the two curves differ in the way that they attempt to average the time-sampling uncertainties. A curve with no adustment is shown to estimate a median value of both discharge and frequency of occurrence, while an expected probability curve is shown to estimate a mean frequency of flood years. The attributes and constraints of the two types of curves for various uses are discussed. 

  6. Electric quadrupole transition probabilities for atomic lithium

    SciTech Connect

    Çelik, Gültekin; Gökçe, Yasin; Yıldız, Murat

    2014-05-15

    Electric quadrupole transition probabilities for atomic lithium have been calculated using the weakest bound electron potential model theory (WBEPMT). We have employed numerical non-relativistic Hartree–Fock wavefunctions for expectation values of radii and the necessary energy values have been taken from the compilation at NIST. The results obtained with the present method agree very well with the Coulomb approximation results given by Caves (1975). Moreover, electric quadrupole transition probability values not existing in the literature for some highly excited levels have been obtained using the WBEPMT.

  7. Non-Gaussian Photon Probability Distribution

    SciTech Connect

    Solomon, Benjamin T.

    2010-01-28

    This paper investigates the axiom that the photon's probability distribution is a Gaussian distribution. The Airy disc empirical evidence shows that the best fit, if not exact, distribution is a modified Gamma mGAMMA distribution (whose parameters are alpha = r, betar/sq root(u)) in the plane orthogonal to the motion of the photon. This modified Gamma distribution is then used to reconstruct the probability distributions along the hypotenuse from the pinhole, arc from the pinhole, and a line parallel to photon motion. This reconstruction shows that the photon's probability distribution is not a Gaussian function. However, under certain conditions, the distribution can appear to be Normal, thereby accounting for the success of quantum mechanics. This modified Gamma distribution changes with the shape of objects around it and thus explains how the observer alters the observation. This property therefore places additional constraints to quantum entanglement experiments. This paper shows that photon interaction is a multi-phenomena effect consisting of the probability to interact P{sub i}, the probabilistic function and the ability to interact A{sub i}, the electromagnetic function. Splitting the probability function P{sub i} from the electromagnetic function A{sub i} enables the investigation of the photon behavior from a purely probabilistic P{sub i} perspective. The Probabilistic Interaction Hypothesis is proposed as a consistent method for handling the two different phenomena, the probability function P{sub i} and the ability to interact A{sub i}, thus redefining radiation shielding, stealth or cloaking, and invisibility as different effects of a single phenomenon P{sub i} of the photon probability distribution. Sub wavelength photon behavior is successfully modeled as a multi-phenomena behavior. The Probabilistic Interaction Hypothesis provides a good fit to Otoshi's (1972) microwave shielding, Schurig et al.(2006) microwave cloaking, and Oulton et al.(2008) sub

  8. Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces

    NASA Astrophysics Data System (ADS)

    Vourdas, A.

    2014-08-01

    The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator {{D}}(H_1, H_2), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors {{P}}(H_1), {{P}}(H_2), to the subspaces H1, H2. As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities.

  9. Quantum probabilities as Dempster-Shafer probabilities in the lattice of subspaces

    SciTech Connect

    Vourdas, A.

    2014-08-15

    The orthocomplemented modular lattice of subspaces L[H(d)], of a quantum system with d-dimensional Hilbert space H(d), is considered. A generalized additivity relation which holds for Kolmogorov probabilities is violated by quantum probabilities in the full lattice L[H(d)] (it is only valid within the Boolean subalgebras of L[H(d)]). This suggests the use of more general (than Kolmogorov) probability theories, and here the Dempster-Shafer probability theory is adopted. An operator D(H{sub 1},H{sub 2}), which quantifies deviations from Kolmogorov probability theory is introduced, and it is shown to be intimately related to the commutator of the projectors P(H{sub 1}),P(H{sub 2}), to the subspaces H{sub 1}, H{sub 2}. As an application, it is shown that the proof of the inequalities of Clauser, Horne, Shimony, and Holt for a system of two spin 1/2 particles is valid for Kolmogorov probabilities, but it is not valid for Dempster-Shafer probabilities. The violation of these inequalities in experiments supports the interpretation of quantum probabilities as Dempster-Shafer probabilities.

  10. Math Academy: Are You Game? Explorations in Probability. Supplemental Math Materials for Grades 3-6

    ERIC Educational Resources Information Center

    Rimbey, Kimberly

    2007-01-01

    Created by teachers for teachers, the Math Academy tools and activities included in this booklet were designed to create hands-on activities and a fun learning environment for the teaching of mathematics to the students. This booklet contains the themed program "Are You Game? Math Academy--Explorations in Probability," which teachers can use to…