Results for 'Statistics - Computation'

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  1.  4
    Geometry driven statistics.Ian L. Dryden & John T. Kent (eds.) - 2015 - Chichester, West Sussex: Wiley.
    A timely collection of advanced, original material in the area of statistical methodology motivated by geometric problems, dedicated to the influential work of Kanti V. Mardia This volume celebrates Kanti V. Mardia's long and influential career in statistics. A common theme unifying much of Mardia’s work is the importance of geometry in statistics, and to highlight the areas emphasized in his research this book brings together 16 contributions from high-profile researchers in the field. Geometry Driven Statistics covers (...)
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  2. Improving Bayesian statistics understanding in the age of Big Data with the bayesvl R package.Quan-Hoang Vuong, Viet-Phuong La, Minh-Hoang Nguyen, Manh-Toan Ho, Manh-Tung Ho & Peter Mantello - 2020 - Software Impacts 4 (1):100016.
    The exponential growth of social data both in volume and complexity has increasingly exposed many of the shortcomings of the conventional frequentist approach to statistics. The scientific community has called for careful usage of the approach and its inference. Meanwhile, the alternative method, Bayesian statistics, still faces considerable barriers toward a more widespread application. The bayesvl R package is an open program, designed for implementing Bayesian modeling and analysis using the Stan language’s no-U-turn (NUTS) sampler. The package combines (...)
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  3.  30
    The Foundations of Statistics.Leonard J. Savage - 1954 - Wiley Publications in Statistics.
    Classic analysis of the subject and the development of personal probability; one of the greatest controversies in modern statistcal thought.
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  4.  19
    The Emergence of Modern Statistics in Agricultural Science: Analysis of Variance, Experimental Design and the Reshaping of Research at Rothamsted Experimental Station, 1919–1933.Giuditta Parolini - 2015 - Journal of the History of Biology 48 (2):301-335.
    During the twentieth century statistical methods have transformed research in the experimental and social sciences. Qualitative evidence has largely been replaced by quantitative results and the tools of statistical inference have helped foster a new ideal of objectivity in scientific knowledge. The paper will investigate this transformation by considering the genesis of analysis of variance and experimental design, statistical methods nowadays taught in every elementary course of statistics for the experimental and social sciences. These methods were developed by the (...)
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  5.  8
    Statistics of intuitionistic versus classical logics.Zofia Kostrzycka & Marek Zaionc - 2004 - Studia Logica 76 (3):307 - 328.
    For the given logical calculus we investigate the proportion of the number of true formulas of a certain length n to the number of all formulas of such length. We are especially interested in asymptotic behavior of this fraction when n tends to infinity. If the limit exists it is represented by a real number between 0 and 1 which we may call the density of truth for the investigated logic. In this paper we apply this approach to the intuitionistic (...)
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  6.  7
    Psi, statistics, and society.Jessica Utts - 1987 - Behavioral and Brain Sciences 10 (4):615.
  7.  58
    Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing.Barry J. Devereux, Kirsten I. Taylor, Billi Randall, Jeroen Geertzen & Lorraine K. Tyler - 2016 - Cognitive Science 40 (2):325-350.
    Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts’ features—the number of concepts they occur in and likelihood of co-occurrence —determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech-to-meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision (...)
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  8.  9
    Probability, Induction and Statistics: The Art of Guessing.Bruno De Finetti - 1972 - New York: John Wiley.
  9.  37
    Combining Statistics and Case-Based Reasoning for Medical Research.Rainer Schmidt & Olga Vorobieva - 2009 - In L. Magnani (ed.), computational intelligence. pp. 673--696.
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  10. Semantics, Hermenutics, Statistics: Some Reflections on the Semantic Web.Graham White - forthcoming - Proceedings of HCI2011.
    We start with the ambition -- dating back to the early days of the semantic web -- of assembling a significant portion human knowledge into a contradiction-free form using semantic web technology. We argue that this would not be desirable, because there are concepts, known as essentially contested concepts, whose definitions are contentious due to deep-seated ethical disagreements. Further, we argue that the ninetenth century hermeneutical tradition has a great deal to say, both about the ambition, and about why it (...)
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  11.  5
    Psychology, statistics, and analytical epistemology.Richard E. Nisbett & Paul Thagard - 1983 - Behavioral and Brain Sciences 6 (2):257-258.
  12. I will abbreviate the causal law, C causes E by C—> E. Notice that C and E are to be filled in by general terms, and not names of particulars; for example, Force causes motion or Aspinn relieves hendache. The generic law C causes E is not to be understood as a universally quantified law about particulars, even about.Ii Statistical Analyses Of Causation - 1999 - In Michael Tooley (ed.), Laws of nature, causation, and supervenience. New York: Garland. pp. 246.
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  13.  4
    Using balance statistics to determine the optimal number of controls in matching studies.Ariel Linden & Steven J. Samuels - 2013 - Journal of Evaluation in Clinical Practice 19 (5):968-975.
  14. La Estadística Neutrosófica es una extensión de la Estadística de Intervalos, mientras que la Estadística Plitogénica es la forma más general de estadística. (Cuarta versión). Neutrosophic Statistics is an extension of Interval Statistics, while Plitogenic Statistics is the most general form of statistics (Fourth version).Florentin Smarandache - 2022 - Neutrosophic Computing and Machine Learning 23 (1):21-38.
    In this paper we show that Neutrosophic Statistics is an extension of Interval Statistics, since it deals with all kinds of indeterminacy (with respect to data, inferential procedures, probability distributions, graphical representations, etc.), allows for indeterminacy reduction, and uses neutrosophic probability which is more general than imprecise and classical probabilities, and has more detailed corresponding probability density functions. Whereas Interval Statistics only deals with indeterminacy that can be represented by intervals. And we respond to the arguments of (...)
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  15.  24
    Lies, damned lies, and statistics: An empirical investigation of the concept of lying.Adam J. Arico & Don Fallis - 2013 - Philosophical Psychology 26 (6):790 - 816.
    There are many philosophical questions surrounding the notion of lying. Is it ever morally acceptable to lie? Can we acquire knowledge from people who might be lying to us? More fundamental, however, is the question of what, exactly, constitutes the concept of lying. According to one traditional definition, lying requires intending to deceive (Augustine. (1952). Lying (M. Muldowney, Trans.). In R. Deferrari (Ed.), Treatises on various subjects (pp. 53?120). New York, NY: Catholic University of America). More recently, Thomas Carson (2006. (...)
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  16. Consciousness without Report: Insights from Summary Statistics and Inattention ‘Blindness’.Marius Usher, Zohar Bronfman, Shiri Talmor, Hilla Jacobson & Baruch Eitam - 2018 - Philosophical Transactions of the Royal Society B: Biological Sciences 373 (1755).
    We contrast two theoretical positions on the relation between phenomenal and access consciousness. First, we discuss previous data supporting a mild Overflow position, according to which transient visual awareness can overflow report. These data are open to two interpretations: (i) observers transiently experience specific visual elements outside attentional focus without encoding them into working memory; (ii) no specific visual elements but only statistical summaries are experienced in such conditions. We present new data showing that under data-limited conditions observers cannot discriminate (...)
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  17.  43
    Perception of ensemble statistics requires attention.Molly Jackson-Nielsen, Michael A. Cohen & Michael A. Pitts - 2017 - Consciousness and Cognition 48:149-160.
  18.  35
    “Let’s build an Anscombe box”: assessing Anscombe’s rebuttal of the statistics objection against indeterminism-based free agency.Thomas Müller - 2022 - Synthese 200 (2):1-22.
    Towards the end of her famous 1971 paper “Causality and Determination”, Elizabeth Anscombe discusses the controversial idea that “ ‘physical haphazard’ could be the only physical correlate of human freedom of action”. In order to illustrate how the high-level freedom of human action can go together with micro-indeterminism without creating a problem for micro-statistics, she provides the analogy of a glass box filled with minute coloured particles whose micro-dynamics is subject to statistical laws, while its outside reliably displays a (...)
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  19.  46
    Evidence for a Global Sampling Process in Extraction of Summary Statistics of Item Sizes in a Set.Midori Tokita, Sachiyo Ueda & Akira Ishiguchi - 2016 - Frontiers in Psychology 7:190369.
    Several studies have shown that our visual system may construct a “summary statistical representation” over groups of visual objects. Although there is a general understanding that human observers can accurately represent sets of a variety of features, many questions on how summary statistics, such as an average, are computed remain unanswered. This study investigated sampling properties of visual information used by human observers to extract two types of summary statistics of item sets, average and variance. We presented three (...)
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  20.  10
    Bayeswatch: an overview of Bayesian statistics.Peter C. Austin, Lawrence J. Brunner & S. M. Janet E. Hux Md - 2002 - Journal of Evaluation in Clinical Practice 8 (2):277-286.
    Increasingly, clinical research is evaluated on the quality of its statistical analysis. Traditionally, statistical analyses in clinical research have been carried out from a ‘frequentist’ perspective. The presence of an alternative paradigm – the Bayesian paradigm – has been relatively unknown in clinical research until recently. There is currently a growing interest in the use of Bayesian statistics in health care research. This is due both to a growing realization of the limitations of frequentist methods and to the ability (...)
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  21.  27
    More is Better: English Language Statistics are Biased Toward Addition.Bodo Winter, Martin H. Fischer, Christoph Scheepers & Andriy Myachykov - 2023 - Cognitive Science 47 (4):e13254.
    We have evolved to become who we are, at least in part, due to our general drive to create new things and ideas. When seeking to improve our creations, ideas, or situations, we systematically overlook opportunities to perform subtractive changes. For example, when tasked with giving feedback on an academic paper, reviewers will tend to suggest additional explanations and analyses rather than delete existing ones. Here, we show that this addition bias is systematically reflected in English language statistics along (...)
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  22. On the explanation for quantum statistics.Simon Saunders - 2006 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 37 (1):192-211.
    The concept of classical indistinguishability is analyzed and defended against a number of well-known criticisms, with particular attention to the Gibbs’paradox. Granted that it is as much at home in classical as in quantum statistical mechanics, the question arises as to why indistinguishability, in quantum mechanics but not in classical mechanics, forces a change in statistics. The answer, illustrated with simple examples, is that the equilibrium measure on classical phase space is continuous, whilst on Hilbert space it is discrete. (...)
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  23.  11
    Temporal and spatial ensemble statistics are formed by distinct mechanisms.Haojiang Ying, Edwin J. Burns J., Amanda M. Choo & Hong Xu - 2020 - Cognition 195 (C):104128.
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  24.  19
    When learning goes beyond statistics: Infants represent visual sequences in terms of chunks.Lauren K. Slone & Scott P. Johnson - 2018 - Cognition 178 (C):92-102.
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  25.  12
    Subcortical encoding of summary statistics in humans.Yuqing Zhao, Ting Zeng, Tongyu Wang, Fang Fang, Yi Pan & Jianrong Jia - 2023 - Cognition 234 (C):105384.
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  26.  9
    Countable Additivity and the Foundations of Bayesian Statistics.John V. Howard - 2006 - Theory and Decision 60 (2-3):127-135.
    At a very fundamental level an individual (or a computer) can process only a finite amount of information in a finite time. We can therefore model the possibilities facing such an observer by a tree with only finitely many arcs leaving each node. There is a natural field of events associated with this tree, and we show that any finitely additive probability measure on this field will also be countably additive. Hence when considering the foundations of Bayesian statistics we (...)
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  27.  5
    On the Geometry of the Berry-Robbins Approach to Spin-Statistics.Nikolaos Papadopoulos & Andrés F. Reyes-Lega - 2010 - Foundations of Physics 40 (7):829-851.
    Within a geometric and algebraic framework, the structures which are related to the spin-statistics connection are discussed. A comparison with the Berry-Robbins approach is made. The underlying geometric structure constitutes an additional support for this approach. In our work, a geometric approach to quantum indistinguishability is introduced which allows the treatment of singlevaluedness of wave functions in a global, model independent way.
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  28.  13
    Remarks on the Configuration Space Approach to Spin-Statistics.Andrés F. Reyes-Lega & Carlos Benavides - 2010 - Foundations of Physics 40 (7):1004-1029.
    The angular momentum operators for a system of two spin-zero indistinguishable particles are constructed, using Isham’s Canonical Group Quantization method. This mathematically rigorous method provides a hint at the correct definition of (total) angular momentum operators, for arbitrary spin, in a system of indistinguishable particles. The connection with other configuration space approaches to spin-statistics is discussed, as well as the relevance of the obtained results in view of a possible alternative proof of the spin-statistics theorem.
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  29.  10
    Frequentist probability and frequentist statistics.J. Neyman - 1977 - Synthese 36 (1):97 - 131.
  30.  11
    On the foundations of statistics.Ian Hacking - 1964 - British Journal for the Philosophy of Science 15 (57):1-26.
  31.  29
    The Philosophy of Quantitative Methods: Understanding Statistics.Brian D. Haig - 2018 - Oup Usa.
    The Philosophy of Quantitative Methods undertakes a philosophical examination of a number of important quantitative research methods within the behavioral sciences in order to overcome the non-critical approaches typically provided by textbooks. These research methods are exploratory data analysis, statistical significance testing, Bayesian confirmation theory and statistics, meta-analysis, and exploratory factor analysis. Further readings are provided to extend the reader's overall understanding of these methods.
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  32.  21
    Paleontology and Darwin’s Theory of Evolution: The Subversive Role of Statistics at the End of the 19th Century.Marco Tamborini - 2015 - Journal of the History of Biology 48 (4):575-612.
    This paper examines the subversive role of statistics paleontology at the end of the 19th and the beginning of the 20th centuries. In particular, I will focus on German paleontology and its relationship with statistics. I argue that in paleontology, the quantitative method was questioned and strongly limited by the first decade of the 20th century because, as its opponents noted, when the fossil record is treated statistically, it was found to generate results openly in conflict with the (...)
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  33.  5
    Duhem's problem, the bayesian way, and error statistics, or "what's belief got to do with it?".Deborah G. Mayo - 1997 - Philosophy of Science 64 (2):222-244.
    I argue that the Bayesian Way of reconstructing Duhem's problem fails to advance a solution to the problem of which of a group of hypotheses ought to be rejected or "blamed" when experiment disagrees with prediction. But scientists do regularly tackle and often enough solve Duhemian problems. When they do, they employ a logic and methodology which may be called error statistics. I discuss the key properties of this approach which enable it to split off the task of testing (...)
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  34.  9
    Cpt Invariance and the Spin-Statistics Connection.Jonathan Bain - 2016 - Oxford University Press UK.
    This book seeks to answer the question "What explains CPT invariance and the spin-statistics connection?" These properties play foundational roles in relativistic quantum field theories, are supported by high-precision experiments, and figure into explanations of a wide range of phenomena, from antimatter, to the periodic table of the elements, to superconductors and superfluids. They can be derived in RQFTs by means of the famous CPT and Spin-Statistics theorems; but, the author argues, these theorems cannot be said to explain (...)
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  35.  11
    Semantics versus statistics in the retreat from locative overgeneralization errors.Ben Ambridge, Julian M. Pine & Caroline F. Rowland - 2012 - Cognition 123 (2):260-279.
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  36.  11
    The summation method in statistics.H. S. Razran & M. E. Wagner - 1931 - Journal of Experimental Psychology 14 (3):270.
  37. Symmetry, Invariance and Ontology in Physics and Statistics.Julio Michael Stern - 2011 - Symmetry 3 (3):611-635.
    This paper has three main objectives: (a) Discuss the formal analogy between some important symmetry-invariance arguments used in physics, probability and statistics. Specifically, we will focus on Noether’s theorem in physics, the maximum entropy principle in probability theory, and de Finetti-type theorems in Bayesian statistics; (b) Discuss the epistemological and ontological implications of these theorems, as they are interpreted in physics and statistics. Specifically, we will focus on the positivist (in physics) or subjective (in statistics) interpretations (...)
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  38.  8
    Limited memory for ensemble statistics in visual change detection.William J. Harrison, Jessica M. V. McMaster & Paul M. Bays - 2021 - Cognition 214 (C):104763.
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  39. Causal inference in statistics. An overview.Judea Pearl - 2009 - Statistics Surveys 3:96-146.
  40.  8
    Rules Versus Statistics: Insights From a Highly Inflected Language.Jelena Mirković, Mark S. Seidenberg & Marc F. Joanisse - 2011 - Cognitive Science 35 (4):638-681.
    Inflectional morphology has been taken as a paradigmatic example of rule-governed grammatical knowledge (Pinker, 1999). The plausibility of this claim may be related to the fact that it is mainly based on studies of English, which has a very simple inflectional system. We examined the representation of inflectional morphology in Serbian, which encodes number, gender, and case for nouns. Linguists standardly characterize this system as a complex set of rules, with disagreements about their exact form. We present analyses of a (...)
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  41.  75
    Infinitesimal idealization, easy road nominalism, and fractional quantum statistics.Elay Shech - 2019 - Synthese 196 (5):1963-1990.
    It has been recently debated whether there exists a so-called “easy road” to nominalism. In this essay, I attempt to fill a lacuna in the debate by making a connection with the literature on infinite and infinitesimal idealization in science through an example from mathematical physics that has been largely ignored by philosophers. Specifically, by appealing to John Norton’s distinction between idealization and approximation, I argue that the phenomena of fractional quantum statistics bears negatively on Mary Leng’s proposed path (...)
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  42. Other issues in statistics II (subgroup analysis and meta-analysis).Jorge Leite & Munir Boodhwani - 2018 - In Felipe Fregni & Ben M. W. Illigens (eds.), Critical thinking in clinical research: applied theory and practice using case studies. New York, NY: Oxford University Press.
     
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  43.  6
    Proximities in statistics: Similarity and distance.Hans-J. Lenz - 2008 - In Giacomo Della Riccia, Didier Dubois & Hans-Joachim Lenz (eds.), Preferences and Similarities. Springer. pp. 161--177.
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  44.  5
    Principles of medical statistics.Grace G. Leybourne - 1937 - The Eugenics Review 29 (3):212.
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  45. Basics of statistics.Claudia Kimie Suemoto & Catherine Lee - 2018 - In Felipe Fregni & Ben M. W. Illigens (eds.), Critical thinking in clinical research: applied theory and practice using case studies. New York, NY: Oxford University Press.
     
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  46.  3
    Marriage fertility statistics.C. Tietze - 1937 - The Eugenics Review 28 (4):308.
  47.  13
    Thermodynamic Entropy in Quantum Statistics for Stock Market Networks.Jianjia Wang, Chenyue Lin & Yilei Wang - 2019 - Complexity 2019:1-11.
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  48. Tipper Discovers Statistics.Berrie Heesen - 2003 - Analytic Teaching and Philosophical Praxis 23 (1):69-71.
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  49. Philosophy and Suicide-Statistics in Austria-Hungary: Variation on a Theme of Masaryk.J. C. Nyiri - 1988 - In On Masaryk. Amsterdam: Rodopi. pp. 291-316.
    In his book The Austrian Mind (1972) W. M. Johnston observes that between 1861 and 1938 a striking number of Austrian intellectuals committed uicide. He also remarks that prior to 1920 suicide was relatively rare among Hungarian intellectuals, and as a possible explanation he refers to their more intensive political activity. The present paper investigates relations between a society's intellectual life and its general suicidal tendencies. In so doing it takes up a central theme of T. G. Masaryk's Suicide as (...)
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  50.  13
    Mathematics Anxiety and Statistics Anxiety. Shared but Also Unshared Components and Antagonistic Contributions to Performance in Statistics.Manuela Paechter, Daniel Macher, Khatuna Martskvishvili, Sigrid Wimmer & Ilona Papousek - 2017 - Frontiers in Psychology 8.
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