Results for 'Statistics'

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  1. Statistical Mechanical Imperialism.Brad Weslake - 2014 - In Alastair Wilson (ed.), Chance and Temporal Asymmetry. Oxford: Oxford University Press. pp. 241-257.
    I argue against the claim, advanced by David Albert and Barry Loewer, that all non-fundamental laws can be derived from those required to underwrite the second law of thermodynamics.
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  2. Statistical Thinking between Natural and Social Sciences and the Issue of the Unity of Science: from Quetelet to the Vienna Circle.Donata Romizi - 2012 - In Dennis Dieks, Wenceslao J. Gonzalez, Stephan Hartmann, Michael Stöltzner & Marcel Weber (eds.), Probabilities, Laws, and Structures. Springer.
    The application of statistical methods and models both in the natural and social sciences is nowadays a trivial fact which nobody would deny. Bold analogies even suggest the application of the same statistical models to fields as different as statistical mechanics and economics, among them the case of the young and controversial discipline of Econophysics . Less trivial, however, is the answer to the philosophical question, which has been raised ever since the possibility of “commuting” statistical thinking and models between (...)
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  3. Demographic statistics in defensive decisions.Renée Jorgensen Bolinger - 2019 - Synthese 198 (5):4833-4850.
    A popular informal argument suggests that statistics about the preponderance of criminal involvement among particular demographic groups partially justify others in making defensive mistakes against members of the group. One could worry that evidence-relative accounts of moral rights vindicate this argument. After constructing the strongest form of this objection, I offer several replies: most demographic statistics face an unmet challenge from reference class problems, even those that meet it fail to ground non-negligible conditional probabilities, even if they did, (...)
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  4. Rehabilitating Statistical Evidence.Lewis Ross - 2019 - Philosophy and Phenomenological Research 102 (1):3-23.
    Recently, the practice of deciding legal cases on purely statistical evidence has been widely criticised. Many feel uncomfortable with finding someone guilty on the basis of bare probabilities, even though the chance of error might be stupendously small. This is an important issue: with the rise of DNA profiling, courts are increasingly faced with purely statistical evidence. A prominent line of argument—endorsed by Blome-Tillmann 2017; Smith 2018; and Littlejohn 2018—rejects the use of such evidence by appealing to epistemic norms that (...)
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  5. On statistical criteria of algorithmic fairness.Brian Hedden - 2021 - Philosophy and Public Affairs 49 (2):209-231.
    Predictive algorithms are playing an increasingly prominent role in society, being used to predict recidivism, loan repayment, job performance, and so on. With this increasing influence has come an increasing concern with the ways in which they might be unfair or biased against individuals in virtue of their race, gender, or, more generally, their group membership. Many purported criteria of algorithmic fairness concern statistical relationships between the algorithm’s predictions and the actual outcomes, for instance requiring that the rate of false (...)
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  6. Statistical Evidence, Sensitivity, and the Legal Value of Knowledge.David Enoch, Levi Spectre & Talia Fisher - 2012 - Philosophy and Public Affairs 40 (3):197-224.
    The law views with suspicion statistical evidence, even evidence that is probabilistically on a par with direct, individual evidence that the law is in no way suspicious of. But it has proved remarkably hard to either justify this suspicion, or to debunk it. In this paper, we connect the discussion of statistical evidence to broader epistemological discussions of similar phenomena. We highlight Sensitivity – the requirement that a belief be counterfactually sensitive to the truth in a specific way – as (...)
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  7. Statistical resentment, or: what’s wrong with acting, blaming, and believing on the basis of statistics alone.David Enoch & Levi Spectre - 2021 - Synthese 199 (3-4):5687-5718.
    Statistical evidence—say, that 95% of your co-workers badmouth each other—can never render resenting your colleague appropriate, in the way that other evidence (say, the testimony of a reliable friend) can. The problem of statistical resentment is to explain why. We put the problem of statistical resentment in several wider contexts: The context of the problem of statistical evidence in legal theory; the epistemological context—with problems like the lottery paradox for knowledge, epistemic impurism and doxastic wrongdoing; and the context of a (...)
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  8. Merely statistical evidence: when and why it justifies belief.Paul Silva - 2023 - Philosophical Studies 180 (9):2639-2664.
    It is one thing to hold that merely statistical evidence is _sometimes_ insufficient for rational belief, as in typical lottery and profiling cases. It is another thing to hold that merely statistical evidence is _always_ insufficient for rational belief. Indeed, there are cases where statistical evidence plainly does justify belief. This project develops a dispositional account of the normativity of statistical evidence, where the dispositions that ground justifying statistical evidence are connected to the goals (= proper function) of objects. There (...)
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  9. The Statistical Nature of Causation.David Papineau - 2022 - The Monist 105 (2):247-275.
    Causation is a macroscopic phenomenon. The temporal asymmetry displayed by causation must somehow emerge along with other asymmetric macroscopic phenomena like entropy increase and the arrow of radiation. I shall approach this issue by considering ‘causal inference’ techniques that allow causal relations to be inferred from sets of observed correlations. I shall show that these techniques are best explained by a reduction of causation to structures of equations with probabilistically independent exogenous terms. This exogenous probabilistic independence imposes a recursive order (...)
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  10. Statistical Evidence, Normalcy, and the Gatecrasher Paradox.Michael Blome-Tillmann - 2020 - Mind 129 (514):563-578.
    Martin Smith has recently proposed, in this journal, a novel and intriguing approach to puzzles and paradoxes in evidence law arising from the evidential standard of the Preponderance of the Evidence. According to Smith, the relation of normic support provides us with an elegant solution to those puzzles. In this paper I develop a counterexample to Smith’s approach and argue that normic support can neither account for our reluctance to base affirmative verdicts on bare statistical evidence nor resolve the pertinent (...)
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  11. Statistical Significance Testing in Economics.William Peden & Jan Sprenger - 2021 - In Conrad Heilmann & Julian Reiss (eds.), The Routledge Handbook of the Philosophy of Economics.
    The origins of testing scientific models with statistical techniques go back to 18th century mathematics. However, the modern theory of statistical testing was primarily developed through the work of Sir R.A. Fisher, Jerzy Neyman, and Egon Pearson in the inter-war period. Some of Fisher's papers on testing were published in economics journals (Fisher, 1923, 1935) and exerted a notable influence on the discipline. The development of econometrics and the rise of quantitative economic models in the mid-20th century made statistical significance (...)
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  12. Probabilities in Statistical Mechanics.Wayne C. Myrvold - 2016 - In Alan Hájek & Christopher Hitchcock (eds.), The Oxford Handbook of Probability and Philosophy. Oxford: Oxford University Press. pp. 573-600.
    This chapter will review selected aspects of the terrain of discussions about probabilities in statistical mechanics (with no pretensions to exhaustiveness, though the major issues will be touched upon), and will argue for a number of claims. None of the claims to be defended is entirely original, but all deserve emphasis. The first, and least controversial, is that probabilistic notions are needed to make sense of statistical mechanics. The reason for this is the same reason that convinced Maxwell, Gibbs, and (...)
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  13. An Alternative Interpretation of Statistical Mechanics.C. D. McCoy - 2020 - Erkenntnis 85 (1):1-21.
    In this paper I propose an interpretation of classical statistical mechanics that centers on taking seriously the idea that probability measures represent complete states of statistical mechanical systems. I show how this leads naturally to the idea that the stochasticity of statistical mechanics is associated directly with the observables of the theory rather than with the microstates (as traditional accounts would have it). The usual assumption that microstates are representationally significant in the theory is therefore dispensable, a consequence which suggests (...)
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  14. Statistical significance under low power: A Gettier case?Daniel Dunleavy - 2020 - Journal of Brief Ideas.
    A brief idea on statistics and epistemology.
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  15. Foundation of statistical mechanics: Mechanics by itself.Orly Shenker - 2017 - Philosophy Compass 12 (12):e12465.
    Statistical mechanics is a strange theory. Its aims are debated, its methods are contested, its main claims have never been fully proven, and their very truth is challenged, yet at the same time, it enjoys huge empirical success and gives us the feeling that we understand important phenomena. What is this weird theory, exactly? Statistical mechanics is the name of the ongoing attempt to apply mechanics, together with some auxiliary hypotheses, to explain and predict certain phenomena, above all those described (...)
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  16. A statistical learning approach to a problem of induction.Kino Zhao - manuscript
    At its strongest, Hume's problem of induction denies the existence of any well justified assumptionless inductive inference rule. At the weakest, it challenges our ability to articulate and apply good inductive inference rules. This paper examines an analysis that is closer to the latter camp. It reviews one answer to this problem drawn from the VC theorem in statistical learning theory and argues for its inadequacy. In particular, I show that it cannot be computed, in general, whether we are in (...)
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  17. Statistics as Figleaves.Felix Bräuer - 2023 - Topoi 42 (2):433-443.
    Recently, Jennifer Saul (“Racial Figleaves, the Shifting Boundaries of the Permissible, and the Rise of Donald Trump”, 2017; “Racist and Sexist Figleaves”, 2021) has explored the use of what she calls “figleaves” in the discourse on race and gender. Following Saul, a figleaf is an utterance that, for some portion of the audience, blocks the conclusion that some other utterance, R, or the person who uttered R is racist or sexist. Such racial and gender figleaves are pernicious, says Saul, because, (...)
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  18. Disparate Statistics.Kevin P. Tobia - 2017 - Yale Law Journal 126 (8):2382-2420.
    Statistical evidence is crucial throughout disparate impact’s three-stage analysis: during (1) the plaintiff’s prima facie demonstration of a policy’s disparate impact; (2) the defendant’s job-related business necessity defense of the discriminatory policy; and (3) the plaintiff’s demonstration of an alternative policy without the same discriminatory impact. The circuit courts are split on a vital question about the “practical significance” of statistics at Stage 1: Are “small” impacts legally insignificant? For example, is an employment policy that causes a one percent (...)
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  19. When statistical evidence is not specific enough.Marcello Di Bello - 2021 - Synthese 199 (5-6):12251-12269.
    Many philosophers have pointed out that statistical evidence, or at least some forms of it, lack desirable epistemic or non-epistemic properties, and that this should make us wary of litigations in which the case against the defendant rests in whole or in part on statistical evidence. Others have responded that such broad reservations about statistical evidence are overly restrictive since appellate courts have expressed nuanced views about statistical evidence. In an effort to clarify and reconcile, I put forward an interpretive (...)
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  20. Four Pillars of Statisticalism.Denis M. Walsh, André Ariew & Mohan Matthen - 2017 - Philosophy, Theory, and Practice in Biology 9 (1):1-18.
    Over the past fifteen years there has been a considerable amount of debate concerning what theoretical population dynamic models tell us about the nature of natural selection and drift. On the causal interpretation, these models describe the causes of population change. On the statistical interpretation, the models of population dynamics models specify statistical parameters that explain, predict, and quantify changes in population structure, without identifying the causes of those changes. Selection and drift are part of a statistical description of population (...)
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  21. Statistical mechanics and thermodynamics: A Maxwellian view.Wayne C. Myrvold - 2011 - Studies in History and Philosophy of Science Part A 42 (4):237-243.
    One finds, in Maxwell's writings on thermodynamics and statistical physics, a conception of the nature of these subjects that differs in interesting ways from the way that they are usually conceived. In particular, though—in agreement with the currently accepted view—Maxwell maintains that the second law of thermodynamics, as originally conceived, cannot be strictly true, the replacement he proposes is different from the version accepted by most physicists today. The modification of the second law accepted by most physicists is a probabilistic (...)
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  22. Neutrosophic Statistics is an extension of Interval Statistics, while Plithogenic Statistics is the most general form of statistics (second version).Florentin Smarandache - 2022 - International Journal of Neutrosophic Science 19 (1):148-165.
    In this paper, we prove that Neutrosophic Statistics is more general than Interval Statistics, since it may deal with all types of indeterminacies (with respect to the data, inferential procedures, probability distributions, graphical representations, etc.), it allows the reduction of indeterminacy, and it uses the neutrosophic probability that is more general than imprecise and classical probabilities and has more detailed corresponding probability density functions. While Interval Statistics only deals with indeterminacy that can be represented by intervals. And (...)
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  23. Cultural Statistics, the Media and the Planning and Development of Calabar.Lawrence Ekwok - 2019 - GNOSI: An Interdisciplinary Journal of Human Theory and Praxis 2 (2).
    This paper, “Cultural Statistics, the Media and the Planning and Development of Calabar, Nigeria” stresses the need for the use of Cultural Statistics and effective media communication in the planning and development of Calabar, the Cross River State Capital. This position is anchored on the fact that in virtually every sphere of life, there can be no development without planning, and there can be no proper planning without accurate data or information. Cultural Statistics, and effective use of (...)
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  24. Legal proof and statistical conjunctions.Lewis D. Ross - 2020 - Philosophical Studies 178 (6):2021-2041.
    A question, long discussed by legal scholars, has recently provoked a considerable amount of philosophical attention: ‘Is it ever appropriate to base a legal verdict on statistical evidence alone?’ Many philosophers who have considered this question reject legal reliance on bare statistics, even when the odds of error are extremely low. This paper develops a puzzle for the dominant theories concerning why we should eschew bare statistics. Namely, there seem to be compelling scenarios in which there are multiple (...)
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  25. Statistical Inference and the Replication Crisis.Lincoln J. Colling & Dénes Szűcs - 2018 - Review of Philosophy and Psychology 12 (1):121-147.
    The replication crisis has prompted many to call for statistical reform within the psychological sciences. Here we examine issues within Frequentist statistics that may have led to the replication crisis, and we examine the alternative—Bayesian statistics—that many have suggested as a replacement. The Frequentist approach and the Bayesian approach offer radically different perspectives on evidence and inference with the Frequentist approach prioritising error control and the Bayesian approach offering a formal method for quantifying the relative strength of evidence (...)
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  26. Quantum Foundations of Statistical Mechanics and Thermodynamics.Orly Shenker - 2022 - In Eleanor Knox & Alastair Wilson (eds.), The Routledge Companion to Philosophy of Physics. London, UK: Routledge. pp. Ch. 29.
    Statistical mechanics is often taken to be the paradigm of a successful inter-theoretic reduction, which explains the high-level phenomena (primarily those described by thermodynamics) by using the fundamental theories of physics together with some auxiliary hypotheses. In my view, the scope of statistical mechanics is wider since it is the type-identity physicalist account of all the special sciences. But in this chapter, I focus on the more traditional and less controversial domain of this theory, namely, that of explaining the thermodynamic (...)
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  27. statistical discrimination.Annabelle Lever - 2016 - The Philosophers Magazine 7 (2).
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  28. Inherent Properties and Statistics with Individual Particles in Quantum Mechanics.Matteo Morganti - 2009 - Studies in History and Philosophy of Science Part B: Studies in History and Philosophy of Modern Physics 40 (3):223-231.
    This paper puts forward the hypothesis that the distinctive features of quantum statistics are exclusively determined by the nature of the properties it describes. In particular, all statistically relevant properties of identical quantum particles in many-particle systems are conjectured to be irreducible, ‘inherent’ properties only belonging to the whole system. This allows one to explain quantum statistics without endorsing the ‘Received View’ that particles are non-individuals, or postulating that quantum systems obey peculiar probability distributions, or assuming that there (...)
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  29. Classical versus Bayesian Statistics.Eric Johannesson - 2020 - Philosophy of Science 87 (2):302-318.
    In statistics, there are two main paradigms: classical and Bayesian statistics. The purpose of this article is to investigate the extent to which classicists and Bayesians can agree. My conclusion is that, in certain situations, they cannot. The upshot is that, if we assume that the classicist is not allowed to have a higher degree of belief in a null hypothesis after he has rejected it than before, then he has to either have trivial or incoherent credences to (...)
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  30. Statistical discrimination.Annabelle Lever - 2016 - The Philosophers' Magazine 72:75-76.
    Racial discrimination uses race as grounds to discriminate in the treatment owed to others; sexual discrimination uses people’s sexual features as grounds for determining how they should be treated compared to others. Analogously, statistical discrimination treats statistical inferences about the groups to which individuals belong as grounds for discriminating amongst them in thought, word and deed. Examples of statistical discrimination include the employer who won’t hire women of childbearing age, because they are likely to take maternity leave at some point (...)
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  31. Accuracy and Statistical Evidence.Arif Ahmed - manuscript
    Abstract. Suppose that the word of an eyewitness makes it 80% probable that A committed a crime, and that B is drawn from a population in which the incidence rate of that crime is 80%. Many philosophers and legal theorists have held that if this is our only evidence against those parties then (i) we may be justified in finding against A but not against B; but (ii) that doing so incurs a loss in the accuracy of our findings. This (...)
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  32. Knowledge, Evidence, and Naked Statistics.Sherrilyn Roush - 2023 - In Luis R. G. Oliveira (ed.), Externalism about Knowledge. Oxford: Oxford University Press.
    Many who think that naked statistical evidence alone is inadequate for a trial verdict think that use of probability is the problem, and something other than probability – knowledge, full belief, causal relations – is the solution. I argue that the issue of whether naked statistical evidence is weak can be formulated within the probabilistic idiom, as the question whether likelihoods or only posterior probabilities should be taken into account in our judgment of a case. This question also identifies a (...)
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  33. Statistical Inference and the Plethora of Probability Paradigms: A Principled Pluralism.Mark L. Taper, Gordon Brittan Jr & Prasanta S. Bandyopadhyay - manuscript
    The major competing statistical paradigms share a common remarkable but unremarked thread: in many of their inferential applications, different probability interpretations are combined. How this plays out in different theories of inference depends on the type of question asked. We distinguish four question types: confirmation, evidence, decision, and prediction. We show that Bayesian confirmation theory mixes what are intuitively “subjective” and “objective” interpretations of probability, whereas the likelihood-based account of evidence melds three conceptions of what constitutes an “objective” probability.
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  34. Connecting Spin and Statistics in Quantum Mechanics.Arthur Jabs - 2014 - arXiv:0810.2399.
    The spin-statistics connection is derived in a simple manner under the postulates that the original and the exchange wave functions are simply added, and that the azimuthal phase angle, which defines the orientation of the spin part of each single-particle spin-component eigenfunction in the plane normal to the spin-quantization axis, is exchanged along with the other parameters. The spin factor (−1)2s belongs to the exchange wave function when this function is constructed so as to get the spinor ambiguity under (...)
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  35. Maxwell-Boltzmann Statistics and the Metaphysics of Modality.Bruce L. Gordon - 2002 - Synthese 133 (3):393-417.
    ABSTRACT. Two arguments have recently been advanced that Maxwell-Boltzmann particles are indistinguishable just like Bose-Einstein and Fermi-Dirac particles. Bringing modal metaphysics to bear on these arguments shows that ontological indistinguishability for classical (MB) particles does not follow. The first argument, resting on symmetry in the occupation representation for all three cases, fails since peculiar correlations exist in the quantum (BE and FD) context as harbingers of ontic indistinguishability, while the indistinguishability of classical particles remains purely epistemic. The second argument, deriving (...)
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  36. Drift and “Statistically Abstractive Explanation”.Mohan Matthen - 2009 - Philosophy of Science 76 (4):464-487.
    A hitherto neglected form of explanation is explored, especially its role in population genetics. “Statistically abstractive explanation” (SA explanation) mandates the suppression of factors probabilistically relevant to an explanandum when these factors are extraneous to the theoretical project being pursued. When these factors are suppressed, the explanandum is rendered uncertain. But this uncertainty traces to the theoretically constrained character of SA explanation, not to any real indeterminacy. Random genetic drift is an artifact of such uncertainty, and it is therefore wrong (...)
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  37. 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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  38. Statistical trends of school size, location and enrolment: An evaluation of public junior secondary schools for sustainable development.Samuel Okpon Ekaette, Eyiene Ameh & Valentine Joseph Owan - 2020 - World Journal of Vocational Education and Training 2 (2):76-88.
    This is a trend study of School Size, Location and Enrolment Figures of Junior secondary schools in Akwa Ibom State of Nigeria covering 2008 – 2016 with implications on sustainable development. The study was tailored to follow the ex-post facto research design. This study was a census, hence the entire population of 227 public secondary schools were used. Secondary quantitative data were obtained using “School Size, Location and Enrolment Figures Checklist (SSLEFC)” were analysed using descriptive statistics, while line graphs (...)
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  39. Sensitivity, Causality, and Statistical Evidence in Courts of Law.Michael Blome-Tillmann - 2015 - Thought: A Journal of Philosophy 4 (2):102-112.
    Recent attempts to resolve the Paradox of the Gatecrasher rest on a now familiar distinction between individual and bare statistical evidence. This paper investigates two such approaches, the causal approach to individual evidence and a recently influential (and award-winning) modal account that explicates individual evidence in terms of Nozick's notion of sensitivity. This paper offers counterexamples to both approaches, explicates a problem concerning necessary truths for the sensitivity account, and argues that either view is implausibly committed to the impossibility of (...)
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  40. Statistical learning of complex questions.Hartmut Fitz - 2010 - In S. Ohlsson & R. Catrambone (eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society. Cognitive Science Society. pp. 2692--2698.
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  41. Vagueness : a statistical epistemicist approach.Jiri Benovsky - 2011 - Teorema: International Journal of Philosophy (3):97-112.
    There are three main traditional accounts of vagueness : one takes it as a genuinely metaphysical phenomenon, one takes it as a phenomenon of ignorance, and one takes it as a linguistic or conceptual phenomenon. In this paper I first very briefly present these views, especially the epistemicist and supervaluationist strategies, and shortly point to some well-known problems that the views carry. I then examine a 'statistical epistemicist' account of vagueness that is designed to avoid precisely these problems – it (...)
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  42. Contemporary Approaches to Statistical Mechanical Probabilities: A Critical Commentary - Part I: The Indifference Approach.Christopher J. G. Meacham - 2010 - Philosophy Compass 5 (12):1116-1126.
    This pair of articles provides a critical commentary on contemporary approaches to statistical mechanical probabilities. These articles focus on the two ways of understanding these probabilities that have received the most attention in the recent literature: the epistemic indifference approach, and the Lewis-style regularity approach. These articles describe these approaches, highlight the main points of contention, and make some attempts to advance the discussion. The first of these articles provides a brief sketch of statistical mechanics, and discusses the indifference approach (...)
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  43. A new statistical solution to the generality problem.Samuel Kampa - 2018 - Episteme 15 (2):228-244.
    The Generality Problem is widely recognized to be a serious problem for reliabilist theories of justification. James R. Beebe's Statistical Solution is one of only a handful of attempted solutions that has garnered serious attention in the literature. In their recent response to Beebe, Julien Dutant and Erik J. Olsson successfully refute Beebe's Statistical Solution. This paper presents a New Statistical Solution that countenances Dutant and Olsson's objections, dodges the serious problems that trouble rival solutions, and retains the theoretical virtues (...)
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  44. Smiting Statist Philosophical Philistinism: a Reply to the Thom Brooks Review of Escape from Leviathan.J. C. Lester - manuscript
    It is possible to pose many difficult and fascinating problems and criticisms for the various theses and arguments in Escape from Leviathan (EfL). This occurred while writing it, and various sharp minds did it on reading drafts or the final product. However, some reviews misunderstand, or ignore, what is written and reassert conventional views. But it is best to answer all published criticisms if only to show how they fail, lest anyone thinks they are sound, and even poor criticisms can (...)
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  45. Agent-causal libertarianism, statistical neural laws and wild coincidences.Jason D. Runyan - 2018 - Synthese 195 (10):4563-4580.
    Agent-causal libertarians maintain we are irreducible agents who, by acting, settle matters that aren’t already settled. This implies that the neural matters underlying the exercise of our agency don’t conform to deterministic laws, but it does not appear to exclude the possibility that they conform to statistical laws. However, Pereboom (Noûs 29:21–45, 1995; Living without free will, Cambridge University Press, Cambridge, 2001; in: Nadelhoffer (ed) The future of punishment, Oxford University Press, New York, 2013) has argued that, if these neural (...)
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  46. Belief, Credence and Statistical Evidence.Davide Fassio & Jie Gao - 2020 - Theoria 86 (4):500-527.
    According to the Rational Threshold View, a rational agent believes p if and only if her credence in p is equal to or greater than a certain threshold. One of the most serious challenges for this view is the problem of statistical evidence: statistical evidence is often not sufficient to make an outright belief rational, no matter how probable the target proposition is given such evidence. This indicates that rational belief is not as sensitive to statistical evidence as rational credence. (...)
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  47. Explaining the Justificatory Asymmetry between Statistical and Individualized Evidence.Renee Bolinger - forthcoming - In Jon Robson & Zachary Hoskins (eds.), The Social Epistemology of Legal Trials. Routledge. pp. 60-76.
    In some cases, there appears to be an asymmetry in the evidential value of statistical and more individualized evidence. For example, while I may accept that Alex is guilty based on eyewitness testimony that is 80% likely to be accurate, it does not seem permissible to do so based on the fact that 80% of a group that Alex is a member of are guilty. In this paper I suggest that rather than reflecting a deep defect in statistical evidence, this (...)
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  48. Publication statistics through the end of 2020, the first COVID-19 year.V.&A. Aisdl - 2020 - AISDL Initiative.
    Most of the following are peer-reviewed publications undertaken during the 2000-2020 period, except for very few reports such as the VIASM SciMath Project papers [1,5]...
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  49. What is the Statistical Inference? : An Invitation to Carnap's inductive Logic.Yusuke Kaneko - 2022 - The Basis : The Annual Bulletin of Research Center for Liberal Education 12:91-117.
    Although written in Japanese, what the statistical inference is philosophically investigated.
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  50. Time's Arrow in a Quantum Universe: On the Status of Statistical Mechanical Probabilities.Eddy Keming Chen - 2020 - In Valia Allori (ed.), Statistical Mechanics and Scientific Explanation: Determinism, Indeterminism and Laws of Nature. World Scientific. pp. 479–515.
    In a quantum universe with a strong arrow of time, it is standard to postulate that the initial wave function started in a particular macrostate---the special low-entropy macrostate selected by the Past Hypothesis. Moreover, there is an additional postulate about statistical mechanical probabilities according to which the initial wave function is a ''typical'' choice in the macrostate. Together, they support a probabilistic version of the Second Law of Thermodynamics: typical initial wave functions will increase in entropy. Hence, there are two (...)
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