Results for 'Naked statistics,'

985 found
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  1. 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 (...)
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  2. Against the Alleged Insufficiency of Statistical Evidence.Sam Fox Krauss - 2020 - Florida State University Law Review 47:801-825.
    Over almost a half-century, evidence law scholars and philosophers have contended with what have come to be called the “Proof Paradoxes.” In brief, the following sort of paradox arises: Factfinders in criminal and civil trials are charged with reaching a verdict if the evidence presented meets a particular standard of proof—beyond a reasonable doubt, in criminal cases, and preponderance of the evidence, in civil trials. It seems that purely statistical evidence can suffice for just such a level of certainty in (...)
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  3. Belief, Credence, and Evidence.Elizabeth Jackson - 2020 - Synthese 197 (11):5073-5092.
    I explore how rational belief and rational credence relate to evidence. I begin by looking at three cases where rational belief and credence seem to respond differently to evidence: cases of naked statistical evidence, lotteries, and hedged assertions. I consider an explanation for these cases, namely, that one ought not form beliefs on the basis of statistical evidence alone, and raise worries for this view. Then, I suggest another view that explains how belief and credence relate to evidence. My (...)
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  4. Proof Paradoxes and Normic Support: Socializing or Relativizing?Marcello Di Bello - 2020 - Mind 129 (516):1269-1285.
    Smith argues that, unlike other forms of evidence, naked statistical evidence fails to satisfy normic support. This is his solution to the puzzles of statistical evidence in legal proof. This paper focuses on Smith’s claim that DNA evidence in cold-hit cases does not satisfy normic support. I argue that if this claim is correct, virtually no other form of evidence used at trial can satisfy normic support. This is troublesome. I discuss a few ways in which Smith can respond.
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  5. Justified Belief and Just Conviction.Clayton Littlejohn - 2021 - In Jon Robson & Zachary Hoskins (eds.), The Social Epistemology of Legal Trials. Routledge.
    Abstract: When do we meet the standard of proof in a criminal trial? Some have argued that it is when the guilt of the defendant is sufficiently probable on the evidence. Some have argued that it is a matter of normic support. While the first view provides us with a nice account of how we ought to manage risk, the second explains why we shouldn’t convict on the basis of naked statistical evidence alone. Unfortunately, this second view doesn’t help (...)
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  6. Civil liability and the 50%+ standard of proof.Martin Smith - 2021 - International Journal of Evidence and Proof 25 (3):183-199.
    The standard of proof applied in civil trials is the preponderance of evidence, often said to be met when a proposition is shown to be more than 50% likely to be true. A number of theorists have argued that this 50%+ standard is too weak – there are circumstances in which a court should find that the defendant is not liable, even though the evidence presented makes it more than 50% likely that the plaintiff’s claim is true. In this paper, (...)
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  7. Spare Not a Naked Soldier: A Response to Daniel Restrepo.Maciek Zając - 2022 - Journal of Military Ethics 21 (1):66-81.
    In his recent JME article Daniel Restrepo argues that both legal and ethical rules should protect the so-called Naked Soldiers, combatants engaged in activity unrelated to military operations and unaware of the imminent danger threatening them. I criticize this position from several angles. I deny the existence of any link between vulnerability and innocence, and claim ignorance of deadly threats does not give rise to a morally distinguished type of vulnerability. I argue that actions not contributing to the war (...)
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  8. 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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  9. Frequentist Statistics as Internalist Reliabilism.Hanti Lin - manuscript
    There has long been an impression that reliabilism implies externalism and that frequentist statistics, due to its reliabilist nature, is inherently externalist. I argue, however, that frequentist statistics can plausibly be understood as a form of internalist reliabilism -- internalist in the conventional sense, yet reliabilist in certain unconventional and intriguing ways. Crucially, in developing the thesis that reliabilism does not imply externalism, my aim is not to stretch the meaning of ‘reliabilism’ merely to sever the implication. Instead, it is (...)
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  10. 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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  11. Krista K. Thomason, Naked: The Dark Side of Shame and Moral Life, Oxford University Press, 2018.Mark Alfano - forthcoming - Criminal Justice Ethics.
    In Naked, Krista K. Thomason offers a multi-faceted account of shame, covering its nature as an emotion, its positive and negative roles in moral life, its association with violence, and its provocation through invitations to shame, public shaming, and stigmatization. Along the way, she reflects on a range of examples drawn from literature, memoirs, journalism, and her own imagination. She also considers alternative views at length, draws a wealth of important distinctions, and articulates many of the most intuitive objections (...)
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  12. Full‐Frontal Morality: The Naked Truth about Gender.Talia Mae Bettcher - 2012 - Hypatia 27 (2):319-337.
    This paper examines Harold Garfinkel's notion of the natural attitude about sex and his claim that it is fundamentally moral in nature. The author looks beneath the natural attitude in order to explain its peculiar resilience and oppressive force. There she reveals a moral order grounded in the dichotomously sexed bodies so constituted through boundaries governing privacy and decency. In particular, naked bodies are sex-differentiated within a system of genital representation through gender presentation—a system that helps constitute the very (...)
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  13. 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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  14. 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, they introduce (...)
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  15. Statistical Significance Testing in Economics.William Peden & Jan Sprenger - 2022 - In Conrad Heilmann & Julian Reiss (eds.), Routledge Handbook of Philosophy of Economics. Routledge.
    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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  16. 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 disparate (...)
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  17. 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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  18. 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. Berlin: 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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  19. 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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  20. 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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  21. 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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  22. Naked: The Dark Side of Shame and Moral Life, by Krista Thomason (Book Review). [REVIEW]Carissa Véliz - 2018 - Notre Dame Philosophical Reviews 1.
    "Naked" is a worthwhile read for anyone interested in shame and its role in morality. The book is particularly timely given how common public shaming has become in online settings. Krista K. Thomason argues that, even though shame is a negative emotion with potentially damaging consequences, its dark side is outweighed by its moral benefits insofar as shame is constitutive of desirable moral commitments. According to the author, being liable to shame is constitutive of respecting other people’s points of (...)
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  23. 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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  24. 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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  25. 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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  26. 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 for hypotheses. (...)
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  27. 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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  28. 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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  29. 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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  30. The emperor is naked: Moral diplomacies and the ethics of AI.Constantin Vica, Cristina Voinea & Radu Uszkai - 2021 - Információs Társadalom 21 (2):83-96.
    With AI permeating our lives, there is widespread concern regarding the proper framework needed to morally assess and regulate it. This has given rise to many attempts to devise ethical guidelines that infuse guidance for both AI development and deployment. Our main concern is that, instead of a genuine ethical interest for AI, we are witnessing moral diplomacies resulting in moral bureaucracies battling for moral supremacy and political domination. After providing a short overview of what we term ‘ethics washing’ in (...)
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  31. 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 are primitive (...)
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  32. 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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  33. 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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  34. 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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  35. 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 begin with (...)
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  36. 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 the media thus (...)
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  37. 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 we respond to (...)
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  38. 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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  39.  94
    Error Statistics Using the Akaike and Bayesian Information Criteria.Henrique Cheng & Beckett Sterner - forthcoming - Erkenntnis.
    Many biologists, especially in ecology and evolution, analyze their data by estimating fits to a set of candidate models and selecting the best model according to the Akaike Information Criterion (AIC) or the Bayesian Information Criteria (BIC). When the candidate models represent alternative hypotheses, biologists may want to limit the chance of a false positive to a specified level. Existing model selection methodology, however, allows for only indirect control over error rates by setting a threshold for the difference in AIC (...)
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  40. Revisiting the two predominant statistical problems: the stopping-rule problem and the catch-all hypothesis problem.Yusaku Ohkubo - 2021 - Annals of the Japan Association for Philosophy of Science 30:23-41.
    The history of statistics is filled with many controversies, in which the prime focus has been the difference in the “interpretation of probability” between Fre- quentist and Bayesian theories. Many philosophical arguments have been elabo- rated to examine the problems of both theories based on this dichotomized view of statistics, including the well-known stopping-rule problem and the catch-all hy- pothesis problem. However, there are also several “hybrid” approaches in theory, practice, and philosophical analysis. This poses many fundamental questions. This paper (...)
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  41. 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 sources of (...)
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  42. 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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  43. (1 other version)statistical discrimination.Annabelle Lever - 2016 - The Philosophers Magazine 7 (2).
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  44. Unusual coincidences, statistics and an intelligent influence.Sergei Chekanov - manuscript
    This paper argues that unusual coincidences, particularly those involving historical events, can be viewed as design patterns, suggesting an intelligent influence over the course of events. A compelling case examined in detail using probability theory concerns the presidencies of Abraham Lincoln (1809–1865) and John F. Kennedy (1917–1963). This and other coincidences involving historical figures disfavor the materialistic perspective and point to the presence of an intelligent agent acting on a global scale, beyond the arrow of time, influencing human lives and (...)
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  45. 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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  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. 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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  48. OBCS: The Ontology of Biological and Clinical Statistics.Jie Zheng, Marcelline R. Harris, Anna Maria Masci, Yu Lin, Alfred Hero, Barry Smith & Yongqun He - 2014 - Proceedings of the Fifth International Conference on Biomedical Ontology 1327:65.
    Statistics play a critical role in biological and clinical research. To promote logically consistent representation and classification of statistical entities, we have developed the Ontology of Biological and Clinical Statistics (OBCS). OBCS extends the Ontology of Biomedical Investigations (OBI), an OBO Foundry ontology supported by some 20 communities. Currently, OBCS contains 686 terms, including 381 classes imported from OBI and 147 classes specific to OBCS. The goal of this paper is to present OBCS for community critique and to describe a (...)
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  49. 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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  50. 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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