In this article, we analyze the third of three papers, in which Einstein presented his quantum theory of the ideal gas of 1924–1925. Although it failed to attract the attention of Einstein’s contemporaries and although also today very few commentators refer to it, we argue for its significance in the context of Einstein’s quantum researches. It contains an attempt to extend and exhaust the characterization of the monatomic ideal gas without appealing to combinatorics. Its ambiguities illustrate Einstein’s confusion with his (...) initial success in extending Bose’s results and in realizing the consequences of what later came to be called Bose–Einstein statistics. We discuss Einstein’s motivation for writing a non-combinatorial paper, partly in response to criticism by his friend Ehrenfest, and we paraphrase its content. Its arguments are based on Einstein’s belief in the complete analogy between the thermodynamics of light quanta and of material particles and invoke considerations of adiabatic transformations as well as of dimensional analysis. These techniques were well known to Einstein from earlier work on Wien’s displacement law, Planck’s radiation theory and the specific heat of solids. We also investigate the possible role of Ehrenfest in the gestation of the theory. (shrink)

An argument has been recently proposed by Watkins, whose objective is to show the impossibility of a statistical explanation of single events. This present paper is an attempt to show that Watkins's argument is unsuccessful, and goes on to argue for an account of statistical explanation which has much in common with Hempel's classic treatment.

Cosmopolitanism and statism represent the two dominant liberal theoretical standpoints in the current debate on global distributive justice. In this paper, I will develop a feminist argument that recommends that statist approaches be rejected. This argument has its roots in the feminist critique of liberal theories of social justice. In Justice, Gender, and the Family Susan Moller Okin argues that many liberal egalitarian theories of justice are inadequate because they assume a strict division between public and private spheres. I will (...) argue that this inadequacy is replicated in statist approaches to global justice. To demonstrate this, I will show how an analogue of Okin's critique of Rawls's A Theory of Justice can be extended to his The Law of Peoples. I will conclude that statist theories inevitably assume a strong divide between public and private spheres and that by doing so they allow for situations marked by gross injustice which anyone concerned with the welfare of the world's most vulnerable should find unacceptable. (shrink)

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 (...) new costs likely to cancel out any justificatory contribution of the statistic, but even if they didn’t, demographic facts are the wrong sort to make a moral difference to agents’ negative rights. I conclude that the popular argument should be rejected, and evidence-relative theories do not have the worrisome implication. (shrink)

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 apply to individual inquirers. My aim in this paper is to rehabilitate purely statistical evidence by arguing that, given the broader aims of legal systems, there are scenarios in which relying on such evidence is appropriate. Along the way I explain why popular arguments appealing to individual epistemic norms to reject legal reliance on bare statistics are unconvincing, by showing that courts and individuals face different epistemic predicaments (in short, individuals can hedge when confronted with statistical evidence, whilst legal tribunals cannot). I also correct some misconceptions about legal practice that have found their way into the recent literature. (shrink)

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 are strong intuitive motivations for doing this. For we can turn almost any case of _non-justifying_ merely statistical evidence into a case of _justifying_ merely statistical evidence by adding information about the dispositions and goals of the objects involved. The resulting view not only helps us understand when and why merely statistical evidence is normatively significant, but it also helps us understand how statistical evidence relates to more standard forms of evidence (perceptual, testimonial). The emerging view also has surprising applications, as it imposes limitations on the epistemic value of fine-tuning arguments for theism as well as undermines a standard class of case-based arguments for moral encroachment. (shrink)

J. S. Bell's argument that only “nonlocal” hidden variable theories can reproduce the quantum statistical correlations of the singlet spin state in the case of two separated spin-1/2 particles is examined in terms of Wigner's formulation. It is shown that a similar argument applies to a single spin-1/2 particle, and that the exclusion of hidden variables depends on an obviously untenable assumption concerning conditional probabilities. The problem of completeness is discussed briefly, and the grounds for rejecting a phase-space reconstruction (...) of the quantum statistics are clarified. (shrink)

It is argued that the symmetry and anti-symmetry of the wave functions of systems consisting of identical particles have nothing to do with the observational indistinguishability of these particles. Rather, a much stronger conceptual indistinguishability is at the bottom of the symmetry requirements. This can be used to argue further, in analogy to old arguments of De Broglie and Schrödinger, that the reality described by quantum mechanics has a wave-like rather than particle-like structure. The question of whether quantum statistics (...) alone can give rise to empirically observable correlations between results of distant measurements is also discussed. (shrink)

The use of algorithms to support prediction-based decision-making is becoming commonplace in a range of domains including health, criminal justice, education, social services, lending, and hiring. An assumption governing such decisions is that there is a property Y such that individual a should be allocated resource R by decision-maker D if a is Y. When there is uncertainty about whether a is Y, algorithms may provide valuable decision support by accurately predicting whether a is Y on the basis of known (...) features of a. Based on recent work on statistical evidence in epistemology this article presents an argument against relying exclusively on algorithmic predictions to allocate resources when they provide purely statistical evidence that a is Y. The article then responds to the objection that any evidence that will increase the proportion of correct decisions should be accepted as the basis for allocations regardless of its epistemic deficiency. Finally, some important practical aspects of the conclusion are considered. (shrink)

Unsupervised statistical learning is the standard setting for the development of the only advanced visual system that is both highly sophisticated and versatile, and extensively studied: that of monkeys and humans. In this extended abstract, we invoke philosophical observations, computational arguments, behavioral data and neurobiological findings to explain why computer vision researchers should care about (1) unsupervised learning, (2) statistical inference, and (3) the visual brain. We then outline a neuromorphic approach to structural primitive learning motivated by (...) these considerations, survey a range of neurobiological findings and behavioral data consistent with it, and conclude by mentioning some of the more challenging directions for future research. (shrink)

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 (...) the arguments by Woodall et al. [1]. We show that not all indeterminacies (uncertainties) may be represented by intervals. Also, in some cases, we should better use hesitant sets (that have less indeterminacy) instead of intervals. We redirect the authors to the Plithogenic Probability and Plithogenic Statistics which are the most general forms of MultiVariate Probability and Multivariate Statistics respectively (including, of course, the Imprecise Probability and Interval Statistics as subclasses). (shrink)

Claims about the occurrence of future events play an important role in pragmatic argumentation. Such claims can be supported by inductive arguments employing anecdotal, statistical, or causal evidence. In an experiment, the actual and perceived persuasiveness of these three types of evidence were assessed. A total of 324 participants read a newspaper article in which it was claimed that the building of a cultural centre would be profitable. This claim was supported by either anecdotal, statistical or causal (...) evidence. The statistical evidence proved to be more convincing than the anecdotal and causal evidence. Although the latter two evidence types were equally unconvincing, the anecdotal evidence was perceived as less persuasive than the causal evidence. Therefore, the actual and perceived persuasiveness of the evidence did not correspond. These results partly replicate the results obtained in previous experiments. They also underscore the need to distinguish between the perceived and the actual persuasiveness of an argument. (shrink)

The purpose of this paper is to provide a systematic appraisal of the covering law and statistical relevance theories of statistical explanation advanced by Carl G. Hempel and by Wesley C. Salmon, respectively. The analysis is intended to show that the difference between these accounts is inprinciple analogous to the distinction between truth and confirmation, where Hempel's analysis applies to what is taken to be the case and Salmon's analysis applies to what is the case. Specifically, it is (...) argued (a) that statistical explanations exhibit the nomic expectability of their explanandum events, which in some cases may be strong but in other cases will not be; (b) that the statistical relevance criterion is more fundamental than the requirement of maximal specificity and should therefore displace it; and, (c) that if statistical explanations are to be envisioned as inductive arguments at all, then only in a qualified sense since, in particular, the requirement of high inductive probability between explanans and explanandum must be abandoned. (shrink)

Inductive logic generalizes the idea of logical entailment and provides standards for the evaluation of non-conclusive arguments. A main application of inductive logic is the generalization of observational data to theoretical models. In the empirical sciences, the mathematical theory of statistics addresses the same problem. This paper argues that there is no separable purely logical aspect of statistical inference in a variety of complex problems. Instead, statistical practice is often motivated by decision-theoretic considerations and resembles empirical science.

Recently some philosophers have emphasized a potentially irreconcilable conceptual antagonism between the statistical characterization of natural selection and the standard scientific discussion of natural selection in terms of forces and causes. Other philosophers have developed an account of the causal character of selectionist statements represented in terms of counterfactuals. I examine the compatibility between such statisticalism and counterfactually based causal accounts of natural selection by distinguishing two distinct statisticalist claims: firstly the suggested impossibility for natural selection to be a (...) cause acting upon populations and secondly the conceptualization that all evolutionary causes occur at the level of interactions between individual organisms. I argue that deriving the latter from the former involves supplementary assumptions concerning precisely what causation is. I critically examine two of these assumptions purportedly preventing natural selection being regarded as a cause: the locality claim and the modularity claim. I conclude that justifying the strongest version of statisticalism—i.e. evolutionary causation only occurs at the level of individual interactions between organisms—would require further metaphysical arguments that are likely to be deemed highly problematic. Additionally, I argue that such a metaphysical position would be considered incongruous with both our scientific and ordinary use of the concepts of causality and explanation as employed within our everyday epistemological framework. (shrink)

The statistical aspects of quantum explanation are intrinsic to quantum physics; individual quantum events are created in the interactions associated with observation and are not describable by predictive theory. The superposition principle shows the essential difference between quantum and non-quantum physics, and the principle is exemplified in the classic single-photon two-slit interference experiment. Recently Mandel and Pfleegor have done an experiment somewhat similar to the optical single-photon experiment but with two independently operated lasers; interference is obtained even with beam (...) intensity so small that only one photon is in the apparatus at a time. The result can be understood in terms of the superposition of states; or, in terms of the Uncertainty Principle, which is found to forbid the determination of which of the two lasers is the source of a given photon (if conditions for interference are to obtain). The Mandel-Pfleegor experiment gives a physical argument against the continuous localization of a photon that is assumed in the hidden variable theories and therefore gives further support for the generally accepted view that an observed entity (observed state) is created in the observation event. This aspect of quantum physics implies a subjectivism on the level of individual quantum-level occurrences, since there is in quantum theory no basis for asserting the existence of the event independently of observation of it. Extension of this subjectivism to large scale, non-quantum phenomena falls within the principles of quantum theory; counter considerations that argue against such an extension are noted. (shrink)

(2013). Statistical models as cognitive models of individual differences in reasoning. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 89-102. doi: 10.1080/19462166.2012.674061.

This paper attempts to analyze the concept of quantum statistical determinism. This is done after we have clarified the epistemic difference between causality and determinism and discussed the content of classical forms of determinism—mechanical and dynamical. Quantum statistical determinism transcends the classical forms, for it expresses the multiple potentialities of quantum systems. The whole argument is consistent with a statistical interpretation of quantum mechanics.

In times of populist mistrust towards experts, it is important and the aim of the paper to ascertain the rationality of arguments from expert opinion and to reconstruct their rational foundations as well as to determine their limits. The foundational approach chosen is probabilistic. However, there are at least three correct probabilistic reconstructions of such argumentations: statistical inferences, Bayesian updating, and interpretive arguments. To solve this competition problem, the paper proposes a recourse to the arguments' justification (...) strengths achievable in the respective situation. (shrink)

Suppose one hundred prisoners are in a yard under the supervision of a guard, and at some point, ninety-nine of them collectively kill the guard. If, after the fact, a prisoner is picked at random and tried, the probability of his guilt is 99%. But despite the high probability, the statistical chances, by themselves, seem insufficient to justify a conviction. The question is why. Two arguments are offered. The first, decision-theoretic argument shows that a conviction solely based on (...) the statistics in the prisoner scenario is unacceptable so long as the goal of expected utility maximization is combined with fairness constraints. The second, risk-based argument shows that a conviction solely based on the statistics in the prisoner scenario lets the risk of mistaken conviction surge potentially too high. The same, by contrast, cannot be said of convictions solely based on DNA evidence or eyewitness testimony. A noteworthy feature of the two arguments in the paper is that they are not confined to criminal trials and can in fact be extended to civil trials. (shrink)

The issue of statelessness poses problems for the statist approach to the philosophy of immigration. Despite the fact that the statist approach claims to constrain the state’s right to exclude with human rights considerations, the arguments statists offer for the right of states to determine their own immigration policies would also justify citizenship rules that would render some children stateless. Insofar as rendering a child stateless is best characterized as a violation of human rights and insofar as some states (...) have direct responsibility for causing such harm, the problem of non-refugee stateless children points to greater constraints than most statists accept on states’ right to determine their own rules for membership. While statists can ultimately account for the right not to be rendered stateless, recognizing these additional human rights constraints ultimately weakens the core of the statist position. (shrink)

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 in their careers; or insurers who wish to charge more to young drivers than to more experienced ones, because they are more likely to have accidents than the latter – or to favour women over men in the cost of premiums for similar reasons. Finally, a famous – infamous – example of statistical discrimination is racial profiling for police purposes, where statistical evidence of differential propensities to crime are used to justify preventive police measures, such as ‘stop and search’, which mainly target young black men, and other racialized minorities. The philosophical appeal of the concept of statistical discrimination is fairly easy to see: it draws our attention to the way that probabilistic claims figure, or might figure, in the distribution of social costs and benefits such as jobs, security, insurance. It therefore gives us a way to test our moral intuitions across different cases, enables us to see how far our moral judgements can be generalised, and whether they have been affected by particularly emotive examples, or by the particular features of a real or hypothetical case. But does that mean that statistical discrimination is unproblematic? This article takes issue with some arguments of Kasper Lippert Rasmussen on the topic. (shrink)

An argument to the effect that non-relativistic quantum particles can be understood as individual objects in spite of the empirical evidence seemingly lending support to the opposite conclusion. Ways to understand quantum indistinguishability and quantum statistics in terms of individuals are indicated.

The debates between Bayesian, frequentist, and other methodologies of statistics have tended to focus on conceptual justifications, sociological arguments, or mathematical proofs of their long run properties. Both Bayesian statistics and frequentist (“classical”) statistics have strong cases on these grounds. In this article, we instead approach the debates in the “Statistics Wars” from a largely unexplored angle: simulations of different methodologies’ performance in the short to medium run. We conducted a large number of simulations using a straightforward decision problem (...) based around tossing a coin with unknown bias and then placing bets. In this simulation, we programmed four players, inspired by Bayesian statistics, frequentist statistics, Jon Williamson’s version of Objective Bayesianism, and a player who simply extrapolates from observed frequencies to general frequencies. The last player functions as a benchmark: a statistical methodology should at least outperform a crude form of induction. We focused on the performance of these methodologies in guiding the players towards good decisions. Unlike an earlier simulation study of this type, we found no systematic difference in performance between the Bayesian and frequentist players, provided the Bayesian used a flat prior and the frequentist used a low confidence level. Unlike that study, we were able to use Big Data methods to mitigate problems of random error in the simulation results. The Williamsonian player, who is a novel element of our study, also had no systematic differences in their performance, provided that they use a low confidence level. These players performed similarly even in the very short run, when players were making different decisions. Our study indicates that all three methodologies should be taken seriously by philosophers and practitioners of statistics. However, the frequentist and Williamsonian performed poorly when their confidence levels were high, and the Bayesian was surprisingly harmed by biased priors, providing some unexpected lessons for these methodologies when facing this type of decision problem. (shrink)

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 from the classical limits of quantum statistical partition functions, embodies a conceptual confusion. After clarifying the doctrine of haecceitism, a third argument is considered that attempts to deflate metaphysical concerns altogether by showing that the phase-space and distribution-space representations of MB-statistics have contrary haecceitistic import. Careful analysis shows this argument to fail as well, leaving de re modality unproblematically grounding particle identity in the classical context while genuine puzzlement about the underlying ontology remains for quantum statistics. (shrink)

: Peter Galison has recently claimed that twentieth-century microphysics has been pursued by two distinct experimental traditions--the image tradition and the logic tradition--that have only recently merged into a hybrid tradition. According to Galison, the two traditions employ fundamentally different forms of experimental argument, with the logic tradition using statistical arguments, while the image tradition strives for non-statistical demonstrations based on compelling ("golden") single events. I show that discoveries in both traditions have employed the same statistical (...) form of argument, even when basing discovery claims on single, golden events. Where Galison sees an epistemic divide between two communities that can only be bridged by a creole- or pidgin-like "interlanguage," there is in fact a shared commitment to a statistical form of experimental argument. (shrink)

Different realistic attitudes towards wavefunctions and quantum states are as old as quantum theory itself. Recently Pusey, Barret and Rudolph on the one hand, and Auletta and Tarozzi on the other, have proposed new interesting arguments in favor of a broad realistic interpretation of quantum mechanics that can be considered the modern heir to some views held by the fathers of quantum theory. In this paper we give a new and detailed presentation of such arguments, propose a new (...) taxonomy of different realistic positions in the foundations of quantum mechanics and assess the scope, within this new taxonomy, of these realistic arguments. (shrink)

The null-hypothesis significance-test procedure (NHSTP) is defended in the context of the theory-corroboration experiment, as well as the following contrasts: (a) substantive hypotheses versus statistical hypotheses, (b) theory corroboration versus statistical hypothesis testing, (c) theoretical inference versus statistical decision, (d) experiments versus nonexperimental studies, and (e) theory corroboration versus treatment assessment. The null hypothesis can be true because it is the hypothesis that errors are randomly distributed in data. Moreover, the null hypothesis is never used as a (...) categorical proposition. Statistical significance means only that chance influences can be excluded as an explanation of data; it does not identify the nonchance factor responsible. The experimental conclusion is drawn with the inductive principle underlying the experimental design. A chain of deductive arguments gives rise to the theoretical conclusion via the experimental conclusion. The anomalous relationship between statistical significance and the effect size often used to criticize NHSTP is more apparent than real. The absolute size of the effect is not an index of evidential support for the substantive hypothesis. Nor is the effect size, by itself, informative as to the practical importance of the research result. Being a conditional probability, statistical power cannot be the apriori probability of statistical significance. The validity of statistical power is debatable because statistical significance is determined with a single sampling distribution of the test statistic based on H0, whereas it takes two distributions to represent statistical power or effect size. Sample size should not be determined in the mechanical manner envisaged in power analysis. It is inappropriate to criticize NHSTP for nonstatistical reasons. At the same time, neither effect size, nor confidence interval estimate, nor posterior probability can be used to exclude chance as an explanation of data. Neither can any of them fulfill the nonstatistical functions expected of them by critics. (shrink)

Two arguments have recently been advanced that Maxwell-Boltzmann particles areindistinguishable just like Bose–Einstein and Fermi–Dirac particles. Bringing modalmetaphysics to bear on these arguments shows that ontological indistinguishabilityfor classical (MB) particles does not follow. The first argument, resting on symmetryin the occupation representation for all three cases, fails since peculiar correlationsexist in the quantum (BE and FD) context as harbingers of ontic indistinguishability,while the indistinguishability of classical particles remains purely epistemic. The secondargument, deriving from the classical limits of quantum (...) statistical partition functions,embodies a conceptual confusion. After clarifying the doctrine of haecceitism, a thirdargument is considered that attempts to deflate metaphysical concerns altogether byshowing that the phase-space and distribution-space representations of MB-statisticshave contrary haecceitistic import. Careful analysis shows this argument to fail as well,leaving de re modality unproblematically grounding particle identity in the classicalcontext while genuine puzzlement about the underlying ontology remains for quantumstatistics. (shrink)

Two arguments have recently been advanced that Maxwell-Boltzmann particles areindistinguishable just like Bose–Einstein and Fermi–Dirac particles. Bringing modalmetaphysics to bear on these arguments shows that ontological indistinguishabilityfor classical (MB) particles does not follow. The first argument, resting on symmetryin the occupation representation for all three cases, fails since peculiar correlationsexist in the quantum (BE and FD) context as harbingers of ontic indistinguishability,while the indistinguishability of classical particles remains purely epistemic. The secondargument, deriving from the classical limits of quantum (...) statistical partition functions,embodies a conceptual confusion. After clarifying the doctrine of haecceitism, a thirdargument is considered that attempts to deflate metaphysical concerns altogether byshowing that the phase-space and distribution-space representations of MB-statisticshave contrary haecceitistic import. Careful analysis shows this argument to fail as well,leaving de re modality unproblematically grounding particle identity in the classicalcontext while genuine puzzlement about the underlying ontology remains for quantumstatistics. (shrink)

The main argument of this paper is that an evaluation of the overall explanatory power of a theory is less problematic and more relevant as an assessment of the state of knowledge than evaluation of statistical explanations of single occurrences in terms of likelihoods that are assigned to explananda.

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 matters conform to either statistical or deterministic physical laws, the complete conformity of an irreducible agent’s settling of matters with what should be expected given the applicable laws would involve coincidences too wild to be credible. Here, I show that Pereboom’s argument depends on the assumption that, at times, the antecedent probability certain behavior will occur applies in each of a number of occasions, and is incapable of changing as a result of what one does from one occasion to the next. There is, however, no evidence this assumption is true. The upshot is the wild coincidence objection is an empirical objection lacking empirical support. Thus, it isn’t a compelling argument against agent-causal libertarianism. (shrink)

This paper explores some connections between competing conceptions of scientific laws on the one hand, and a problem in the foundations of statistical mechanics on the other. I examine two proposals for understanding the time asymmetry of thermodynamic phenomenal: David Albert's recent proposal and a proposal that I outline based on Hans Reichenbach's “branch systems”. I sketch an argument against the former, and mount a defense of the latter by showing how to accommodate statistical mechanics to recent developments (...) in the philosophy of scientific laws. (shrink)

An intricate, long, and occasionally heated debate surrounds Boltzmann’s H-theorem (1872) and his combinatorial interpretation of the second law (1877). After almost a century of devoted and knowledgeable scholarship, there is still no agreement as to whether Boltzmann changed his view of the second law after Loschmidt’s 1876 reversibility argument or whether he had already been holding a probabilistic conception for some years at that point. In this paper, I argue that there was no abrupt statistical turn. In the (...) first part, I discuss the development of Boltzmann’s research from 1868 to the formulation of the H-theorem. This reconstruction shows that Boltzmann adopted a pluralistic strategy based on the interplay between a kinetic and a combinatorial approach. Moreover, it shows that the extensive use of asymptotic conditions allowed Boltzmann to bracket the problem of exceptions. In the second part I suggest that both Loschmidt’s challenge and Boltzmann’s response to it did not concern the H-theorem. The close relation between the theorem and the reversibility argument is a consequence of later investigations on the subject. (shrink)

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 reviews three cases and argues that the interpretation problem of probabil- ity is insufficient to begin a philosophical analysis of the current issues in the field of statistics. A novel viewpoint is proposed to examine the relationship between the stopping-rule problem and the catch-all hypothesis problem. (shrink)

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 sometimes elicit elucidation. Thus, we now turn to the review. (shrink)

Is the welfare state neutral to personal morality?1 In today's welfare states one can find numerous life-styles existing side by side. These indicate a wide scope for 'personal moralities'2, but do not prove that the welfare state is 'neutral' to them. Welfare states interfere in more or less onerous ways with the business of (private) life with police checks, administrative controls and a vast arsenal of regulatory, penal and/or fiscal regimes. Some of the regulations may be more or less reasonable (...) attempts to minimise the risk of one person inflicting irreparable damage on others or their property, but a great many are not. It is not too difficult to see the hand of special (economic, ideological, even sectarian) interests in the bulk of the rules and regulations on the books.3 The state's non-neutrality is often an unintended outcome, but not always. Officials introduce new regulations with proud declarations of their intention to enforce particular 'moral choices', to treat one thing as a 'merit good' and another as an evil. They also justify intrusive policies with blatantly paternalistic arguments—remember their promise, or was it threat, to take care of us "from the cradle to the grave"—, with self-congratulatory references to an unspecified 'responsibility of the government'. There is no more direct negation of the role of private morality than the claim that one discharges one's own responsibility by depriving others of the opportunity to exercise theirs. As far as protection against onerous interference is concerned, the presumption of innocence—which is the linchpin of the rule of law—counts for very little. One delinquent person or business entity is often enough to let loose the regulatory juggernaut on everybody in the same group or category. In short, the question, whether the welfare state is neutral to personal morality, is largely rhetorical and academic. Behind the question there is the presupposition that the welfare state should be neutral to personal morality.. (shrink)

The detection of hate speech and fake news in political discourse is at the same time a crucial necessity for democratic societies and a challenge for several areas of study. However, most of the studies have focused on what is explicitly stated: false article information, language that expresses hatred, derogatory expressions. This paper argues that the explicit dimension of manipulation is only one – and the least problematic – of the risks of political discourse. The language of the unsaid is (...) much more dangerous and incomparably more difficult to detect, hidden in different types of fallacies and inappropriate uses of emotive language. Through a threefold coding scheme based on the instruments of argumentation theory and pragmatics, a corpus of argumentative tweets published by 4 politicians (Matteo Salvini, Donald Trump, Jair Bolsonaro, and Joseph Biden) within 6 months from their taking office (corresponding to the official end of their election campaign) is analyzed, detecting the types of argument, the fallacies, and the uses and misuses of “emotive words.” This coding results in the argumentation profiles of the speakers, which are compared statistically to show their different implicit strategies and deceptive tactics. (shrink)

According to Lange,?Really Statistical explanations? constitute an important kind of non-causalscientific explanation. However, Roski has argued that all alleged RS explanations are either causalexplanations or not explanations at all. In so arguing, Roski has invoked Kahneman?s interpretation of onealleged RS explanation. I employ Roski?s arguments as an opportunity to elaborate and defend RS explanations. Iargue that?RS explanations? genuinely explain rather than deny the presuppositions of why-questions. I argue thatthe RS model is not excessively permissive in allowing some explanations (...) to work purely statistically rather than bydescribing causal relations. I argue that Roski?s view that some?RS explanations? operate by describing causalrelations fails to capture the kind of explanatory insight that RS explanations provide. I elaborate the notion of a?characteristically statistical phenomenon? that figures in the RS model and thereby explain how an RS explanationreveals that its explanandum is independent of any causal facts or specific chances, but rather depends only on ageneric sort of arrangement of chances. Finally, I argue that Roski misinterprets Kahneman, who actually holds thatthe explanation he discusses is a non-causal explanation that nicely fits the RS model. RS explanations constitutean important kind of non-causal scientific explanation. (shrink)

The phenomenon of regression toward the mean is notoriously liable to be overlooked or misunderstood; regression fallacies are easy to commit. But even when regression phenomena are duly recognized, it remains perplexing how they can feature in explanations. This article develops a philosophical account of regression explanations as “statistically autonomous” explanations that cannot be deepened by adducing details about causal histories, even if the explananda as such are embedded in the causal structure of the world. That regression explanations have (...) class='Hi'>statistical autonomy was first suggested by Ian Hacking and has recently been defended and elaborated by André Ariew, Yasha Rohwer, and Collin Rice. However, I will argue that these analyses fail to capture what regression’s statistical autonomy consists in and how it sets regression explanations apart from other kinds of explanation. The alternative account I develop also shows what is amiss with a recent denial of regression’s statistical autonomy. Marc Lange has argued that facts that can be explained as regression phenomena can in principle also be explained by citing a conjunction of causal histories. The account of regression explanation developed here shows that his argument is based on a misunderstanding of the nature of statistical autonomy. (shrink)

In his paper titled ‘Against “measurement” ’ [Physics World 3(8), 33–40 [1990]], Bell criticised arguments that use the concept of measurement to justify the statistical interpretation of quantum theory. Among these was the text of Gottfried [Quantum Mechanics (Benjamin, New York, [1966])]. Gottfried has replied to this criticism, claiming to show that, for systems with both continuous and discrete degrees of freedom, the statistical interpretation for the discrete variables is implied by requiring that the continuous variables are (...) described classically. In the present paper, Gottfried’s argument is criticised. It is suggested that he takes over aspects of classical physics which are in conflict with the classical limit of the Schrödinger equation. He incorrectly assumes that, in the output from a Stern-Gerlach apparatus, the wave-function of any ion is restricted to one or another of the beams. (shrink)

Theories of statistical testing may be seen as attempts to provide systematic means for evaluating scientific conjectures on the basis of incomplete or inaccurate observational data. The Neyman-Pearson Theory of Testing (NPT) has purported to provide an objective means for testing statistical hypotheses corresponding to scientific claims. Despite their widespread use in science, methods of NPT have themselves been accused of failing to be objective; and the purported objectivity of scientific claims based upon NPT has been called into (...) question. The purpose of this paper is first to clarify this question by examining the conceptions of (I) the function served by NPT in science, and (II) the requirements of an objective theory of statistics upon which attacks on NPT's objectivity are based. Our grounds for rejecting these conceptions suggest altered conceptions of (I) and (II) that might avoid such attacks. Second, we propose a reformulation of NPT, denoted by NPT*, based on these altered conceptions, and argue that it provides an objective theory of statistics. The crux of our argument is that by being able to objectively control error frequencies NPT* is able to objectively evaluate what has or has not been learned from the result of a statistical test. (shrink)

The rapidly increasing role of automation throughout the economy, culture and our personal lives has generated a large literature on the risks of algorithmic decision-making, particularly in high-stakes legal settings. Algorithmic tools are charged with bias, shrouded in secrecy, and frequently difficult to interpret. However, these criticisms have tended to focus on particular implementations, specific predictive techniques, and the idiosyncrasies of the American legal-regulatory regime. They do not address the more fundamental unease about the prospect that we might one day (...) replace judges with algorithms, no matter how fair, transparent, and intelligible they become. The aim of this paper is to propose an account of the source of that unease, and to evaluate its plausibility. I trace foundational unease with algorithmic decision-making in the law to the powerful intuition that there is a basic moral and legal difference between showing that something is true of many people just like you and showing that it is true of you. Human judgment attends to the exception; automation insists on blindly applying the rule. I show how this intuitive thought is connected to both epistemological arguments about the value of statistical evidence, as well as to court-centered conceptions of the rule of law. Unease with algorithmic decision-making in the law thus draws on an intuitive principle that underpins a disparate range of views in legal philosophy. This suggests the principle is deeply ingrained. Nonetheless, I argue that the powerful intuition is not as decisive as it may seem, and indeed runs into significant epistemological and normative challenges. At an epistemological level, I show how concerns about statistical evidence's ability to track the truth can be resolved by adopting a probabilistic, rather than modal, conception of truth-tracking. At a normative level, commitment to highly individualized decision-making co-exists with equally ingrained and competing principles, such as consistent application of law. This suggests that the “rule of law” may not identify a discrete set of institutional arrangements, as proponents of a court-centric conception would have it, but rather a more loosely defined set of values that could potentially be operationalized in multiple ways, including through some level of algorithmic adjudication. Although the prospect of replacing judges with algorithms is indeed unsettling, it does not necessarily entail unreasonable verdicts or an attack on the rule of law. (shrink)

This paper recommends how authors of statistical studies can communicate to general audiences fully, clearly, and comfortably. The studies may use statistical methods to explore issues in science, engineering, and society or they may address issues in statistics specifically. In either case, readers without explicit statistical training should have no problem understanding the issues, the methods, or the results at a non-technical level. The arguments for those results should be clear, logical, and persuasive. This paper also (...) provides advice for editors of general journals on selecting high quality statistical articles without the need for exceptional work or expense. Finally, readers are also advised to watch out for some common errors or misuses of statistics that can be detected without a technical statistical background. (shrink)

A widespread assumption in the contemporary discussion of probabilistic models of cognition, often attributed to the Bayesian program, is that inference is optimal when the observer's priors match the true priors in the world—the actual “statistics of the environment.” But in fact the idea of a “true” prior plays no role in traditional Bayesian philosophy, which regards probability as a quantification of belief, not an objective characteristic of the world. In this paper I discuss the significance of the traditional Bayesian (...) epistemic view of probability and its mismatch with the more objectivist assumptions about probability that are widely held in contemporary cognitive science. I then introduce a novel mathematical framework, the observer lattice, that aims to clarify this issue while avoiding philosophically tendentious assumptions. The mathematical argument shows that even if we assume that “ground truth” probabilities actually do exist, there is no objective way to tell what they are. Different observers, conditioning on different information, will inevitably have different probability estimates, and there is no general procedure to determine which one is right. The argument sheds light on the use of probabilistic models in cognitive science, and in particular on what exactly it means for the mind to be “tuned” to its environment. (shrink)