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Error and the Growth of Experimental Knowledge

University of Chicago (1996)

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  1. Error probabilities for inference of causal directions.Jiji Zhang - 2008 - Synthese 163 (3):409 - 418.
    A main message from the causal modelling literature in the last several decades is that under some plausible assumptions, there can be statistically consistent procedures for inferring (features of) the causal structure of a set of random variables from observational data. But whether we can control the error probabilities with a finite sample size depends on the kind of consistency the procedures can achieve. It has been shown that in general, under the standard causal Markov and Faithfulness assumptions, the procedures (...)
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  • A bayesian way to make stopping rules matter.Daniel Steel - 2003 - Erkenntnis 58 (2):213--227.
    Disputes between advocates of Bayesians and more orthodox approaches to statistical inference presuppose that Bayesians must regard must regard stopping rules, which play an important role in orthodox statistical methods, as evidentially irrelevant.In this essay, I show that this is not the case and that the stopping rule is evidentially relevant given some Bayesian confirmation measures that have been seriously proposed. However, I show that accepting a confirmation measure of this sort comes at the cost of rejecting two useful ancillaryBayesian (...)
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  • Severe tests, arguing from error, and methodological underdetermination.Deborah G. Mayo - 1997 - Philosophical Studies 86 (3):243-266.
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  • A new solution to the paradoxes of rational acceptability.Igor Douven - 2002 - British Journal for the Philosophy of Science 53 (3):391-410.
    The Lottery Paradox and the Preface Paradox both involve the thesis that high probability is sufficient for rational acceptability. The standard solution to these paradoxes denies that rational acceptability is deductively closed. This solution has a number of untoward consequences. The present paper suggests that a better solution to the paradoxes is to replace the thesis that high probability suffices for rational acceptability with a somewhat stricter thesis. This avoids the untoward consequences of the standard solution. The new solution will (...)
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  • The quantitative problem of old evidence.E. C. Barnes - 1999 - British Journal for the Philosophy of Science 50 (2):249-264.
    The quantitative problem of old evidence is the problem of how to measure the degree to which e confirms h for agent A at time t when A regards e as justified at t. Existing attempts to solve this problem have applied the e-difference approach, which compares A's probability for h at t with what probability A would assign h if A did not regard e as justified at t. The quantitative problem has been widely regarded as unsolvable primarily on (...)
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  • Robust evidence and secure evidence claims.Kent W. Staley - 2004 - Philosophy of Science 71 (4):467-488.
    Many philosophers have claimed that evidence for a theory is better when multiple independent tests yield the same result, i.e., when experimental results are robust. Little has been said about the grounds on which such a claim rests, however. The present essay presents an analysis of the evidential value of robustness that rests on the fallibility of assumptions about the reliability of testing procedures and a distinction between the strength of evidence and the security of an evidence claim. Robustness can (...)
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  • Experimental practice and an error statistical account of evidence.Deborah G. Mayo - 2000 - Philosophy of Science 67 (3):207.
    In seeking general accounts of evidence, confirmation, or inference, philosophers have looked to logical relationships between evidence and hypotheses. Such logics of evidential relationship, whether hypothetico-deductive, Bayesian, or instantiationist fail to capture or be relevant to scientific practice. They require information that scientists do not generally have (e.g., an exhaustive set of hypotheses), while lacking slots within which to include considerations to which scientists regularly appeal (e.g., error probabilities). Building on my co-symposiasts contributions, I suggest some directions in which a (...)
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  • (1 other version)Contrastive knowledge.Antti Karjalainen & Adam Morton - 2003 - Philosophical Explorations 6 (2):74 – 89.
    We describe the three place relation of contrastive knowledge, which holds between a person, a target proposition, and a contrasting proposition. The person knows that p rather than that q. We argue for three claims about this relation. (a) Many common sense and philosophical ascriptions of knowledge can be understood in terms of it. (b) Its application is subject to fewer complications than non-contrastive knowledge is. (c) It applies over a wide range of human and nonhuman cases.
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  • Randomness Is Unpredictability.Antony Eagle - 2005 - British Journal for the Philosophy of Science 56 (4):749-790.
    The concept of randomness has been unjustly neglected in recent philosophical literature, and when philosophers have thought about it, they have usually acquiesced in views about the concept that are fundamentally flawed. After indicating the ways in which these accounts are flawed, I propose that randomness is to be understood as a special case of the epistemic concept of the unpredictability of a process. This proposal arguably captures the intuitive desiderata for the concept of randomness; at least it should suggest (...)
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  • The phenomena of homology.Paul Edmund Griffiths - 2007 - Biology and Philosophy 22 (5):643-658.
    Philosophical discussions of biological classification have failed to recognise the central role of homology in the classification of biological parts and processes. One reason for this is a misunderstanding of the relationship between judgments of homology and the core explanatory theories of biology. The textbook characterisation of homology as identity by descent is commonly regarded as a definition. I suggest instead that it is one of several attempts to explain the phenomena of homology. Twenty years ago the ‘new experimentalist’ movement (...)
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  • Counterexamples to a likelihood theory of evidence.Malcolm R. Forster - 2006 - Minds and Machines 16 (3):319-338.
    The likelihood theory of evidence (LTE) says, roughly, that all the information relevant to the bearing of data on hypotheses (or models) is contained in the likelihoods. There exist counterexamples in which one can tell which of two hypotheses is true from the full data, but not from the likelihoods alone. These examples suggest that some forms of scientific reasoning, such as the consilience of inductions (Whewell, 1858. In Novum organon renovatum (Part II of the 3rd ed.). The philosophy of (...)
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  • Demonstration by simulation: The philosophical significance of experiment in helmholtz's theory of perception.Patrick Joseph McDonald - 2003 - Perspectives on Science 11 (2):170-207.
    : Understanding Helmholtz's philosophy of science requires attention to his experimental practice. I sketch out such a project by showing how experiment shapes his theory of perception in three ways. One, the theory emerged out of empirical and experimental research. Two, the concept of experiment fills a critical conceptual gap in his theory of perception. Experiment functions not merely as a scientific technique, but also as a general epistemological strategy. Three, Helmholtz's experimental practice provides essential clues to the interpretation of (...)
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  • Some epistemological concerns about dissociative identity disorder and diagnostic practices in psychology.Michael J. Shaffer & Jeffery S. Oakley - 2005 - Philosophical Psychology 18 (1):1-29.
    In this paper we argue that dissociative identity disorder (DID) is best interpreted as a causal model of a (possible) post-traumatic psychological process, as a mechanical model of an abnormal psychological condition. From this perspective we examine and criticize the evidential status of DID, and we demonstrate that there is really no good reason to believe that anyone has ever suffered from DID so understood. This is so because the proponents of DID violate basic methodological principles of good causal modeling. (...)
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  • Lessons from the Large Hadron Collider for model-based experimentation: the concept of a model of data acquisition and the scope of the hierarchy of models.Koray Karaca - 2018 - Synthese 195 (12):1-22.
    According to the hierarchy of models account of scientific experimentation developed by Patrick Suppes and elaborated by Deborah Mayo, theoretical considerations about the phenomena of interest are involved in an experiment through theoretical models that in turn relate to experimental data through data models, via the linkage of experimental models. In this paper, I dispute the HoM account in the context of present-day high-energy physics experiments. I argue that even though the HoM account aims to characterize experimentation as a model-based (...)
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  • Lessons from the Large Hadron Collider for model-based experimentation: the concept of a model of data acquisition and the scope of the hierarchy of models.Koray Karaca - 2018 - Synthese 195 (12):5431-5452.
    According to the hierarchy of models (HoM) account of scientific experimentation developed by Patrick Suppes and elaborated by Deborah Mayo, theoretical considerations about the phenomena of interest are involved in an experiment through theoretical models that in turn relate to experimental data through data models, via the linkage of experimental models. In this paper, I dispute the HoM account in the context of present-day high-energy physics (HEP) experiments. I argue that even though the HoM account aims to characterize experimentation as (...)
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  • Preregistration Does Not Improve the Transparent Evaluation of Severity in Popper’s Philosophy of Science or When Deviations are Allowed.Mark Rubin - manuscript
    One justification for preregistering research hypotheses, methods, and analyses is that it improves the transparent evaluation of the severity of hypothesis tests. In this article, I consider two cases in which preregistration does not improve this evaluation. First, I argue that, although preregistration can facilitate the transparent evaluation of severity in Mayo’s error statistical philosophy of science, it does not facilitate this evaluation in Popper’s theory-centric approach. To illustrate, I show that associated concerns about Type I error rate inflation are (...)
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  • Type I error rates are not usually inflated.Mark Rubin - 2021
    The inflation of Type I error rates is thought to be one of the causes of the replication crisis. Questionable research practices such as p-hacking are thought to inflate Type I error rates above their nominal level, leading to unexpectedly high levels of false positives in the literature and, consequently, unexpectedly low replication rates. In this article, I offer an alternative view. I argue that questionable and other research practices do not usually inflate relevant Type I error rates. I begin (...)
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  • Likelihoodism and Guidance for Belief.Tamaz Tokhadze - 2022 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 53 (4):501-517.
    Likelihoodism is the view that the degree of evidential support should be analysed and measured in terms of likelihoods alone. The paper considers and responds to a popular criticism that a likelihoodist framework is too restrictive to guide belief. First, I show that the most detailed and rigorous version of this criticism, as put forward by Gandenberger (2016), is unsuccessful. Second, I provide a positive argument that a broadly likelihoodist framework can accommodate guidance for comparative belief, even when objectively well-grounded (...)
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  • Statistical significance and its critics: practicing damaging science, or damaging scientific practice?Deborah G. Mayo & David Hand - 2022 - Synthese 200 (3):1-33.
    While the common procedure of statistical significance testing and its accompanying concept of p-values have long been surrounded by controversy, renewed concern has been triggered by the replication crisis in science. Many blame statistical significance tests themselves, and some regard them as sufficiently damaging to scientific practice as to warrant being abandoned. We take a contrary position, arguing that the central criticisms arise from misunderstanding and misusing the statistical tools, and that in fact the purported remedies themselves risk damaging science. (...)
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  • Data quality, experimental artifacts, and the reactivity of the psychological subject matter.Uljana Feest - 2022 - European Journal for Philosophy of Science 12 (1):1-25.
    While the term “reactivity” has come to be associated with specific phenomena in the social sciences, having to do with subjects’ awareness of being studied, this paper takes a broader stance on this concept. I argue that reactivity is a ubiquitous feature of the psychological subject matter and that this fact is a precondition of experimental research, while also posing potential problems for the experimenter. The latter are connected to the worry about distorted data and experimental artifacts. But what are (...)
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  • (1 other version)The epistemological foundations of data science: a critical analysis.Jules Desai, David Watson, Vincent Wang, Mariarosaria Taddeo & Luciano Floridi - manuscript
    The modern abundance and prominence of data has led to the development of “data science” as a new field of enquiry, along with a body of epistemological reflections upon its foundations, methods, and consequences. This article provides a systematic analysis and critical review of significant open problems and debates in the epistemology of data science. We propose a partition of the epistemology of data science into the following five domains: (i) the constitution of data science; (ii) the kind of enquiry (...)
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  • SÖZDE-BİLİMSEL KONULAR.Oktay Kızkapan - 2021 - Ankara, Türkiye: Pegem Akademi.
    Sözde-bilim ile ilgili bu tartışmalar uluslararası literatürde yapılıyor olsa da Türkiye’de henüz bu konuların eleştirel olarak ele alındığı söylenemez. Dolayısıyla sözde-bilimlerin eleştirel olarak ele alındığı öğrenme ortamlarının öğrencilerin bilime ve sözde-bilime ilişkin algılarına etkisi üzerine yapılacak araştırmalar konunun daha iyi anlaşılmasını sağlayabilir ve belki de ilerideki program değişiklerinde öğretim programlarında sözde-bilimin yer bulmasının yolunu açabilir.
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  • What is a data model?: An anatomy of data analysis in high energy physics.Antonis Antoniou - 2021 - European Journal for Philosophy of Science 11 (4):1-33.
    Many decades ago Patrick Suppes argued rather convincingly that theoretical hypotheses are not confronted with the direct, raw results of an experiment, rather, they are typically compared with models of data. What exactly is a data model however? And how do the interactions of particles at the subatomic scale give rise to the huge volumes of data that are then moulded into a polished data model? The aim of this paper is to answer these questions by presenting a detailed case (...)
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  • 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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  • How to Assess the Epistemic Wrongness of Sponsorship Bias? The Case of Manufactured Certainty.Jon Leefmann - 2021 - Frontiers In 6 (Article 599909):1-13.
    Although the impact of so-called “sponsorship bias” has been the subject of increased attention in the philosophy of science, what exactly constitutes its epistemic wrongness is still debated. In this paper, I will argue that neither evidential accounts nor social–epistemological accounts can fully account for the epistemic wrongness of sponsorship bias, but there are good reasons to prefer social–epistemological to evidential accounts. I will defend this claim by examining how both accounts deal with a paradigm case from medical epistemology, recently (...)
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  • Were experiments ever neglected? Ian Hacking and the history of philosophy of experiment.Massimiliano Simons & Matteo Vagelli - 2021 - Philosophical Inquiries 9 (1):167-188.
    Ian Hacking’s Representing and Intervening is often credited as being one of the first works to focus on the role of experimentation in philosophy of science, catalyzing a movement which is sometimes called the “philosophy of experiment” or “new experimentalism”. In the 1980s, a number of other movements and scholars also began focusing on the role of experimentation and instruments in science. Philosophical study of experimentation has thus seemed to be an invention of the 1980s whose central figure is Hacking. (...)
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  • Making coherent senses of success in scientific modeling.Beckett Sterner & Christopher DiTeresi - 2021 - European Journal for Philosophy of Science 11 (1):1-20.
    Making sense of why something succeeded or failed is central to scientific practice: it provides an interpretation of what happened, i.e. an hypothesized explanation for the results, that informs scientists’ deliberations over their next steps. In philosophy, the realism debate has dominated the project of making sense of scientists’ success and failure claims, restricting its focus to whether truth or reliability best explain science’s most secure successes. Our aim, in contrast, will be to expand and advance the practice-oriented project sketched (...)
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  • How to be a scientific realist (if at all): a study of partial realism.Dean Peters - 2012 - Dissertation, London School of Economics
    "Partial realism" is a common position in the contemporary philosophy of science literature. It states that the "essential" elements of empirically successful scientific theories accurately represent corresponding features the world. This thesis makes several novel contributions related to this position. Firstly, it offers a new definition of the concept of “empirical success”, representing a principled merger between the use-novelty and unification accounts. Secondly, it provides a comparative critical analysis of various accounts of which elements are "essential" to the success of (...)
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  • The Problem of New Evidence: P-Hacking and Pre-Analysis Plans.Zoe Hitzig & Jacob Stegenga - 2020 - Diametros 17 (66):10-33.
    We provide a novel articulation of the epistemic peril of p-hacking using three resources from philosophy: predictivism, Bayesian confirmation theory, and model selection theory. We defend a nuanced position on p-hacking: p-hacking is sometimes, but not always, epistemically pernicious. Our argument requires a novel understanding of Bayesianism, since a standard criticism of Bayesian confirmation theory is that it cannot represent the influence of biased methods. We then turn to pre-analysis plans, a methodological device used to mitigate p-hacking. Some say that (...)
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  • La valeur de l'incertitude : l'évaluation de la précision des mesures physiques et les limites de la connaissance expérimentale.Fabien Grégis - 2016 - Dissertation, Université Sorbonne Paris Cité Université Paris.Diderot (Paris 7)
    Abstract : A measurement result is never absolutely accurate: it is affected by an unknown “measurement error” which characterizes the discrepancy between the obtained value and the “true value” of the quantity intended to be measured. As a consequence, to be acceptable a measurement result cannot take the form of a unique numerical value, but has to be accompanied by an indication of its “measurement uncertainty”, which enunciates a state of doubt. What, though, is the value of measurement uncertainty? What (...)
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  • How to Do Things with Theory: The Instrumental Role of Auxiliary Hypotheses in Testing.Corey Dethier - 2019 - Erkenntnis 86 (6):1453-1468.
    Pierre Duhem’s influential argument for holism relies on a view of the role that background theory plays in testing: according to this still common account of “auxiliary hypotheses,” elements of background theory serve as truth-apt premises in arguments for or against a hypothesis. I argue that this view is mistaken. Rather than serving as truth-apt premises in arguments, auxiliary hypotheses are employed as “epistemic tools”: instruments that perform specific tasks in connecting our theoretical questions with the world but that are (...)
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  • Productive Theory-Ladenness in fMRI.Emrah Aktunc - forthcoming - Synthese.
    Several developments for diverse scientific goals, mostly in physics and physiology, had to take place, which eventually gave us fMRI as one of the central research paradigms of contemporary cognitive neuroscience. This technique stands on solid foundations established by the physics of magnetic resonance and the physiology of hemodynamics and is complimented by computational and statistical techniques. I argue, and support using concrete examples, that these foundations give rise to a productive theory-ladenness in fMRI, which enables researchers to identify and (...)
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  • Counting experiments.Jonathan Livengood - 2017 - Philosophical Studies 176 (1):175-195.
    In this paper, I show how one might resist two influential arguments for the Likelihood Principle by appealing to the ontological significance of creative intentions. The first argument for the Likelihood Principle that I consider is the argument from intentions. After clarifying the argument, I show how the key premiss in the argument may be resisted by maintaining that creative intentions sometimes independently matter to what experiments exist. The second argument that I consider is Gandenberger’s :475–503, 2015) rehabilitation of Birnbaum’s (...)
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  • 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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  • Why Replication is Overrated.Uljana Feest - 2019 - Philosophy of Science 86 (5):895-905.
    Current debates about the replication crisis in psychology take it for granted that direct replication is valuable and focus their attention on questionable research practices in regard to statistical analyses. This paper takes a broader look at the notion of replication as such. It is argued that all experimentation/replication involves individuation judgments and that research in experimental psychology frequently turns on probing the adequacy of such judgments. In this vein, I highlight the ubiquity of conceptual and material questions in research, (...)
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  • Manipulating the Alpha Level Cannot Cure Significance Testing.David Trafimow, Valentin Amrhein, Corson N. Areshenkoff, Carlos J. Barrera-Causil, Eric J. Beh, Yusuf K. Bilgiç, Roser Bono, Michael T. Bradley, William M. Briggs, Héctor A. Cepeda-Freyre, Sergio E. Chaigneau, Daniel R. Ciocca, Juan C. Correa, Denis Cousineau, Michiel R. de Boer, Subhra S. Dhar, Igor Dolgov, Juana Gómez-Benito, Marian Grendar, James W. Grice, Martin E. Guerrero-Gimenez, Andrés Gutiérrez, Tania B. Huedo-Medina, Klaus Jaffe, Armina Janyan, Ali Karimnezhad, Fränzi Korner-Nievergelt, Koji Kosugi, Martin Lachmair, Rubén D. Ledesma, Roberto Limongi, Marco T. Liuzza, Rosaria Lombardo, Michael J. Marks, Gunther Meinlschmidt, Ladislas Nalborczyk, Hung T. Nguyen, Raydonal Ospina, Jose D. Perezgonzalez, Roland Pfister, Juan J. Rahona, David A. Rodríguez-Medina, Xavier Romão, Susana Ruiz-Fernández, Isabel Suarez, Marion Tegethoff, Mauricio Tejo, Rens van de Schoot, Ivan I. Vankov, Santiago Velasco-Forero, Tonghui Wang, Yuki Yamada, Felipe C. M. Zoppino & Fernando Marmolejo-Ramos - 2018 - Frontiers in Psychology 9.
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  • Duhem’s problem revisited: logical versus epistemic formulations and solutions.Michael Dietrich & Phillip Honenberger - 2020 - Synthese 197 (1):337-354.
    When the results of an experiment appears to disconfirm a hypothesis, how does one know whether it’s the hypothesis, or rather some auxiliary hypothesis or assumption, that is at fault? Philosophers’ answers to this question, now known as “Duhem’s problem,” have differed widely. Despite these differences, we affirm Duhem’s original position that the logical structure of this problem alone does not allow a solution. A survey of philosophical approaches to Duhem’s problem indicates that what allows any philosopher, or scientists for (...)
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  • The objectivity of Subjective Bayesianism.Jan Sprenger - 2018 - European Journal for Philosophy of Science 8 (3):539-558.
    Subjective Bayesianism is a major school of uncertain reasoning and statistical inference. It is often criticized for a lack of objectivity: it opens the door to the influence of values and biases, evidence judgments can vary substantially between scientists, it is not suited for informing policy decisions. My paper rebuts these concerns by connecting the debates on scientific objectivity and statistical method. First, I show that the above concerns arise equally for standard frequentist inference with null hypothesis significance tests. Second, (...)
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  • Was regression to the mean really the solution to Darwin’s problem with heredity?: Essay Review of Stigler, Stephen M. 2016. The Seven Pillars of Statistical Wisdom. Cambridge, Massachusetts: Harvard University Press. [REVIEW]Adam Krashniak & Ehud Lamm - 2017 - Biology and Philosophy (5):1-10.
    Statistical reasoning is an integral part of modern scientific practice. In The Seven Pillars of Statistical Wisdom Stephen Stigler presents seven core ideas, or pillars, of statistical thinking and the historical developments of each of these pillars, many of which were concurrent with developments in biology. Here we focus on Stigler’s fifth pillar, regression, and his discussion of how regression to the mean came to be thought of as a solution to a challenge for the theory of natural selection. Stigler (...)
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  • Evidential holism.Joe Morrison - 2017 - Philosophy Compass 12 (6):e12417.
    Evidential holism begins with something like the claim that “it is only jointly as a theory that scientific statements imply their observable consequences.” This is the holistic claim that Elliott Sober tells us is an “unexceptional observation”. But variations on this “unexceptional” claim feature as a premise in a series of controversial arguments for radical conclusions, such as that there is no analytic or synthetic distinction that the meaning of a sentence cannot be understood without understanding the whole language of (...)
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  • (1 other version)Simplicity, Inference and Modelling: Keeping It Sophisticatedly Simple.Arnold Zellner, Hugo A. Keuzenkamp & Michael McAleer (eds.) - 2001 - New York: Cambridge University Press.
    The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor, 'entia non sunt multiplicanda praeter necessitatem': entities are not to be multiplied beyond necessity. A problem with Ockham's razor is that nearly everybody seems to accept it, but few are able to define its exact meaning and to make it operational in a non-arbitrary way. Using a multidisciplinary perspective including philosophers, mathematicians, econometricians and economists, this 2002 monograph examines simplicity (...)
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  • Robustness Analysis as Explanatory Reasoning.Jonah N. Schupbach - 2018 - British Journal for the Philosophy of Science 69 (1):275-300.
    When scientists seek further confirmation of their results, they often attempt to duplicate the results using diverse means. To the extent that they are successful in doing so, their results are said to be robust. This paper investigates the logic of such "robustness analysis" [RA]. The most important and challenging question an account of RA can answer is what sense of evidential diversity is involved in RAs. I argue that prevailing formal explications of such diversity are unsatisfactory. I propose a (...)
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  • Representation and Invariance of Scientific Structures.Patrick Suppes - 2002 - CSLI Publications (distributed by Chicago University Press).
    An early, very preliminary edition of this book was circulated in 1962 under the title Set-theoretical Structures in Science. There are many reasons for maintaining that such structures play a role in the philosophy of science. Perhaps the best is that they provide the right setting for investigating problems of representation and invariance in any systematic part of science, past or present. Examples are easy to cite. Sophisticated analysis of the nature of representation in perception is to be found already (...)
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  • Climate Simulations: Uncertain Projections for an Uncertain World.Rafaela Hillerbrand - 2014 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 45 (1):17-32.
    Between the fourth and the recent fifth IPCC report, science as well as policy making have made great advances in dealing with uncertainties in global climate models. However, the uncertainties public decision making has to deal with go well beyond what is currently addressed by policy makers and climatologists alike. It is shown in this paper that within an anthropocentric framework, a whole hierarchy of models from various scientific disciplines is needed for political decisions as regards climate change. Via what (...)
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  • State of the Field: Why novel prediction matters.Heather Douglas & P. D. Magnus - 2013 - Studies in History and Philosophy of Science Part A 44 (4):580-589.
    There is considerable disagreement about the epistemic value of novel predictive success, i.e. when a scientist predicts an unexpected phenomenon, experiments are conducted, and the prediction proves to be accurate. We survey the field on this question, noting both fully articulated views such as weak and strong predictivism, and more nascent views, such as pluralist reasons for the instrumental value of prediction. By examining the various reasons offered for the value of prediction across a range of inferential contexts , we (...)
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  • Experimentation in Cognitive Neuroscience and Cognitive Neurobiology.Jacqueline Anne Sullivan - 2014 - In Levy Neil & Clausen Jens (eds.), Handbook on Neuroethics. Springer.
    Neuroscience is a laboratory-based science that spans multiple levels of analysis from molecular genetics to behavior. At every level of analysis experiments are designed in order to answer empirical questions about phenomena of interest. Understanding the nature and structure of experimentation in neuroscience is fundamental for assessing the quality of the evidence produced by such experiments and the kinds of claims that are warranted by the data. This article provides a general conceptual framework for thinking about evidence and experimentation in (...)
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  • Towards the Methodological Turn in the Philosophy of Science.Hsiang-Ke Chao, Szu-Ting Chen & Roberta L. Millstein - 2013 - In Hsiang-Ke Chao, Szu-Ting Chen & Roberta L. Millstein (eds.), Mechanism and Causality in Biology and Economics. Dordrecht: Springer.
    This chapter provides an introduction to the study of the philosophical notions of mechanisms and causality in biology and economics. This chapter sets the stage for this volume, Mechanism and Causality in Biology and Economics, in three ways. First, it gives a broad review of the recent changes and current state of the study of mechanisms and causality in the philosophy of science. Second, consistent with a recent trend in the philosophy of science to focus on scientific practices, it in (...)
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  • A Synthesis of Hempelian and Hypothetico-Deductive Confirmation.Jan Sprenger - 2013 - Erkenntnis 78 (4):727-738.
    This paper synthesizes confirmation by instances and confirmation by successful predictions, and thereby the Hempelian and the hypothetico-deductive traditions in confirmation theory. The merger of these two approaches is subsequently extended to the piecemeal confirmation of entire theories. It is then argued that this synthetic account makes a useful contribution from both a historical and a systematic perspective.
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  • Error and inference: an outsider stand on a frequentist philosophy.Christian P. Robert - 2013 - Theory and Decision 74 (3):447-461.
    This paper is an extended review of the book Error and Inference, edited by Deborah Mayo and Aris Spanos, about their frequentist and philosophical perspective on testing of hypothesis and on the criticisms of alternatives like the Bayesian approach.
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  • Justifying inference to the best explanation as a practical meta-syllogism on dialectical structures.Gregor Betz - 2013 - Synthese 190 (16):3553-3578.
    This article discusses how inference to the best explanation can be justified as a practical meta - argument. It is, firstly, justified as a practical argument insofar as accepting the best explanation as true can be shown to further a specific aim. And because this aim is a discursive one which proponents can rationally pursue in — and relative to — a complex controversy, namely maximising the robustness of one’s position, IBE can be conceived, secondly, as a meta - argument. (...)
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