Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence, business, epidemiology, social science and economics.

This text provides a critique of the subjective Bayesian view of statistical inference, and proposes the author's own error-statistical approach as an alternative framework for the epistemology of experiment. It seeks to address the needs of researchers who work with statistical analysis.

One of Ian Hacking's earliest publications, this book showcases his early ideas on the central concepts and questions surrounding statistical reasoning. He explores the basic principles of statistical reasoning and tests them, both at a philosophical level and in terms of their practical consequences for statisticians. Presented in a fresh twenty-first-century series livery, and including a specially commissioned preface written by Jan-Willem Romeijn, illuminating its enduring importance and relevance to philosophical enquiry, Hacking's influential and original work has been revived for (...) a new generation of readers. (shrink)

Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike [1973], which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light (...) on the theoretical virtues of parsimoniousness, unification, and non ad hocness, on the dispute about Bayesianism, and on empiricism and scientific realism. * Both of us gratefully acknowledge support from the Graduate School at the University of Wisconsin-Madison, and NSF grant DIR-8822278 (M.F.) and NSF grant SBE-9212294 (E.S.). Special thanks go to A. W. F. Edwards.William Harper. Martin Leckey. Brian Skyrms, and especially Peter Turney for helpful comments on an earlier draft. (shrink)

Contemporary Bayesian confirmation theorists measure degree of (incremental) confirmation using a variety of non-equivalent relevance measures. As a result, a great many of the arguments surrounding quantitative Bayesian confirmation theory are implicitly sensitive to choice of measure of confirmation. Such arguments are enthymematic, since they tacitly presuppose that certain relevance measures should be used (for various purposes) rather than other relevance measures that have been proposed and defended in the philosophical literature. I present a survey of this pervasive class of (...) Bayesian confirmation-theoretic enthymemes, and a brief analysis of some recent attempts to resolve the problem of measure sensitivity. (shrink)

Dr Edwards' stimulating and provocative book advances the thesis that the appropriate axiomatic basis for inductive inference is not that of probability, with its addition axiom, but rather likelihood - the concept introduced by Fisher as a measure of relative support amongst different hypotheses. Starting from the simplest considerations and assuming no more than a modest acquaintance with probability theory, the author sets out to reconstruct nothing less than a consistent theory of statistical inference in science.

Another title in the reissued Oxford Classic Texts in the Physical Sciences series, Jeffrey's Theory of Probability, first published in 1939, was the first to develop a fundamental theory of scientific inference based on the ideas of Bayesian statistics. His ideas were way ahead of their time and it is only in the past ten years that the subject of Bayes' factors has been significantly developed and extended. Until recently the two schools of statistics were distinctly different and set apart. (...) Recent work has changed all that and today's graduate students and researchers all require an understanding of Bayesian ideas. This book is their starting point. (shrink)

The text is the Russian translation of W. Whewell’s work “Novum Organon Renovatum” (Preface and Book I Aphorisms concerning ideas), which is the third edition of the second volume of his major work “The philosophy of the Inductive Sciences founded upon their History”. In the text, W. Whewell proposes his theory of scientific method and classification of the necessary scientific ideas as a basis, from where every particular scientific discipline derives. By adopting the structure of the notorious Francis Bacon’s “Novum (...) Organon”, Whewell reverses the order of scientific genesis, opposing himself to inductivism – the most influential philosophical theory of his time. (shrink)

This book presents a clear and critical view of the orthodox logical empiricist tradition, pointing the way to significant developments for the understanding of science both as research and as culture.

William Whewell’s philosophy of scientific discovery is applied to the problem of understanding the nature of unification and explanation by the composition of causes in Newtonian mechanics. The essay attempts to demonstrate: the sense in which ”approximate’ laws successfully refer to real physical systems rather than to idealizations of them; why good theoretical constructs are not badly underdetermined by observation; and why, in particular, Newtonian forces are not conventional and how empiricist arguments against the existence of component causes, and against (...) the veracity of the fundamental laws, are flawed. (shrink)

A system whose expected state changes with time cannot have both a forward-directed translationally invariant probabilistic law and a backward-directed translationally invariant law. When faced with this choice, science seems to favor the former. An asymmetry between cause and effect may help to explain why temporally oriented laws are usually forward-directed.

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The thesis that observation necessarily fails to determine theory is false in the sense that observation can provide overwhelming evidence for a particular theory or even a hypothesis within the theory. The saga of quantum discontinuity illustrates the power of evidence to determine theory and shows how that power can be underestimated by inadequate caricatures of the evidential case. That quantum discontinuity can save the phenomena of black body radiation is the widely known result, but it leaves open the possibilities (...) of other accounts. That these phenomena, with the aid of minimal assumptions, entail quantum discontinuity is the crucial but now largely forgotten result. It was first demonstrated by Ehrenfest and Poincaré in 1911 and 1912. (shrink)

Woodward's long awaited book is an attempt to construct a comprehensive account of causation explanation that applies to a wide variety of causal and explanatory claims in different areas of science and everyday life. The book engages some of the relevant literature from other disciplines, as Woodward weaves together examples, counterexamples, criticisms, defences, objections, and replies into a convincing defence of the core of his theory, which is that we can analyse causation by appeal to the notion of manipulation.

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements (...) of causally relevant parameters contributes to the evidential support of the theory. This is illustrated by Newton's argument from orbital phenomena to the inverse-square law of gravitation. (shrink)

Sober (1984) has considered the problem of determining the evidential support, in terms of likelihood, for a hypothesis that is incomplete in the sense of not providing a unique probability function over the event space in its domain. Causal hypotheses are typically like this because they do not specify the probability of their initial conditions. Sober's (1984) solution to this problem does not work, as will be shown by examining his own biological examples of common cause explanation. The proposed solution (...) will lead to the conclusion, contra Sober, that common cause hypotheses explain statistical correlations and not matchings between event tokens. (shrink)

The Akaike Information Criterion can be a valuable tool of scientific inference. This statistic, or any other statistical method for that matter, cannot, however, be the whole of scientific methodology. In this paper some of the limitations of Akaikean statistical methods are discussed. It is argued that the full import of empirical evidence is realized only by adopting a richer ideal of empirical success than predictive accuracy, and that the ability of a theory to turn phenomena into accurate, agreeing measurements (...) of causally relevant parameters contributes to the evidential support of the theory. This is illustrated by Newton's argument from orbital phenomena to the inverse-square law of gravitation. (shrink)

Van Fraassen has argued that quantum mechanics does not conform to the pattern of common cause explanation used by Salmon as a precise formulation of Smart's 'cosmic coincidence' argument for scientific realism. This paper adds to this list some common examples from classical physics that also do not conform to Salmon's explanatory schema. This is bad news and good news for the realist. The bad news is that Salmon's argument for realism does not work; the good news is that realism (...) need not demand hidden variables in quantum mechanics if they are not used in classical mechanics. Many correlations in physics are explained in terms of property identity (contra Salmon). This leads to a new argument against van Fraassen because the unified version of the theory obtained by identifying theoretical properties is always less empirically adequate. (shrink)

Section 2 will begin by formulating Reichenbach’s principle of common cause in a more general way than is usual but in a way that makes the idea behind it a lot clearer. The way that Salmon has pushed the principle into the services of scientific realism will be explained in terms of an example, van Fraassen objects, Salmon modifies his stand and van Fraassen rejoins - all in section 2. (See van Fraassen 1980, chapter 2).In this episode I think van (...) Fraassen right in claiming - against Salmon that there is no categorical imperative for common cause explanation, and I add my own examples in section 3. The first example ‘is the explanation of the correlation between the equilibrium positions of two objects on a balance in terms of their property of “mass” and the law of moments. (shrink)