"How do we go about weighing evidence, testing hypotheses and making inferences? According to the model of 'inference to the Best explanation', we work out what to inter from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In inference to the Best Explanation, Peter Lipton gives this important and influential idea the development and assessment it deserves." "The (...) second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contractive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of Inference to the Best Explanation has also been updated throughout and incudes a new bibliography."--BOOK JACKET. (shrink)

The object of this paper is to show why recent research in the psychology of deductive and probabilistic reasoning does not have.

APA PsycNET abstract: This is the first volume of a two-volume work on Probability and Induction. Because the writer holds that probability logic is identical with inductive logic, this work is devoted to philosophical problems concerning the nature of probability and inductive reasoning. The author rejects a statistical frequency basis for probability in favor of a logical relation between two statements or propositions. Probability "is the degree of confirmation of a hypothesis (or conclusion) on the basis of some given evidence (...) (or premises)." Furthermore, all principles and theorems of inductive logic are analytic, and the entire system is to be constructed by means of symbolic logic and semantic methods. This means that the author confines himself to the formalistic procedures of word and symbol systems. The resulting sentence or language structures are presumed to separate off logic from all subjectivist or psychological elements. Despite the abstractionism, the claim is made that if an inductive probability system of logic can be constructed it will have its practical application in mathematical statistics, and in various sciences. 16-page bibliography. (PsycINFO Database Record (c) 2016 APA, all rights reserved). (shrink)

This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain (...) in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

"First published by Oxford University Press, 1916."--Title page verso.

The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.

Scientific reasoning is—and ought to be—conducted in accordance with the axioms of probability. This Bayesian view—so called because of the central role it accords to a theorem first proved by Thomas Bayes in the late eighteenth ...

First published in 2000. Routledge is an imprint of Taylor & Francis, an informa company.

The final work of a distinguished physicist, this remarkable volume examines the emotive significance of time, the time order of mechanics, the time direction of thermodynamics and microstatistics, the time direction of macrostatistics, and the time of quantum physics. Coherent discussions include accounts of analytic methods of scientific philosophy in the investigation of probability, quantum mechanics, the theory of relativity, and causality. "[Reichenbach’s] best by a good deal."—Physics Today. 1971 ed.

These essays critically reassess the widely accepted view that statistical methods of analysis can, and do, yield causal understanding of social phenomena. They emphasize the historical, philosophical and conceptual perspectives that underlie and inform current methodological controversies.

An introduction to informal logic, critical thinking and rhetoric utilizing actual public discourse .

The present text book is intended as an introduction to elementary logic. Its content, structure, and manner have been determined in large measure - perhaps 'caused' is the better word- by certain desiderata about which the reader should be informed at the outset. The leading idea is that even an introductory treatment of logic may profitably be fashioned around a rigorous framework.

The Aims of the Book -/- 1. To improve your skill in analyzing and evaluating arguments and presentations of the kind you find in everyday discourse (news media, discussions, advertisements), textbooks, and lectures. 2. To improve your skill in presenting arguments, reports and instructions clearly and persuasively. 3. To improve your critical instincts, that is, your immediate judgments of your attitudes toward the communications and behavior of others and yourself, so that you consistently approach them with the standards of reason (...) and the attitude of reasonableness. 4. To improve your knowledge about the facts and arguments relevant to a large number of important contemporary issues in politics, education, ethics, and several practical fields. -/- These are practical aims but not narrow practical aims: the third one, in particular, is very far-reaching and requires a whole shift of values for most of us. So this is intended to be a powerful, as well as practical, book using practical, everyday examples of the kind that a citizen, especially a citizen-student, runs into all the time. -/- The text starts with a short discussion of reasoning itself, then explores the details of this approach, and then gets down to practical procedures for improving one's reasoning skills. The discussions and examples always begin at a rather elementary level, but they get into harder material fairly quickly. If you are, or are hoping to be, a teacher or a lawyer, a scientist or an executive, what you learn here will be professional skills for you—vital professional skills. But for any citizen, they are also essential skills. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

The present study examined the effects of semantic structure on simple inductive judgments about category members. For a particular category, subjects were told that one of the species had a given property and were asked to estimate the proportion of instances in the other species that possessed the property. The results indicated that category structure—in particular, the typicality of the species—influenced subjects' judgments. These results were interpreted by models based on the following assumption: When little is known about the underlying (...) distribution of a property, subjects assume that the distribution mirrors that of better-known properties. For this reason, if subjects learn that an unknown property is possessed by a typical species, they are more likely to generalize than if the same fact had been learned about an atypical species. (shrink)

How do we go about weighing evidence, testing hypotheses, and making inferences? The model of " inference to the best explanation " -- that we infer the hypothesis that would, if correct, provide the best explanation of the available evidence--offers a compelling account of inferences both in science and in ordinary life. Widely cited by epistemologists and philosophers of science, IBE has nonetheless remained little more than a slogan. Now this influential work has been thoroughly revised and updated, and features (...) a new introduction and two new chapters. Inference to the Best Explanation is an unrivaled exposition of a theory of particular interest in the fields both of epistemology and the philosophy of science. (shrink)

This major work challenges some widely held positions in epistemology - those of Peirce and Popper on the one hand and those of Quine and Kuhn on the other.

Mind and environment evolve in tandem—almost a platitude. Much of judgment and decision making research, however, has compared cognition to standard statistical models, rather than to how well it is adapted to its environment. The author argues two points. First, cognitive algorithms are tuned to certain information formats, most likely to those that humans have encountered during their evolutionary history. In par ticular, Bayesian computations are simpler when the information is in a frequency format than when it is in a (...) probability format. The author investigates whether fre quency formats can make physicians reason more often the Bayesian way. Second, cognitive algorithms need to operate under constraints of limited time, knowledge, and computational power, and they need to exploit the structures of their environments. The author describes a fast and frugal algorithm, Take The Best, that violates standard principles of rational inference but can be as accurate as sophisticated "optimal" mod els for diagnostic inference. Key words: Bayes' theorem; bounded rationality; infor mation format; probabilistic reasoning; satisficing; training; medical education. (shrink)

What role have experiments played, and should they play, in physics? How does one come to believe rationally in experimental results? The Neglect of Experiment attempts to provide answers to both of these questions. Professor Franklin's approach combines the detailed study of four episodes in the history of twentieth century physics with an examination of some of the philosophical issues involved. The episodes are the discovery of parity nonconservation in the 1950s; the nondiscovery of parity nonconservation in the 1930s, when (...) the results of experiments indicated, at least in retrospect, the symmetry violation, but the significance of those results was not realized; the discovery and acceptance of CP symmetry; and Millikan's oil-drop experiment. Franklin examines the various roles that experiment plays, including its role in deciding between competing theories, confirming theories, and calling fo new theories. The author argues that one can provide a philosophical justification for these roles. He contends that if experiment plays such important roles, then one must have good reason to believe in experimental results. He then deals with deveral problems concerning such reslults, including the epistemology of experiment, how one comes to believe rationally in experimental results, the question of the influence of theoretical presuppositions on results, and the problem of scientific fruad. This original and important contribution to the study of the philosophy of experimental science is an outgrowth of many years of research. Franklin brings to this work more than a decade of experience as an experimental high-energy physicist, along with his significant contributions to the history and philosophy of science. (shrink)

What role have experiments played, and should they play, in physics? How does one come to believe rationally in experimental results? The Neglect of Experiment attempts to provide answers to both of these questions. Professor Franklin's approach combines the detailed study of four episodes in the history of twentieth century physics with an examination of some of the philosophical issues involved. The episodes are the discovery of parity nonconservation in the 1950s; the nondiscovery of parity nonconservation in the 1930s, when (...) the results of experiments indicated, at least in retrospect, the symmetry violation, but the significance of those results was not realized; the discovery and acceptance of CP symmetry; and Millikan's oil-drop experiment. Franklin examines the various roles that experiment plays, including its role in deciding between competing theories, confirming theories, and calling fo new theories. The author argues that one can provide a philosophical justification for these roles. He contends that if experiment plays such important roles, then one must have good reason to believe in experimental results. He then deals with deveral problems concerning such reslults, including the epistemology of experiment, how one comes to believe rationally in experimental results, the question of the influence of theoretical presuppositions on results, and the problem of scientific fruad. This original and important contribution to the study of the philosophy of experimental science is an outgrowth of many years of research. Franklin brings to this work more than a decade of experience as an experimental high-energy physicist, along with his significant contributions to the history and philosophy of science. (shrink)

How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of _Inference to the Best Explanation_, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In _Inference to the Best Explanation_, Peter Lipton gives this important and influential idea the development and assessment it deserves. The (...) second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of _Inference to the Best Explanation_ has also been updated throughout and includes a new bibliography. (shrink)

An understanding of cause--effect relationships is fundamental to the study of cognition. In this book, outstanding specialists from comparative psychology, social psychology, developmental psychology, anthropology, and philosophy present the newest developments in the study of causal cognition and discuss their different perspectives. They reflect on the role and forms of causal knowledge, both in animal and human cognition, on the development of human causal cognition from infancy, and on the relationship between individual and cultural aspects of causal understanding. The result (...) is a state-of-the-art, informative, insightful, and interdisciplinary debate aimed at the non-specialist. (shrink)

We are pleased to release this edition of Ralph Johnson’s The Rise of Informal Logic as Volume 2 in the series Windsor Studies in Argumentation. This edition is a reprint of the previous Vale Press edition with some typographical errors and other minor mistakes corrected. The prime motive for gathering Ralph H. Johnson’s essays under one cover is their clear articulation of the goals, concerns and problems of the discipline of informal logic. To my knowledge all of the published articles, (...) even of the 1980s, are still in print. But some are obtainable only by special request of a journal back issue. Their availability, even their existence, is not nearly widely enough known, and this volume is dedicated to remedying that disservice to those currently working in the field of informal logic, critical thinking, argumentation, and practical reasoning. Three of these sixteen pieces appear here in print for the first time. The previously published pieces have appeared from 1980 to 1992 as chapters in collective works or as articles in journals, and these in turn published in Canada, USA, The Netherlands and Belgium. It is hoped that gathering this hitherto scattered material under one cover will contribute to a greater understanding of what informal logic is, and to an enhanced sense of the impact of Johnson’s ideas. A discipline of informal logic might exist today without the writings of Johnson and his frequent co-author, J. Anthony Blair. But it would almost certainly be quite different from what it actually is. (shrink)

This is an introductory guide to the basic principles of constructing good arguments and criticizing bad ones. It is nontechnical in its approach, and is based on 150 key examples, each discussed and evaluated in clear, illustrative detail. The author explains how errors, fallacies, and other key failures of argument occur. He shows how correct uses of argument are based on sound argument strategies for reasoned persuasion and critical questions for responding. Among the many subjects covered are: techniques of posing, (...) replying to, and criticizing questions, forms of valid argument, relevance, appeals to emotion, personal attack, uses and abuses of expert opinion, problems in deploying statistics, loaded terms, equivocation, and arguments from analogy. (shrink)

Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling.

... Press for their editorial perspicacity, to the National Institutes of Health for the partial financial support they gave me while I was writing some of the chapters, and to Donald Michie for suggesting the title Good Thinking.

This is an introductory guide to the basic principles of constructing good arguments and criticizing bad ones. It is nontechnical in its approach, and is based on 150 key examples, each discussed and evaluated in clear, illustrative detail. The author explains how errors, fallacies, and other key failures of argument occur. He shows how correct uses of argument are based on sound argument strategies for reasoned persuasion and critical questions for responding. Among the many subjects covered are: techniques of posing, (...) replying to, and criticizing questions, forms of valid argument, relevance, appeals to emotion, personal attack, uses and abuses of expert opinion, problems in deploying statistics, loaded terms, equivocation, and arguments from analogy. (shrink)

Simple Heuristics That Make Us Smart invites readers to embark on a new journey into a land of rationality that differs from the familiar territory of cognitive science and economics. Traditional views of rationality tend to see decision makers as possessing superhuman powers of reason, limitless knowledge, and all of eternity in which to ponder choices. To understand decisions in the real world, we need a different, more psychologically plausible notion of rationality, and this book provides it. It is about (...) fast and frugal heuristics--simple rules for making decisions when time is pressing and deep thought an unaffordable luxury. These heuristics can enable both living organisms and artificial systems to make smart choices, classifications, and predictions by employing bounded rationality. But when and how can such fast and frugal heuristics work? Can judgments based simply on one good reason be as accurate as those based on many reasons? Could less knowledge even lead to systematically better predictions than more knowledge? Simple Heuristics explores these questions, developing computational models of heuristics and testing them through experiments and analyses. It shows how fast and frugal heuristics can produce adaptive decisions in situations as varied as choosing a mate, dividing resources among offspring, predicting high school drop out rates, and playing the stock market. As an interdisciplinary work that is both useful and engaging, this book will appeal to a wide audience. It is ideal for researchers in cognitive psychology, evolutionary psychology, and cognitive science, as well as in economics and artificial intelligence. It will also inspire anyone interested in simply making good decisions. (shrink)