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 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 has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and (...) made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

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)

With this treatise, an insightful exploration of the probabilistic connection between philosophy and the history of science, the famous economist breathed new life into studies of both disciplines. Originally published in 1921, this important mathematical work represented a significant contribution to the theory regarding the logical probability of propositions. Keynes effectively dismantled the classical theory of probability, launching what has since been termed the “logical-relationist” theory. In so doing, he explored the logical relationships between classifying a proposition as “highly probable” (...) and as a “justifiable induction.” Unabridged republication of the classic 1921 edition. (shrink)

Described by the philosopher A.J. Ayer as a work of 'great originality and power', this book revolutionized contemporary thinking on science and knowledge. Ideas such as the now legendary doctrine of 'falsificationism' electrified the scientific community, influencing even working scientists, as well as post-war philosophy. This astonishing work ranks alongside The Open Society and Its Enemies as one of Popper's most enduring books and contains insights and arguments that demand to be read to this day.

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)

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

A basic system of inductive logic; An axiomatic foundation for the logic of inductive generalization; A survey of inductive systems; On the condition of partial exchangeability; Representation theorems of the de finetti type; De finetti's generalizations of excahngeability; The structure of probabilities defined on first-order languages; A subjectivit's guide to objective chance.

We wish to give a precise formulation of the intuitive concept: The degree to which the known facts support a given hypothesis.

A basic system of inductive logic; An axiomatic foundation for the logic of inductive generalization; A survey of inductive systems; On the condition of partial exchangeability; Representation theorems of the de finetti type; De finetti's generalizations of excahngeability; The structure of probabilities defined on first-order languages; A subjectivit's guide to objective chance.

We express here the statement » The probability of a given b equals r « symbolically by » p = r «. A formal axiomatic calculus can be constructed comprising all the well‐known laws of probability theory. This calculus can be interpreted in various ways. The present paper is a criticism of the subjective interpretation; that is to say, of any interpretation which assumes that probability expresses degrees of incomplete knowledge: a is the statement incompletely known, b is our total (...) knowledge, and p is the degree to which a is entailed by b. The subjective interpretation has often been proposed as an explanation and even a sharpening of the various objective theories . It is shown in the paper that this proposal cannot be realised because the subjective theory cannot lead to results which are compatible with the objective theory. This is due to various reasons, the most important of which is that the objective theory interprets » b « in » p « as a statement of the objective conditions of an experiment and » a « as one of its possible results. The subjective theory on the other hand interprets » b « as our total relevant knowledge which will in general include some knowledge of previous results of the experiment. It is shown that this must lead to incompatibility owing to the fact that this knowledge of previous results must influence the value of the probability.It is shown, in this way, that any probabilistic theory of the process of learning from experience—that is to say, any probabilistic theory of induction—must lead to contradictions.RésuméL'énoncé: » La probabilité de a, si b est donné, est égale à r « est ici exprimé symboliquement par » p = r «. On peut construire un système axiomatique formel qui contient toutes les règles bien connues du calcul des probabilités. Ce calcul formel peut ětre interprété de manières très différentes. L'article contient une critique des interprétations subjectives, c'est‐à‐dire des interprétations qui admettent que la probabilité exprime des degrés de connaissance incomplète: a est un énoncé qu'on ne connaǐt que partiellement, b est notre connaissance totale, et p exprime le degré auquel a est implicitement contenu dans b. L'interprétation subjective a souvent été proposée comme une explication et un renforcement des différentes théories objectives . Dans cet article, l'auteur montre que ce projet n'est pas réalisable, car la théorie subjective mène à des résultats qui contredisent la théorie objective. Plusieurs circonstances sont responsables de cette situation; la plus importante, c'est que la théorie interprète le » b « dans » p « comme une description des conditions objectives d'une expérience . D'autre part, la théorie subjective interprète » b « comme notre savoir total , et ce savoir inclura en général des informations sur les résultats obtenus antérieurement pour cette expérience. L'auteur montre que ce fait conduit à une contradiction entre les deux interprétations, car cette connaissance doit avoir une influence sur la valeur subjective de la probabilité.A l'aide de ce raisonnement, on peut montrer que la théorie des probabilités appliquée au processus inductif tirant une expérience du domaine expérimental conduit à des contradictions.ZusammenfassungDie Aussage » Die Wahrscheinlichkeit von a, wenn b gegeben ist, ist gleich r « wird hier symbolisch durch » p = r « ausgedrückt. Ein formales Axiomensystem kann konstruiert werden, das alle die wohlbekannten Regeln der Wahrscheinlichkeitsrechnung enthält. Dieser formale Kalkül kann in sehr verschiedener Weise interpretiert werden. Der Artikel enthält eine Kritik der subjektiven Interpretationen; das heisst, jener Interpretationen die annehmen, dass die Wahrscheinlichkeit Grade von unvollständigem Wissen ausdrückt: a ist ein Satz der unvollständig gewusst wird, b ist unser Gesamtwissen, und p drückt den Grad aus zu dem a in b implizit enthalten ist. Die subjektive Interpretation wurde oft als eine Erklärung und Verschärfung der verschiedenen objektiven Theorien vorgeschlagen. In dem Artikel wird gezeigt, dass der Vorschlag undurchführbar ist, da die subjektive Theorie zu Resultaten führt, die der objektiven Theorie widersprechen. Verschiedene Umstände tragen zu dieser Situation bei. Der wichtigste dieser Umstände ist, dass die objektive Theorie das » b « in » p « als eine Beschreibung der objektiven Bedingungen eines Experimentes interpretiert . Andererseits interpretiert die subjektive Theorie » b « als unser Gesamtwissen , und dieses wird im allgemeinen Informationen bezüglich früherer Resultate dieses Experiments einschliessen. Es wird gezeigt, dass das zu einem Widerspruch zwischen den Interpretationen führt, da dieses Wissen Einfluss auf den subjektiven Wahrscheinlichkeitswert haben muss.Mit Hilfe dieses Gedankenganges wird gezeigt, dass die Wahrscheinlichkeitstheorie des induktiven Lernens aus der Erfahrung zu Widersprüchen führt. (shrink)