Reprint of the original, first published in 1838.

Ever since the beginning of modern probability theory in the seventeenth century there has been a continuous debate over the meaning and applicability of the concept of probability. This book presents a coherent and well thoughtout framework for the use of probabilistic models to describe unique phenomena in a purely objective way. Although Estimating and Choosing was written with geostatistical applications in mind, the approach is of general applicability across the whole spectrum of probabilistic modelling. The only full-fledged treatment of the foundations of practical probability modelling ever written, this book fills an important gap in the literature of probability and statistics.

This collection of philosophical essays looks at various technical problems in the use of probability theory for guidance in practical decisions. This text is intended for those who already have a basic grounding in philosophy, logic and probabilty theory.

The problem of how to estimate probabilities has interested philosophers, statisticians, actuaries, and mathematicians for a long time. It is currently of interest for automatic recognition, medical diagnosis, and artificial intelligence in general. The main purpose of this monograph is to review existing methods, especially those that are new or have not been written up in a connected manner. The need for nontrivial theory arises because our samples are usually too small for us to rely exclusively on the frequency definition of probability. Most of the techniques described in this book depend on a modern Bayesian approach. The maximum-entropy principle, also relevant to this discussion, is used in the last chapter. It is hoped that the book will stimulate further work in a field whose importance will increasingly be recognized. Methods for estimating probabilities are related to another part of statistics, namely, significance testing, and examples of this relationship are also presented. Many readers will be persuaded by this work that it is necessary to make use of a theory of subjective probability in order to estimate physical probabilities; and also that a useful idea is that of a hierarchy of three types of probability which can sometimes be identified with, physical, logical, and subjective probabilities. The Estimation of Probabilities is intended for statisticians, probabilists, philosophers of science, mathematicians, medical diagnosticians, and workers on artificial intelligence.

This volume brings together many of Terence Horgan's essays on paradoxes: Newcomb's problem, the Monty Hall problem, the two-envelope paradox, the sorites paradox, and the Sleeping Beauty problem. Newcomb's problem arises because the ordinary concept of practical rationality constitutively includes normative standards that can sometimes come into direct conflict with one another. The Monty Hall problem reveals that sometimes the higher-order fact of one's having reliably received pertinent new first-order information constitutes stronger pertinent new information than does the new first-order information itself. The two-envelope paradox reveals that epistemic-probability contexts are weakly hyper-intensional; that therefore, non-zero epistemic probabilities sometimes accrue to epistemic possibilities that are not metaphysical possibilities; that therefore, the available acts in a given decision problem sometimes can simultaneously possess several different kinds of non-standard expected utility that rank the acts incompatibly. The sorites paradox reveals that a certain kind of logical incoherence is inherent to vagueness, and that therefore, ontological vagueness is impossible. The Sleeping Beauty problem reveals that some questions of probability are properly answered using a generalized variant of standard conditionalization that is applicable to essentially indexical self-locational possibilities, and deploys "preliminary" probabilities of such possibilities that are not prior probabilities. The volume also includes three new essays: one on Newcomb's problem, one on the Sleeping Beauty problem, and an essay on epistemic probability that articulates and motivates a number of novel claims about epistemic probability that Horgan has come to espouse in the course of his writings on paradoxes. A common theme unifying these essays is that philosophically interesting paradoxes typically resist either easy solutions or solutions that are formally/mathematically highly technical. Another unifying theme is that such paradoxes often have deep-sometimes disturbing-philosophical morals.

Change and necessity is a statement of Darwinian natural selection as a process driven by chance necessity, devoid of purpose or intent.

This volume presents twelve original essays on the metaphysics of science, with particular focus on the physics of chance and time. Experts in the field subject familiar approaches to searching critiques, and make bold new proposals in a number of key areas. Together, they set the agenda for future work on the subject.

This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.