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An award-winning history of the Enlightenment quest to devise a mathematical model of rationality What did it mean to be reasonable in the Age of Reason? Enlightenment mathematicians such as Blaise Pascal, Jakob Bernoulli, and Pierre Simon Laplace sought to answer this question, laboring over a theory of rational decision, action, and belief under conditions of uncertainty. Lorraine Daston brings to life their debates and philosophical arguments, charting the development and application of probability theory by some of the greatest thinkers of the age. Now with an incisive new preface, Classical Probability in the Enlightenment traces the emergence of new kind of mathematics designed to turn good sense into a reasonable calculus.
"This book presents a comprehensive, insightful survey of the history of probability, both in terms of its scientific and its social uses. . . . It represents a substantial contribution not only to the history of probability but also to our understanding of the Enlightenment in general".--Joseph W. Dauben, "American Scientist".
Were indigenous Americans descendants of the lost tribes of Israel? From the moment Europeans realized Columbus had landed in a place unknown to them in 1492, they began speculating about how the Americas and their inhabitants fit into the Bible. For many, the most compelling explanation was the Hebraic Indian theory, which proposed that indigenous Americans were the descendants of the ten lost tribes of Israel. For its proponents, the theory neatly explained why this giant land and its inhabitants were not mentioned in the Biblical record. In Old Canaan in a New World, Elizabeth Fenton shows that though the Hebraic Indian theory may seem far-fetched today, it had a great deal of currency and significant influence over a very long period of American history. Indeed, at different times the idea that indigenous Americans were descended from the lost tribes of Israel was taken up to support political and religious positions on diverse issues including Christian millennialism, national expansion, trade policies, Jewish rights, sovereignty in the Americas, and scientific exploration. Through analysis of a wide collection of writings—from religious texts to novels—Fenton sheds light on a rarely explored but important part of religious discourse in early America. As the Hebraic Indian theory evolved over the course of two centuries, it revealed how religious belief and national interest intersected in early American history.
This is a history of the use of Bayes theoremfrom its discovery by Thomas Bayes to the rise of the statistical competitors in the first part of the twentieth century. The book focuses particularly on the development of one of the fundamental aspects of Bayesian statistics, and in this new edition readers will find new sections on contributors to the theory. In addition, this edition includes amplified discussion of relevant work.
Contemporary philosopher John Searle has characterized Gottfried Wilhelm Leibniz (1646-1716) as "the most intelligent human being who has ever lived." The German philosopher, mathematician, and logician invented calculus (independently of Sir Isaac Newton), topology, determinants, binary arithmetic, symbolic logic, rational mechanics, and much more. His metaphysics bequeathed a set of problems and approaches that have influenced the course of Western philosophy from Kant in the eighteenth century until the present day. On Leibniz examines many aspects of Leibniz's work and life. This expanded edition adds new chapters that explore Leibniz's revolutionary deciphering machine; his theoretical interest in cryptography and its ties to algebra; his thoughts on eternal recurrence theory; his rebuttal of the thesis of improvability in the world and cosmos; and an overview of American scholarship on Leibniz. Other chapters reveal Leibniz as a substantial contributor to theories of knowledge. Discussions of his epistemology and methodology, its relationship to John Maynard Keynes and Talmudic scholarship, broaden the traditional view of Leibniz. Rescher also views Leibniz's scholarly development and professional career in historical context. As a "philosopher courtier" to the Hanoverian court, Leibniz was associated with the leading intellectuals and politicians of his era, including Spinoza, Huygens, Newton, Queen Sophie Charlotte, and Tsar Peter the Great. Rescher extrapolates the fundamentals of Leibniz's ontology: the theory of possible worlds, the world's contingency, space-time frameworks, and intermonadic relationships. In conclusion, Rescher positions Leibniz as a philosophical role model for today's scholars. He argues that many current problems can be effectively addressed with principles of process philosophy inspired by Leibniz's system of monadology.
Who decides what should be recognized as knowledge? What forces engender knowledge? How do certain forms of it acquire precedence over the rest, and why? Exploring these fundamental questions, this book provides an introductory outline of the vast history of knowledge systems under the broad categories of European and non-European, specifically Indian. It not only traces ontology and epistemology in spatio-temporal terms, but also contextualizes methodological development by comparing Indian and European systems of knowledge and their methods of production as well as techniques ensuring reliability. Knowledge cannot have a history of its own, independent of social history. Therefore, using a vast array of sources, including Greek, Prakrit, Chinese, and Arab texts, the book situates the history of knowledge production within the matrix of multiple socio-economic and politico-cultural systems. Further, the volume also analyses the process of the rise of science and new science and reviews speculative thoughts about the dynamics of the subatomic micro-universe as well as the mechanics of the galactic macro-universe.
By examining the rise of life insurance institutions in 18th-century England, this book offers fresh insight into the history of a commercial society learning to apply speculative techniques to the management of risk.
This book includes algorithms that illustrate the famous Monté Carlo Methods and the computer simulation of stochastic experiments in the areas of random numbers generation, the simulation of random phenomena, the computation of Pi and e (the base of logarithms), both simple and multiple integration, the computation of areas and volumes, probability and statistical distributions, in addition to an introduction to the novel Complex Probability Paradigm. As such, it will be of interest to all scholars, researchers, and undergraduate and graduate students in mathematics, computer science, and science in general.
This book analyses selected algorithms for random and stochastic phenomena in the areas of basic probability, random variables, mathematical expectation, special probability and statistical distributions, random processes, and Markov chains. It also presents a novel approach, titled the “Complex Probability Paradigm”, and applies it to the Brownian motion. As such, the book will be of interest to all scholars, researchers, and undergraduate and graduate students in mathematics, computer science, and science in general.