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John Venn was an English mathematician, logician and philosopher noted for introducing the Venn diagram, used in the fields of set theory, probability, logic, statistics, competition math, and computer science. In 1866, Venn published The Logic of Chance, a ground-breaking book which espoused the frequency theory of probability, offering that probability should be determined by how often something is forecast to occur as opposed to "educated" assumptions. Venn then further developed George Boole's theories in the 1881 work Symbolic Logic, where he highlighted what would become known as Venn diagrams.
Offering a bold new vision on the history of modern logic, Lukas M. Verburgt and Matteo Cosci focus on the lasting impact of Aristotle's syllogism between the 1820s and 1930s. For over two millennia, deductive logic was the syllogism and syllogism was the yardstick of sound human reasoning. During the 19th century, this hegemony fell apart and logicians, including Boole, Frege and Peirce, took deductive logic far beyond its Aristotelian borders. However, contrary to common wisdom, reflections on syllogism were also instrumental to the creation of new logical developments, such as first-order logic and early set theory. This volume presents the period under discussion as one of both tradition...
This is the first book to present a carefully chosen and annotated selection of the unpublished writings and correspondence of the English logician John Venn (1834-1923). Today remembered mainly as the inventor of the famous diagram that bears his name, Venn was an important figure of nineteenth-century Cambridge, where he worked alongside leading thinkers, such as Henry Sidgwick and Alfred Marshall, on the development of the Moral Sciences Tripos. Venn published three influential textbooks on logic, contributed some dozen articles to the then newly-established journal Mind, of which he became co-editor in 1892, and counted F.W. Maitland, William Cunningham and Arthur Balfour among his pupil...
Now in its second edition, Probabilistic Models for Dynamical Systems expands on the subject of probability theory. Written as an extension to its predecessor, this revised version introduces students to the randomness in variables and time dependent functions, and allows them to solve governing equations.Introduces probabilistic modeling and explo
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