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The Nature Of Statistics

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The Nature Of Statistics

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Author : W. Allen Wallis
language : en
Publisher: Courier Corporation
Release Date : 2014-04-15

The Nature Of Statistics written by W. Allen Wallis and has been published by Courier Corporation this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-15 with Mathematics categories.

Classic text focuses on everyday applications as well as those of scientific research. Minimal mathematical background necessary. Includes lively examples from business, government, and other fields. "Fascinating." — The New York Times. 1962 edition.

The Nature Of Statistical Evidence

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Author : Bill Thompson
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-21

The Nature Of Statistical Evidence written by Bill Thompson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-21 with Mathematics categories.

The purpose of this book is to discuss whether statistical methods make sense. The present volume begins the task of providing interpretations and explanations of several theories of statistical evidence. It should be relevant to anyone interested in the logic of experimental science. Have we achieved a true Foundation of Statistics? We have made the link with one widely accepted view of science and we have explained the senses in which Bayesian statistics and p-values allow us to draw conclusions. This book has substantial implications for all users of Statistical methods.

The Nature Of Statistics

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Author : Wilson Allen Wallis
language : en
Publisher:
Release Date : 1968

The Nature Of Statistics written by Wilson Allen Wallis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1968 with Statistics categories.

The Nature Of Statistics

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Author : Wilson Allen Wallis
language : en
Publisher:
Release Date : 1962

The Nature Of Statistical Learning Theory

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Author : Vladimir N. Vapnik
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

The Nature Of Statistical Learning Theory written by Vladimir N. Vapnik and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-17 with Mathematics categories.

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning from the general point of view of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. These include: - the general setting of learning problems and the general model of minimizing the risk functional from empirical data - a comprehensive analysis of the empirical risk minimization principle and shows how this allows for the construction of necessary and sufficient conditions for consistency - non-asymptotic bounds for the risk achieved using the empirical risk minimization principle - principles for controlling the generalization ability of learning machines using small sample sizes - introducing a new type of universal learning machine that controls the generalization ability.

The Nature Of Statistical Learning Theory

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Author : Vladimir Vapnik
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-29

The Nature Of Statistical Learning Theory written by Vladimir Vapnik and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-29 with Mathematics categories.

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.