Computer age statistical inference : algorithms, evidence, and data science /

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Bibliographic Details
Author / Creator:Efron, Bradley, author.
Imprint:New York, NY, USA : Cambridge University Press, 2016.
©2016
Description:xix, 475 pages : color illustrations ; 24 cm.
Language:English
Series:Institute of Mathematical Statistics monographs ; 5
Institute of Mathematical Statistics monographs ; 5.
Subject:
Format: Print Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/10818238
Hidden Bibliographic Details
Other authors / contributors:Hastie, Trevor, author.
ISBN:9781107149892
1107149894
Notes:Includes bibliographical references (page 453-462) and indexes.
Description
Summary:The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Physical Description:xix, 475 pages : color illustrations ; 24 cm.
Bibliography:Includes bibliographical references (page 453-462) and indexes.
ISBN:9781107149892
1107149894