Computer Age Statistical Inference, Student Edition: Algorithms, Evidence, and Data Science
(Part of the Institute of Mathematical Statistics Monographs Series)
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Book Overview
The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. '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? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. 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. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science.
Format:Paperback
Language:English
ISBN:1108823416
ISBN13:9781108823418
Release Date:June 2021
Publisher:Cambridge University Press
Length:506 Pages
Weight:2.45 lbs.
Dimensions:0.9" x 6.0" x 8.9"
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