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

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Computer age statistical inference :/ Bradley Efron, Trevor Hastie.
Reminder of title:	algorithms, evidence, and data science /
Author:	Efron, Bradley,
other author:	Hastie, Trevor,
Description:	1 online resource (xix, 475 pages) :digital, PDF file(s). :
Notes:	Title from publisher's bibliographic system (viewed on 04 Jul 2016).
Subject:	Mathematical statistics - Data processing. -
Online resource:	https://doi.org/10.1017/CBO9781316576533
ISBN:	9781316576533 (ebook)

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

Computer age statistical inference :algorithms, evidence, and data science /Bradley Efron, Trevor Hastie. - 1 online resource (xix, 475 pages) :digital, PDF file(s). - Institute of Mathematical Statistics monographs ;5. - Institute of Mathematical Statistics monographs ;5..

Title from publisher's bibliographic system (viewed on 04 Jul 2016).

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.

ISBN: 9781316576533 (ebook)Subjects--Topical Terms:

558446
Mathematical statistics
--Data processing.

LC Class. No.: QA276.4 / .E47 2016

Dewey Class. No.: 519.50285

Computer age statistical inference : = algorithms, evidence, and data science /
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500 $a Title from publisher's bibliographic system (viewed on 04 Jul 2016).
520 $a 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.
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