Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs)

ISBN-13: 9781107149892
ISBN-10: 1107149894
Edition: 1
Author: Trevor Hastie, Bradley Efron
Publication date: 2016
Publisher: Cambridge University Press
Format: Hardcover 495 pages
FREE shipping on ALL orders
Sell - Get cash immediately!
Get cash immediately!

Book details

ISBN-13: 9781107149892
ISBN-10: 1107149894
Edition: 1
Author: Trevor Hastie, Bradley Efron
Publication date: 2016
Publisher: Cambridge University Press
Format: Hardcover 495 pages
Category: Algebra , Calculus , Statistics , Computers , Mathematics , Criminal Law

Summary

Acknowledged authors Trevor Hastie , Bradley Efron wrote Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs) comprising 495 pages back in 2016. Textbook and eTextbook are published under ISBN 1107149894 and 9781107149892. Since then Computer Age Statistical Inference: Algorithms, Evidence, and Data Science (Institute of Mathematical Statistics Monographs) textbook was available to sell back to BooksRun online for the top buyback price of $ 17.92 or rent at the marketplace.

Description

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.

Reader reviews

Rate this book!