Computer Age Statistical Inference: Algorithms, Evidence, and Data Science
by Bradley Efron, Trevor Hastie
Publisher: Stanford University 2016
ISBN/ASIN: 1107149894
Number of pages: 493
Description:
This book takes us on a 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.
Download or read it online for free here:
Download link
(8.1MB, PDF)
Similar books
Multivariate Statistics: Concepts, Models, and Applicationsby David W. Stockburger - Missouri State University
The book for a course in multivariate statistics for first year graduate or advanced undergraduates. It is neither a mathematical treatise nor a cookbook. Instead of complicated mathematical proofs the author wrote about mathematical ideas.
(16666 views)
A First Course on Time Series Analysis with SASby Michael Falk at al. - University of Wuerzburg
This book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. The book addresses students of statistics, economics, demography, engineering.
(17130 views)
Theory of Statisticsby James E. Gentle - George Mason University
This document is directed toward students for whom mathematical statistics is or will become an important part of their lives. Obviously, such students should be able to work through the details of 'hard' proofs and derivations.
(16184 views)
Engineering Statistics and Quality Controlby Irving W. Burr - McGraw-Hill
The present book is the outgrowth of a course in statistics for engineers which has been given at Purdue University. The book is written primarily as a text book for junior, senior, and graduate students of engineering and physical science.
(17191 views)