000			01744nam a22002057a 4500
008			221028b2021 |||||||| |||| 00| 0 eng d
020			_a9781108823418
082			_a519.5028 EFR-B
100			_aEfron, Bradley
245			_aComputer age statistical inference : _balgorithms, evidence, and data science / _cBradley Efron and Trevor Hastie
260			_aUnited Kingdom _bCambridge University Press _c2021
300			_a491 p.
365			_aGBP _b29.99.
500			_aThe 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.
650			_aMathematical statistics--Data processing
650			_aMathematical statistics
650			_aMachine learning--Statistical methods
650			_aStatistics
700			_aHastie, Trevor
999			_c83230 _d83230