000			01924 a2200265 4500
005			20250401150644.0
008			180130b xxu||||| |||| 00| 0 eng d
020			_a9781107149892
040			_cIIT Kanpur
041			_aeng
082			_a519.50285 _bEf78c
100			_aEfron, Bradley
245			_aComputer age statistical inference _balgorithms, evidence and data science _cBradley Efron [and] Trevor Hastie
260			_bCambridge University Press _c2016 _aNew York
300			_axix,475p.
440			_aInstitute of mathematical statistics monographs
490			_a / edited by D. R. Cox ...[et al.]
500			_aIncludes bibliographical references and indexes
520			_aThe 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.
650			_aMathematical statistics -- Data processing
650			_aMathematical statistics
650			_aMachine learning -- Statistical methods
700			_aHastie, Trevor
942			_cBK
999			_c558493 _d558493