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Computer Age Statistical Inference, Student Edition - Algorithms, Evidence, and Data Science (Paperback)
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Computer Age Statistical Inference, Student Edition - Algorithms, Evidence, and Data Science (Paperback)
Series: Institute of Mathematical Statistics Monographs
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The 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.
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