Computer Age Statistical Inference: Algorithms, Evidence, and Data Science

• Category: Computer
• Author: Bradley Efron and Trevor Hastie
• Pages: 495 pages
• File type: PDF (493 pages)

Read and download free eBook intituled Computer Age Statistical Inference: Algorithms, Evidence, and Data Science in format PDF (493 pages) – 495 pages created by Bradley Efron and Trevor Hastie.

A masterful guide to how the inferential bases of classical statistics can provide a principled disciplinary frame for the data science of the twenty-first century. Every aspiring data scientist should carefully study this book, use it as a reference, and carry it with them everywhere.

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.

Read and Download Links:

Computer Age Statistical Inference: Algorithms, Evidence, and Data Science