• Order to parcel locker

    Order to parcel locker
  • easy pay

    easy pay
  • Reduced price
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science

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

9781107149892
327.54 zł
294.78 zł Save 32.76 zł Tax included
Lowest price within 30 days before promotion: 294.78 zł
Quantity
Available in 4-6 weeks

  Delivery policy

Choose Paczkomat Inpost, Orlen Paczka, DPD or Poczta Polska. Click for more details

  Security policy

Pay with a quick bank transfer, payment card or cash on delivery. Click for more details

  Return policy

If you are a consumer, you can return the goods within 14 days. Click for more details

Description
The 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.
Product Details
66969
9781107149892
9781107149892

Data sheet

Publication date
2016
Issue number
1
Cover
hard cover
Pages count
495
Dimensions (mm)
158.00 x 236.00
Weight (g)
930
  • Part I. Classic Statistical Inference:: 1. Algorithms and inference; 2. Frequentist inference; 3. Bayesian inference; 4. Fisherian inference and maximum likelihood estimation; 5. Parametric models and exponential families; Part II. Early Computer-Age Methods:: 6. Empirical Bayes; 7. James-Stein estimation and ridge regression; 8. Generalized linear models and regression trees; 9. Survival analysis and the EM algorithm; 10. The jackknife and the bootstrap; 11. Bootstrap confidence intervals; 12. Cross-validation and Cp estimates of prediction error; 13. Objective Bayes inference and Markov chain Monte Carlo; 14. Statistical inference and methodology in the postwar era; Part III. Twenty-First Century Topics:: 15. Large-scale hypothesis testing and false discovery rates; 16. Sparse modeling and the lasso; 17. Random forests and boosting; 18. Neural networks and deep learning; 19. Support-vector machines and kernel methods; 20. Inference after model selection; 21. Empirical Bayes estimation strategies; Epilogue; References; Index.
Comments (0)