Introduction to Mathematical Statistics

Introduction to Mathematical Statistics : United States Edition

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Designed for two-semester, beginning graduate courses in Mathematical Statistics, and for senior undergraduate Mathematics, Statistics, and Actuarial Science majors, this text retains its ongoing features and continues to provide students with background material.
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Product details

  • Hardback | 692 pages
  • 180.34 x 231.14 x 27.94mm | 1,111.3g
  • Pearson
  • Upper Saddle River, NJ, United States
  • English
  • 6th edition
  • 0130085073
  • 9780130085078
  • 843,421

Back cover copy

This classic book retains its outstanding ongoing features and continues to provide readers with excellent background material necessary for a successful understanding of mathematical statistics. Chapter topics cover classical statistical inference procedures in estimation and testing, and an in-depth treatment of sufficiency and testing theory--including uniformly most powerful tests and likelihood ratios. Many illustrative examples and exercises enhance the presentation of material throughout the book. For a more complete understanding of mathematical statistics.
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Table of contents

1. Probability and Distribution.

2. Multivariate Distributions.

3. Some Special Distributions.

4. Unbiasedness, Consistency, and Limiting Distributions.

5. Introduction to Inference.

6. Maximum Likelihood Methods.

7. Sufficiency.

8. Optimal Tests of Hypotheses.

9. Inferences about Normal Models.

10. Nonparametric Statistics.

11. Bayesian Statistics.

12. Comparison of Least Squares and Robust Procedures for Linear Models.

Appendix A. Regularity Conditions.

Appendix B. R-Functions.
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Review quote

"The writing style is exceptionally clear; also in the more advanced portion, I haven't any reservations about use. It is a much more professional and modern text than ours. I would seriously consider adopting the text if I teach it again and shall suggest it to my colleagues." - Walter Freiberger, Brown University

"The Hogg/McKean/Craig revision stands out as a modernized version of Hogg and Craig. This revision enhances considerably the statistical inference part with discussion of new procedures and methods, and puts in perspective a broad array of modern statistical methods." - Hosam Mahmoud, George Washington University
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Rating details

74 ratings
3.54 out of 5 stars
5 30% (22)
4 24% (18)
3 27% (20)
2 8% (6)
1 11% (8)
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