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. Book Cover......Page 1 Title Page......Page 2 CONTENTS......Page 6 Preface......Page 12 1. Probability and Distributions......Page 16 2. Multivariate Distributions......Page 88 3. Some Special Distributions......Page 148 4. Unbiasedness, Consistency, and Limiting Distributions......Page 212 5. Some Elementary Statistical Inferences......Page 248 6. Maximum Likelihood Methods......Page 326 7. Sufficiency......Page 382 8. Optimal Tests of Hypotheses......Page 434 9. Inferences about Normal Models......Page 478 10. Nonparametric Statistics......Page 530 11. Bayesian Statistics......Page 594 12. Linear Models......Page 630 App. A: Mathematics......Page 676 App. B: R and S-PLUS Functions......Page 680 App. C: Tables of Distributions......Page 686 App. D: References......Page 694 App. E: Answers to Selected Exercises......Page 698 INDEX......Page 708 For Two-semester, Beginning Graduate Courses In Mathematical Statistics, And For Senior Undergraduate Mathematics, Statistics, And Actuarial Science Majors, This Text Retains Its Outstanding Ongoing Features And Continues To Provide Students With Excellent Background Material Necessary For A Successful Understanding Of Mathematical Statistics. Probability And Distributions -- Multivariate Distributions -- Some Special Distributions -- Unbiasedness, Consistency, And Limiting Distributions -- Some Elementary Statistical Inferences -- Maximum Likelihood Methods -- Sufficiency -- Optimal Tests Of Hypotheses -- Inferences About Normal Models -- Nonparametric Statistics -- Bayesian Statistics -- Linear Models. Robert V. Hogg, Joseph W. Mckean, Allen T. Craig. Includes Bibliographical References (p. 679-682) And Index. For one or two-semester, undergraduate mathematical statistics course, or for beginning graduate courses in mathematical statistics. This classic text retains its outstanding features and continues to provide students with excellent background in the mathematics of statistics. Extensively revised with three new chapters. The fifth edition of this text offers a careful presentation of the probability needed for mathematical statistics and the mathematics of statistical inference.
