This item has been replaced by Introduction to Mathematical Statistics, 7th Edition
Robert V. Hogg, University of Iowa
Allen T. Craig, Late, Professor of Statistics, University of Iowa
Joseph W. McKean, Western Michigan University
©2005 | Pearson
| Format | Paper |
| ISBN-13: | 9780130085078 |
| Availability |
This item has been replaced by Introduction to Mathematical Statistics, 7th Edition |
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 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
Offers students a complete theory of estimation and testing.
Helps students understand the bootstrap methods used throughout the book.
Makes it easier for students to find various items because more definitions, equations, and theorems are given by chapter section, and display numbers.
Enables students and instructors to find the original source better.
Enhances students' comprehension and retention as they progress through the material.
Offers students a complete theory of estimation and testing.
Helps students understand the bootstrap methods used throughout the book.
Makes it easier for students to find various items because more definitions, equations, and theorems are given by chapter section, and display numbers.
Enables students and instructors to find the original source better.
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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