Introduction to Mathematical Statistics
International Edition
6th Edition
Published on 1. July 2004
Book
Paperback/Softback
692 pages
978-0-13-122605-0 (ISBN)
Description
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.
Reviews / Votes
"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
More details
Edition
6th edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
Professional and scholarly
Dimensions
Height: 180 mm
Width: 235 mm
Thickness: 21 mm
Weight
1025 gr
ISBN-13
978-0-13-122605-0 (9780131226050)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions
Robert V. Hogg | Joeseph McKean | Allen T. Craig
Introduction to Mathematical Statistics
International Edition
Book
10/2012
7th Edition
Pearson
€193.73
Article exhausted; check for reprint
Content
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.
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.