This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.
Author(s): George Casella; Roger L. Berger
Edition: 2
Publisher: Cengage Learning
Year: 2001
Language: English
Pages: 688
Contents
Colophon
Preface to the Second Edition
Preface to the First Edition
1. Probability Theory
2. Transformations and Expectations
3. Common Families of Distributions
4. Multiple Random Variables
5. Properties of Random Sample
6. Principles of Data Reduction
7. Point Estimation
8. Hypothesis Testing
9. Interval Estimation
10. Asymptotic Evaluations
11. Analysis of Variance and Regression
12. Regression Models
Appendix: Computer Algebra
Table of Common Distributions
References
Author Index
Subject Index
