Designed for a one-semester advanced undergraduate or graduate statistical theory course, this book clearly explains the underlying ideas, mathematics, and principles of major statistical concepts, including parameter estimation, confidence intervals, hypothesis testing, asymptotic analysis, Bayesian inference, linear models etc.

Table of Contents

1. Introduction
2. Point Estimation
3. Confidence Intervals, Bounds, and Regions
4. Hypothesis Testing
5. Asymptotic Analysis
6. Bayesian Inference
7. Elements of Statistical Decision Theory
8. Linear Models
9. Nonparametric Estimation
10. Probabilistic Review
11. Solutions of Selected Exercises

About the Author

Felix Abramovich is a professor at the Department of Statistics and Operations Research at Tel Aviv University.

Ya’acov Ritov is a professor in the Department of Statistics at the University of Michigan, Ann Arbor. He is a professor emeritus of Statistics at the Hebrew University of Jerusalem.