All of Statistics

All of Statistics is a comprehensive textbook on statistics written by Larry Wasserman, a professor of statistics at Carnegie Mellon University. The book provides a thorough introduction to statistical concepts and methods, including probability theory, statistical inference, regression analysis, and hypothesis testing. It is intended for students and researchers in a variety of fields, including mathematics, engineering, computer science, and the natural and social sciences.

The book is divided into six parts:

1. Probability: This section covers basic concepts in probability theory, including random variables, probability distributions, conditional probability, and Bayes' rule.

2. Statistical Inference: This section covers the principles of statistical inference, including point estimation, confidence intervals, and hypothesis testing.

3. Linear Regression: This section covers linear regression models, including simple linear regression, multiple regression, and logistic regression.

4. Nonparametric Methods: This section covers nonparametric methods, including rank-based tests and density estimation.

5. Bayesian Methods: This section covers Bayesian methods, including Bayes' theorem, Bayesian inference, and hierarchical models.

6. Advanced Topics: This section covers advanced topics in statistics, including high-dimensional data analysis, time series analysis, and causal inference.

Throughout the book, Wasserman emphasizes the importance of understanding the underlying concepts and principles of statistics, rather than just memorizing formulas and procedures. He also provides numerous examples and exercises to help readers develop their skills in statistical analysis.

Overall, All of Statistics is a highly-regarded textbook that provides a comprehensive introduction to statistical theory and methods. It is suitable for undergraduate and graduate students, as well as researchers and practitioners in a range of fields.