all-of-statistics

This repository contains my personal notes and complete solutions from my self-study of Larry Wasserman's "All of Statistics: A Concise Course in Statistical Inference". This follows an older edition of the book, though there is almost complete overlap with the latest edition.

Main definitions, ideas, and theorems from each chapter are included in the notes, but examples are usually skipped. This repository is not intended as a replacement for the book.

Each included chapter has a Jupyter notebook including notes on the chapter and exercise solutions -- notes and solutions using LaTeX in markdown and executable Python.

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Name		Name	Last commit message	Last commit date
Latest commit History 208 Commits
data		data
.gitignore		.gitignore
Chapter 02 - Probability.ipynb		Chapter 02 - Probability.ipynb
Chapter 03 - Random Variables.ipynb		Chapter 03 - Random Variables.ipynb
Chapter 04 - Expectation.ipynb		Chapter 04 - Expectation.ipynb
Chapter 05 - Inequalities.ipynb		Chapter 05 - Inequalities.ipynb
Chapter 06 - Convergence of Random Variables.ipynb		Chapter 06 - Convergence of Random Variables.ipynb
Chapter 07 - Models, Statistical Inference and Learning.ipynb		Chapter 07 - Models, Statistical Inference and Learning.ipynb
Chapter 08 - Estimating the CDF and Statistical Functionals.ipynb		Chapter 08 - Estimating the CDF and Statistical Functionals.ipynb
Chapter 09 - The Bootstrap.ipynb		Chapter 09 - The Bootstrap.ipynb
Chapter 10 - Parametric Inference.ipynb		Chapter 10 - Parametric Inference.ipynb
Chapter 11 - Hypothesis Testing and p-values.ipynb		Chapter 11 - Hypothesis Testing and p-values.ipynb
Chapter 12 - Bayesian Inference.ipynb		Chapter 12 - Bayesian Inference.ipynb
Chapter 13 - Statistical Decision Theory.ipynb		Chapter 13 - Statistical Decision Theory.ipynb
Chapter 14 - Linear Regression.ipynb		Chapter 14 - Linear Regression.ipynb
Chapter 15 - Multivariate Models.ipynb		Chapter 15 - Multivariate Models.ipynb
Chapter 16 - Inference about Independence.ipynb		Chapter 16 - Inference about Independence.ipynb
Chapter 17 - Undirected Graphs and Conditional Independence.ipynb		Chapter 17 - Undirected Graphs and Conditional Independence.ipynb
Chapter 18 - Loglinear Models.ipynb		Chapter 18 - Loglinear Models.ipynb
Chapter 19 - Causal Inference.ipynb		Chapter 19 - Causal Inference.ipynb
Chapter 20 - Directed Graphs.ipynb		Chapter 20 - Directed Graphs.ipynb
Chapter 21 - Nonparametric Curve Estimation.ipynb		Chapter 21 - Nonparametric Curve Estimation.ipynb
Chapter 22 - Smoothing Using Orthogonal Functions.ipynb		Chapter 22 - Smoothing Using Orthogonal Functions.ipynb
Chapter 23 - Classification.ipynb		Chapter 23 - Classification.ipynb
Chapter 24 - Stochastic Processes.ipynb		Chapter 24 - Stochastic Processes.ipynb
Chapter 25 - Simulation Methods.ipynb		Chapter 25 - Simulation Methods.ipynb
README.md		README.md

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