Think Stats

Probability and Statistics for Programmers

by Allen B. Downey, published by O'Reilly Media.

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Code examples and solutions are available from this subversion repository or this zip file.

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Read the related blog Probably Overthinking It.

Description

Think Stats is an introduction to Probability and Statistics for Python programmers.

  • Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets.

  • If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.

  • Most introductory books don't cover Bayesian statistics, but Think Stats is based on the idea that Bayesian methods are too important to postpone. By taking advantage of the PMF and CDF libraries, it is possible for beginners to learn the concepts and solve challenging problems.

This book is under the Creative Commons Attribution-NonCommercial 3.0 Unported License, which means that you are free to copy, distribute, and modify it, as long as you attribute the work and don't use it for commercial purposes.

Other Free Books by Allen Downey are available from Green Tea Press.

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