Free Python Book - Think Stats: Probability and Statistics for Programmers

From today on, I would like to introduce several free online Python Book that may interest you.
Think Stats is an introduction to Probability and Statistics for Python programmers.

Think Stats: Probability and Statistics for Programmers

This HTML version of is provided for convenience, but it is not the best format for the book. In particular, some of the symbols are not rendered correctly.

You might prefer to read the PDF version (Download), or you can buy a hardcopy here.

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Think Stats: Probability and Statistics for Programmers

Allen B. Downey

Version 1.5.9

Copyright 2011 Allen B. Downey

Permission is granted to copy, distribute, and/or modify this document under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported License, which is available athttp://creativecommons.org/licenses/by-nc/3.0/.

• Preface
  • Why I wrote this book
  • How I wrote this book
  • Contributor List
• Statistical thinking for programmers
  • Do first babies arrive late?
  • A statistical approach
  • The National Survey of Family Growth
  • Tables and records
  • Significance
  • Glossary
• Descriptive statistics
  • Means and averages
  • Variance
  • Distributions
  • Representing histograms
  • Plotting histograms
  • Representing PMFs
  • Plotting PMFs
  • Outliers
  • Other visualizations
  • Relative risk
  • Conditional probability
  • Reporting results
  • Glossary
• Cumulative distribution functions
  • The class size paradox
  • The limits of PMFs
  • Percentiles
  • Cumulative distribution functions
  • Representing CDFs
  • Back to the survey data
  • Conditional distributions
  • Random numbers
  • Summary statistics revisited
  • Glossary
• Continuous distributions
  • The exponential distribution
  • The Pareto distribution
  • The normal distribution
  • Normal probability plot
  • The lognormal distribution
  • Why model?
  • Generating random numbers
  • Glossary
• Probability
  • Rules of probability
  • Monty Hall
  • Poincaré
  • Another rule of probability
  • Binomial distribution
  • Streaks and hot spots
  • Bayes’s theorem
  • Glossary
• Operations on distributions
  • Skewness
  • Random Variables
  • PDFs
  • Convolution
  • Why normal?
  • Central limit theorem
  • The distribution framework
  • Glossary
• Hypothesis testing
  • Testing a difference in means
  • Choosing a threshold
  • Defining the effect
  • Interpreting the result
  • Cross-validation
  • Reporting Bayesian probabilities
  • Chi-square test
  • Efficient resampling
  • Power
  • Glossary
• Estimation
  • The estimation game
  • Guess the variance
  • Understanding errors
  • Exponential distributions
  • Confidence intervals
  • Bayesian estimation
  • Implementing Bayesian estimation
  • Censored data
  • The locomotive problem
  • Glossary
• Correlation
  • Standard scores
  • Covariance
  • Correlation
  • Making scatterplots in pyplot
  • Spearman’s rank correlation
  • Least squares fit
  • Goodness of fit
  • Correlation and Causation
  • Glossary
• Index