Books & Videos

Table of Contents

  1. Chapter 1 Statistical Thinking for Programmers

    1. Do First Babies Arrive Late?

    2. A Statistical Approach

    3. The National Survey of Family Growth

    4. Tables and Records

    5. Significance

    6. Glossary

  2. Chapter 2 Descriptive Statistics

    1. Means and Averages

    2. Variance

    3. Distributions

    4. Representing Histograms

    5. Plotting Histograms

    6. Representing PMFs

    7. Plotting PMFs

    8. Outliers

    9. Other Visualizations

    10. Relative Risk

    11. Conditional Probability

    12. Reporting Results

    13. Glossary

  3. Chapter 3 Cumulative Distribution Functions

    1. The Class Size Paradox

    2. The Limits of PMFs

    3. Percentiles

    4. Cumulative Distribution Functions

    5. Representing CDFs

    6. Back to the Survey Data

    7. Conditional Distributions

    8. Random Numbers

    9. Summary Statistics Revisited

    10. Glossary

  4. Chapter 4 Continuous Distributions

    1. The Exponential Distribution

    2. The Pareto Distribution

    3. The Normal Distribution

    4. Normal Probability Plot

    5. The Lognormal Distribution

    6. Why Model?

    7. Generating Random Numbers

    8. Glossary

  5. Chapter 5 Probability

    1. Rules of Probability

    2. Monty Hall

    3. Poincaré

    4. Another Rule of Probability

    5. Binomial Distribution

    6. Streaks and Hot Spots

    7. Bayes’s Theorem

    8. Glossary

  6. Chapter 6 Operations on Distributions

    1. Skewness

    2. Random Variables

    3. PDFs

    4. Convolution

    5. Why Normal?

    6. Central Limit Theorem

    7. The Distribution Framework

    8. Glossary

  7. Chapter 7 Hypothesis Testing

    1. Testing a Difference in Means

    2. Choosing a Threshold

    3. Defining the Effect

    4. Interpreting the Result

    5. Cross-Validation

    6. Reporting Bayesian Probabilities

    7. Chi-Square Test

    8. Efficient Resampling

    9. Power

    10. Glossary

  8. Chapter 8 Estimation

    1. The Estimation Game

    2. Guess the Variance

    3. Understanding Errors

    4. Exponential Distributions

    5. Confidence Intervals

    6. Bayesian Estimation

    7. Implementing Bayesian Estimation

    8. Censored Data

    9. The Locomotive Problem

    10. Glossary

  9. Chapter 9 Correlation

    1. Standard Scores

    2. Covariance

    3. Correlation

    4. Making Scatterplots in Pyplot

    5. Spearman’s Rank Correlation

    6. Least Squares Fit

    7. Goodness of Fit

    8. Correlation and Causation

    9. Glossary

  1. Colophon