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No Bullshit Stats Notebooks
Statistics overview
Introduction
Chapter 1: DATA
Chapter 2: Probability theory
Chapter 3: Inferential statistics
Chapter 4: Linear models
Chapter 1 — Data
Section 1.1 — Introduction to data
Section 1.2 — Data in practice
Section 1.3 — Descriptive statistics
Descriptive statistics exercises
Chapter 2 — Probability theory
Section 2.1 — Discrete random variables
Exercises for Section 2.1 Discrete random variables
Section 2.2 — Multiple random variables
Section 2.3 — Inventory of discrete distributions
Section 2.4 — Calculus prerequisites
Section 2.5 — Continuous random variables
Section 2.6 — Inventory of continuous distributions
Section 2.7 — Random variable generation
Section 2.8 — Probability models for random samples
Chapter 3 — Inferential statistics
Section 3.1 — Estimators
Exercises for Section 3.1 Estimates and estimators
Section 3.2 — Confidence intervals
Exercises for Section 3.2 Confidence intervals
Section 3.3 — Introduction to hypothesis testing
Section 3.4 — Hypothesis testing using analytical approximations
Section 3.5 — Two-sample hypothesis tests
Section 3.6 — Statistical design and error analysis
Section 3.7 — Inventory of statistical tests
Statistical analysis examples
Statistical design examples
One-sample z-test for the mean
One-sample t-test for the mean
Welch’s two-sample
\(t\)
-test
Analysis of variance (ANOVA)
Two-sample equivalence test
Chapter 4 — Linear models
Section 4.1 — Simple linear regression
Section 4.2 — Multiple linear regression
Section 4.3 — Interpreting linear models
Section 4.4 — Regression with categorical predictors
Section 4.5 — Model selection for causal inference
Section 4.6 — Generalized linear models
Chapter 5 — Bayesian statistics
Section 5.1 — Introduction to Bayesian statistics
Section 5.2 — Bayesian inference computations
Section 5.3 — Bayesian linear models
Section 5.4 — Bayesian difference between means
Section 5.5 — Hierarchical models
Appendix
Appendix C — Python tutorial
Appendix D — Pandas tutorial
Appendix E — Seaborn tutorial
Calculus tutorial
Blog posts
Using Python for learning statistics Part 1
Repository
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