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No Bullshit Guide to Statistics
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
Section 2.2 — Multiple random variables
Section 2.3 — Inventory of discrete distributions
Section 2.4 — Continuous random variables
Section 2.5 — Multiple continuous random variables
Section 2.6 — Inventory of continuous distributions
Section 2.7 — Simulation and empirical distributions
Section 2.8 — Probability models for random samples
Chapter 3 — Classical 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
Appendix F — Calculus tutorial
noBSstats Reading Group
Blog posts
Using Python for learning statistics Part 1
Using Python for probability calculations
Sampling distributions
Bootstrap estimation
Hypothesis testing using simulation
Permutation tests for comparing two groups
Python libraries for doing statistics
Python libraries for doing statistics
Repository
Open issue
Index
