Stat.istics

Analyzing and Modeling Rank Data (1996) covers the basic descriptive statistics and models for rank data, i.e., data in which a number of judges rank n of objects from 1 to n.

Multivariate Statistics: Old School (2017) developed from many times teaching Multivariate Analysis (STAT 571).

Mathematical Statistics: Old School (2017) similarly developed from many times teaching Mathematical Statistics (STAT 500, 510).

Notes on Statistical Models for Ranking Data are notes for a course on ranking data that I taught before working on the above ranking book.

Stat 100. A workbook used in an online version of STAT 100, to go along with Statistics by Freedman, Pisani, and Purves.

Statistical Learning. These notes are a riff on the excellent text, The Elements of Statistical Learning by Hastie, Tibshirani, and Friedman.

Analysis of Variance. These notes are based on another excellent text, Plane Answers to Complex Questions by Ronald Christensen.

The Null Distributions of Popular Distance Functions for Rank Vectors (Draft) details exact, approximate, and asymptotic null distributions for various distance functions. It is intended to accompany an R package, everything still being under construction.

Data Program: Analyze data — Histograms, scatter plots, multiple regression, one- and two-way ANOVA, chi-square tests of independence, logistic regression, rotating point clouds.

Guessing correlations: Match correlations with scatter plots. It's a game!

Box models: Randomly draws tickets from a box, to see the law of averages, the central limit theorem, and confidence intervals.

Monty Hall: Win a new car!

Study Worksheet: Input information about a study to see the degree to which you might ascribe causation.