Resource Library

This article discusses a project-based approach to teaching statistics. An appendix contains a list of 20 projects that have been successfully assigned.

This course features a full set of lecture notes and problem sets introducing students to the modeling, quantification, and analysis of uncertainty. Topics covered include: formulation and solution in sample space, random variables, transform techniques, simple random processes and their probability distributions, Markov processes, limit theorems, and elements of statistical inference.

This course is second in the series of undergraduate Statistical Physics courses and features comprehensive lecture notes and assignments. Course topics include probability distributions for classical and quantum systems; microcanonical, canonical, and grand canonical partition-functions and associated thermodynamic potentials; conditions of thermodynamic equilibrium for homogeneous and heterogeneous systems; non-interacting Bose and Fermi gases; mean field theories for real gases, binary mixtures, magnetic systems, polymer solutions; phase and reaction equilibria, critical phenomena; fluctuations, correlation functions and susceptibilities, and Kubo formulae; evolution of distribution functions: Boltzmann and Smoluchowski equations.

This article contains practical information on teaching statistics to a political science class.

This page contains a short article on Simpson's Paradox with an example of how standardizing changes the results. It also contains links to other articles on Simpson's Paradox, including a newspaper article illustrating that this topic is timely.

This page contains information and links about statistical literacy. Some links are to textbooks, online articles, resources, and information about upcoming events.

This page discusses disadvantages of large datasets with regard to Simpson's Paradox.

The ICPSR provides access to a large repository of social science and political data. Data sets can be constructed and downloaded for use in most popular statistical packages.

This page is a collection of examples, demonstrations, and exercises that can be used to motivate a lecture, demonstrate an important point, or create a laboratory exercise for students. Topics include the following: Descriptives, Normal Distribution, Sampling Distributions, Probability, Chi-Square, t tests, Power, Correlation/Regression, One-way Anova, Multiple Comparisons, Factorial Anova, Repeated Measures, Multiple Regression, General Linear Model, Log Linear Models, and Distribution-Free Tests.

Each dataset in this collection includes description of the study, description of the data file, statistical topic covered, and reference. Topics addressed include: correlation, one-way ANOVA, Bonferroni multiple comparison procedure, regression (simple, multiple, and loglinear), chi-square, and the t-test.