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 in Statistical Mechanics features problem sets and exams. Basic principles examined include: the laws of thermodynamics and the concepts of temperature, work, heat, and entropy; postulates of classical statistical mechanics, microcanonical, canonical, and grand canonical distributions; applications to lattice vibrations, ideal gas, photon gas; quantum statistical mechanics; Fermi and Bose systems; and interacting systems: cluster expansions, van der Waal's gas, and mean-field theory.

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 has data sets used by UCLA statistics classes. The html files in the second column contain descriptions of a particular data set and a link to the data at the end of the file. There are also .dat and .dta files that contain just data, with no description.

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 site describes what to do with data sets instead of simply presenting theory and methods as they appear in standard textbooks. It emphasizes statistical practices.

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.