Resource Library

MacAnova is a free, noncommercial, interactive statistical analysis program for Windows 95/98/NT, Windows 3.1 with Win32s, Macintosh and Unix. MacAnova has many capabilities but its strengths are analysis of variance and related models, matrix algebra, time series analysis (time and frequency domain), and (to a lesser extent) uni-variate and multi-variate exploratory statistics.

This site offers links to a multitude of data tables in PDF format. Topics include national trends in injury hospitalizations, trends in health and aging, summary health statistics for the U.S. population, trends in health insurance and access to medical care for children under age 19 years, and many more.

This site provides links to tests and quizzes for the Statistics and Data Analysis for Public Policy and Sociology course at Duke University for 1992 through 1995.

In this handout, students are asked to compare the ages of terminated employees to the ages of retained employees. Students will use the comparison to decide if the data supports the conclusion of age discrimination.

The datasets on this page are classified by analysis technique (ANOVA, Linear Regression, Markov Chain Monte Carlo, Nonlinear Regression, and Univariate Summary Statistics) and by level of difficulty (lower, average, higher). They were originally intended to test statistical software.

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.

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.

This site gives the outlines and shows the lessons for psychology 340/341: Advanced Statistical Methods.

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.