Resource Library

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.

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.

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.

This is an article published in the Journal of Statistics Education describing the ANOVA Visualization Tool and how it can be used in class.

This Java applet helps students visualize features and factors of one and two-way ANOVA tables together with representational models and model parameters.

The Journal of Statistics Education disseminates knowledge for the improvement of statistics education at all levels, including elementary, secondary, post-secondary, post-graduate, continuing, and workplace education. It is distributed electronically and, in accord with its broad focus, publishes articles that enhance the exchange of a diversity of interesting and useful information among educators, practitioners, and researchers around the world. The intended audience includes anyone who teaches statistics, as well as those interested in research on statistical and probabilistic reasoning. All submissions are rigorously refereed using a double-blind peer review process.

The applets in this section demonstrate basic issues of experimental design. The Poor Experimental Design ignores randomization rules and allows for increased experimental error. The Improved Experimental Design offers improvement over the first design by adding randomization and reducing experimental error. Both applets require the input of several participants. The purpose of the applets is to test the reaction times between a participant's dominant and non-dominant hand. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/ExpDesign.html

The applets in this section allow you to see how the common Xbar control chart is constructed with known variance. The Xbar chart is constructed by collecting a sample of size n at different times t. The process is considered to be out of control if the sample mean of the current sample falls above or below the control limits. The user has the options to change each parameter individually and all at once. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/ControlCharts.html