Resource Library

This site explains the 2x2 factorial experimental design, it's components, and it's effects. Graphs illustrate the concepts discussed.

This resource defines what a p-value is, why .05 is significant, and when to use it. It also covers related topics such as one-tailed/two-tailed tests and hypothesis testing.

Gives four practice problems on the t-test. Gives both the data sets and the mean and standard deviations if you did not want to compute them. Requires students to interpret and reason through some of their answers.

The Against All Odds video series provides an extensive introduction to statistics. It consists of 26 half hour video episodes that include lecturing on statistical topics, animations of statistical topics and video of real world examples. The series is available online or can be purchased on VHS video tape. The statistical material in the series was supervised by Dr. David Moore and accordingly much of the material echos the language used in Moore's textbooks. Topics covered include most topics from an introductory statistics course and slightly more advanced topics such as seasonal variation, blocking of experimental designs and even Chernof faces. The material is very well suited for students in undergraduate statistics classes.

This comprehensive collection of calculators provides users with resources for everything from introductory statistics to advanced statistical methods. Users can search by the following categories: Dictionaries, Courses with Calculators and Applets, Courses All Inclusive, and Statistics A-Z. Users can also search by the following statistical specialties: Agriculture, ANOVA, ANCOVA, Bayesian, Economics, Employment, Health, Information & Library Science, Psychology, Reliability Modeling, Research: Marketing and Opinion, Sampling Analysis, and SAS.

This tutorial illustrates the basic principles of the Central Limit Theorem and enhances conceptual understand of why the Central Limit Theorem is important to inferential statistics.

This tutorial takes the learner step-by-step in applying descriptive and inferential statistics using a real world situation.

This applet demonstrates probability as the area under the normal and the standard normal curves. Students can manipulate mean, standard deviation, and lower and upper bounds to find probabilities.

This simulation applet shows groups of confidence intervals for a given alpha based on a standard normal distribution. It shows how changes in alpha affect the proportion of confidence intervals that contain the mean. An article and an alternative source for this applet can be found at http://www.amstat.org/publications/jse/v6n3/applets/confidenceinterval.html.

This applet allows you to explore the validity of confidence intervals on a proportion with various values for sample size (N) and population proportion (Pi). After you specify N, Pi, the level of confidence, and the number of simulations you wish to perform, the applet samples data according to your specification and computes a confidence interval for each simulation. The proportion of simulations for which the confidence interval contains Pi is recorded. If the method for constructing confidence intervals is valid, then about 95% of the 95% confidence intervals should contain Pi.