Resource Library

Using cooperative learning methods, this activity helps students develop a better intuitive understanding of what is meant by variability in statistics. Emphasis is placed on the standard deviation as a measure of variability. This lesson also helps students to discover that the standard deviation is a measure of the density of values about the mean of a distribution. As such, students become more aware of how clusters, gaps, and extreme values affect the standard deviation.

This tutorial explains the theory and use of the Wilcoxon Matched-Pairs Ranks test and demonstrates it with an example on project quality. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of Pearson's Product Moment Coefficient of Correlation and demonstrates it with an example on GPA and test scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of One-Way ANOVA and demonstrates it with an example on final exam scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of the Chi-Square Test for goodness of fit and demonstrates it with an example on mastery test scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of Multiple Regression and demonstrates it with an example on SAT scores and GPA. Data is given as well as SPSS and Minitab code.

This article introduces Radial Basis Function (RBF) networks. These networks rely heavily on regression analysis techniques. Topics include Nonparametric Regression, Classification and Time Series Prediction, Linear Models, Least Squares, Model Selection Criteria, Ridge Regression, and Forward Selection.

This glossary defines and explains statistical terms for introductory students. The glossary can be shown in alphabetical order or in suggested learning order. Click on the topic of interest to see the definition. Use the arrows at the bottom to proceed to the next topic or click the blue dot to return to the contents page.

This glossary gives definitions for numerous statistical terms, concepts, methods, and rules.

CAST contains three complete introductory statistics courses, one advanced statistical methods course, and additional modules. Each introductory course presents the same topics, but with different applications. The first is a general version, the second is a biometric version with examples relating to biological, agricultural and health sciences, and the third is a business version. Each course comes in a student version and a lecture version. The additional modules cover Multiple and Nonlinear Regression, Quality Control, and Simulation. Registration is required, but free. Individuals or classes can register.