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  • This website provides data files, examples, guides that are referenced in David Howell's textbook published in 2013. There is also a student manual and links to other useful websites.
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  • This site is a tutorial that takes students through a mayoral election process while discussing the concept of randomness. Topics include margin of error and confidence levels.
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  • This exercise uses descriptive statistics to analyze a data set about how rats respond to rock music vs. classical music.
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  • This short article discusses how the comparative ratios of the tails of normal distributions can result in bias in hiring practices. It contains a link to an applet that shows the comparative tail probability ratios.
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  • PSPP is a statistical analysis program. It is an upwardly compatible replacement of the proprietary statistical analysis program called SPSS. PSPP is a program for statistical analysis of sampled data. It interprets commands in the SPSS language and produces tabular output in ASCII, HTML, or PostScript format.

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  • This activity provides students with 24 histograms representing distributions with differing shapes and characteristics. By sorting the histograms into piles that seem to go together, and by describing those piles, students develop awareness of the different versions of particular shapes (e.g., different types of skewed distributions, or different types of normal distributions), that not all histograms are easy to classify, that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.). Key words: Histogram, shape, normal, uniform, skewed, symmetric, bimodal
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  • This Java applet helps students visualize features and factors of one and two-way ANOVA tables together with representational models and model parameters.
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  • This is an article published in the Journal of Statistics Education describing the ANOVA Visualization Tool and how it can be used in class.
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  • 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.
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  • This module contains discussions on t-test, ANOVA, correlation, two-way factorial ANOVA, regression, chi-squared, and distributions and provides links to a variety of activities relevant to the discussions.
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