Resource Library

Using cooperative learning methods, 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), and that not all histograms are easy to classify. Students also learn that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.).

Using cooperative learning methods, this lesson introduces distributions for univariate data, emphasizing how distributions help us visualize central tendencies and variability. Students collect real data on head circumference and hand span, then describe the distributions in terms of shape, center, and spread. The lesson moves from informal to more technically appropriate descriptions of distributions.

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 site contains 100 modules designed to introduce concepts in statistics. The modules are divided into categories such as Descriptive Statistics, Inferential Statistics, Related Measures, Enumeration Statistics, and ANOVA. Click the green button on the side to start the modules, then click "Main Menu" at the top to see a list of topics. Topics include Describing Numbers, Normal Curve, Sampling Distributions, Hypothesis Testing, Regression, and Chi-Square. The site also includes a glossary, statistical tables and simulations, and a personalized progress report. Key Words: Collection; Central Tendency; Spread; Correlation.

This tutorial explains the theory and use of the Mann-Whitney test and demonstrates it with an example on traditional lecture versus computer-based teaching. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of the Kruskal-Wallis test and demonstrates it with an example on exam scores, homework scores, and project scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of the Friedman Two Way ANOVA and demonstrates it with an example on exam scores, homework scores, and project scores. Data is given as well as SPSS and Minitab code.

This tutorial explains the theory and use of the Spearman's Rank-Difference Correlation Coefficient and demonstrates it with an example on exam scores, homework scores, and project scores. Data is given as well as SPSS and Minitab code.

This collection of tutorials demonstrates various statistical topics with data and provides SPSS and Minitab code. Topics covered: Measures of Central Tendency; Sign Test; Chi-Square; Mann-Whitney Test; Wilcoxon Matched-Pairs Signed-Ranks Test; Kruskal-Wallis One-Way Analysis of Variance; Friedman Two-Way Analysis of Variance; Spearman Rank Correlation; Pearson Product-Moment Correlation; Multiple Regression; t-Test for Independent Samples; t-Test for Matched Pairs; One-Way ANOVA; Two-Way ANOVA.

This tutorial introduces various statistics used to analyze and summarize data. The tutorial covers both the arithmetic and geometric means, median, mode, standard deviation, coefficient of variation, skewness, kurtosis, quadrants, and histrogram analysis. The application is flow cytometry, but others may use this tutorial as well.