Resource Library

A cartoon for teaching about the key caveats of correlation and regression. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

This page helps readers know which statistcal tests are appropriate for the different types of data. Two charts display the information. A discussion of study design and sample size, as well as exercise questions with solutions are also provided.

This applet introduces the concept of confidence intervals. Select an alpha level, sample size, and the number of experiments, and click "Play." For each sample, the applet will show the data points as blue dots and the confidence interval as a red, vertical line. The true population mean is shown as a horizontal purple line, and green ovals indicate which intervals do not contain the true mean.

This page provides links to distribution calculators, conceptual demonstration applets, statistical tables, online data analysis packages, function and image-processing tools, and other online computing resources. Key Words: Binomial; Normal; Exponential; Chi-Square; Geometric; Hypergeometric; Negative Binomial; Poisson; Student's T; F-Distribution; Wilcoxon Rank-Sum; Central Limit Theorem; Regression; Normal Approximation to Poisson; Confidence Intervals; Hypothesis Tests; Power; Sample-Size; ANOVA; Galton's Board; Function Plots; Edge Detection; Image Warping & Stretching; Polynomial Model Fitting; Wilcoxon-Mann-Whitney Statistic.

This applet shows a scatterplot of height versus foot length. Users can add or delete points and then guess the regression line by clicking "Your Line" and moving the blue regression line. By clicking "Regression Line" users can see the actual regression line. The applet also shows the correlation and R-square for the data as well as the residuals and squared residuals for the guessed regression line and the actual regression line.

As discussed, the murder rates for Blacks in the United States are substantially higher than those for Whites, with Latino murder rates falling in the middle. These differences have existed throughout the 20th and into the 21st century and, with few exceptions, are found in different sections of the United States. Although biological and genetic explanations for racial differences in crime rates, including murder, have been discredited and are no longer accepted by most criminologists, both cultural and structural theories are widespread in the literature on crime and violence. It is also important to remember that Latino is an ethnic rather than a racial classification. The point of this exercise is to examine differences in selected structural positions of Blacks, Whites and Latinos in the United States that may help explain long-standing differences in their murder rates.

This lesson introduces simple linear regression with several Excel spreadsheet examples such as temperature versus cricket chirps, height versus shoe size, and laziness versus amount of TV watched. These activities require class participation.

This page explains simple linear regression with an example on muscle strength versus lean body mass.

This page provides a table for selecting an appropriate statistical method based on type of data and what information is desired from the data. It also compares parametric and nonparametric tests, one-sided and two-sided p-values, paired and unpaired tests, Fisher's test and the Chi-square test, and regression and correlation. It comes from Chapter 37 of the textbook, "Intuitive Biostatistics".

This applet allows students to explore three methods for measuring "goodness of fit" of a linear model. Users can manipulate both the data and the regression line to see changes in the square error, the absolute error, and the shortest distance from the data point to the regression line.