Resource Library

This case study aims to answer the question, "How does one select employees to perform physically demanding jobs?" It examines the relationship between isometric strength tests and job performance for 147 workers. Concepts: correlation, linear regression, multiple regression.

This case study compares a low-fat diet to a "Mediterranean diet" to see which led to better health. Concept: Chi Square test of independence

This case study covers the concepts including: boxplots, stem and leaf displays, two-sample t tests, and analysis of variance. It also assesses the question, "Does an instructor's reputation affect ratings of the instructor's lecture?"

This case study addresses the question: "Will a smiling person accused of a crime be treated more leniently than one who is not smiling? If so, does the type of smile make a difference?" It concerns the following concepts: quantile/boxplots, contrasts among means, Dunnett's test, and Bonferroni correction.

This case study assesses the question, "Can the application of magnetic fields be an effective treatment for pain?" It addresses concepts including: boxplots, stem and leaf displays, correlated t-test, two-sample t-test, repeated measures analysis of variance, and analysis of covariance.

This case study addresses the question: "Does the mere presence of a weapon increase the accessibility of aggressive thoughts?" It concerns the following concepts: quantile and box plots, stem and leaf displays, one-sample t test, confidence interval, within-subjects ANOVA, and consequences of violation of normality assumption.

This is a simulation illustrating the regression toward the mean phenomenon.

This applet demonstrates how the reliability of X and Y affect various aspects of the regression of Y on X.

In this demonstration a scatterplot is displayed and you draw in a regression line by hand. You can then compare your line to the best least squares fit. You can also try to guess the value of Pearson's correlation coefficient.

In this free online video program, "students will advance from histograms through smooth curves to normal curves, and finally to a single normal curve for standardized measurement, as this program shows ways to describe the shape of a distribution using progressively simpler methods. In a lesson on creating a density curve, students also learn why, under steadily decreasing deviation, today's baseball players are less likely to achieve a .400 batting average." This individual video is accessed by scrolling down to the "Individual Program Descriptions - 4. Normal Distributions" and click the "VOD" icon at the top-right of the description.