Resource Library

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 applet lets you explore the effect of violations of the assumptions of normality and homogeneity of variance on the type I error rate and power of t tests (and two-group analysis of variance).

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.

As described on the page itself: "The simulation shows a scatterplot of data from a bivariate distribution in which the relationship between the two variables is linear. You can change the "input" values of slope, standard error of the estimate, or standard deviation of X for this data sample, and see the effects of your change. "

This free online video program "lays out the parts of the confidence interval and gives an example of how it is used to measure the accuracy of long-term mean blood pressure. An example from politics and population surveys shows how margin of error and confidence levels are interpreted. The program also explains the use of a formula to convert the z* values into values on the sampling distribution curve. Finally, the concepts are applied to an issue of animal ethics."

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.