Resource Library

This excerpt from Engineering Statistics Handbook gives a definition for and examples of outliers. A sub-page also discusses Grubbs' Test for Outliers

This lesson describes bootstrapping in the context of a statistics class for psychology students.

This exercise includes a discussion on comparing data with very different sample sizes and nonhomogeneity of variance. The data comes from a study on the behavior of pregnant women with regard to cigarette smoking.

This exercise uses descriptive statistics to analyze a data set about how rats respond to rock music vs. classical music.

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.

This page provides survey data on the sexual activity of male and female subjects and discusses choosing appropriate statistics to describe the data as well as reporting bias. It also links to a Chance article about the same study.

As described in the web page itself: "This document was prepared as an illustration of the use of both t tests and correlation/regression analysis in drawing conclusions from data in an actual study." The study compares athletic performance of swimmers that are optimists vs. pessimists.

This correlation and regression example compares performance on reading comprehension questions to performace on the SAT. It also compares those who read the passage referred to by the questions to those who did not. Exercise questions and answers are also provided.

This set of exercises asks students to model relationships and test them based on the chi-square distribution. The data used is based on testosterone levels and delinquency rate of American military men.

Residual plots and other diagnostics are important to deciding whether or not linear regression is appropriate for a set of data. Many students might believe that if the correlation coefficient is strong enough, these diagnostic checks are not important. The data set included in this activity was created to lure students into a situation that looks on the surface to be appropriate for the use of linear regression but is instead based (loosely) on a quadratic function. Key words: regression, residuals