Resource Library

Users can select from detailed tables and geographical comparison tables to generate data from the 2000 Census.

This text document lists detailed learning objectives for introductory statistics courses. Learning objectives are brief, clear statements of what learners will be able to perform at the end of a course. These objectives were developed for a one semester general education introductory statistics course. The objectives cover the broad categories of Graphics, Summary Statistics, The Normal Distribution, Correlation and Scatterplots, Introduction to Regression, Two way Tables, Data Collection and Surveys, Basic Probability, Sampling Distributions, Confidence Intervals, Tests of Hypothesis, and T-distributions.

A short discussion of what outliers are and their helpfulness in analyzing data.

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 short article discusses the difference between "important" and "statistically significant." The data used come from a study comparing male faculty salaries to female faculty salaries.

This short article discusses how the comparative ratios of the tails of normal distributions can result in bias in hiring practices. It contains a link to an applet that shows the comparative tail probability ratios.

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

This site is a tutorial that takes students through a mayoral election process while discussing the concept of randomness. Topics include margin of error and confidence levels.