Resource Library

This tutorial on Friedman's Test includes its definition, assumptions, characteristics, and hypotheses. An example using output from the WINKS software is given, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.

This page discusses the differences in parametric and nonparametric tests and when to use then.

Using cooperative learning methods, this activity provides students with 24 histograms representing distributions with differing shapes and characteristics. By sorting the histograms into piles that seem to go together, and by describing those piles, students develop awareness of the different versions of particular shapes (e.g., different types of skewed distributions, or different types of normal distributions), and that not all histograms are easy to classify. Students also learn that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.).

Using cooperative learning methods, this lesson introduces distributions for univariate data, emphasizing how distributions help us visualize central tendencies and variability. Students collect real data on head circumference and hand span, then describe the distributions in terms of shape, center, and spread. The lesson moves from informal to more technically appropriate descriptions of distributions.

Using cooperative learning methods, this activity helps students develop a better intuitive understanding of what is meant by variability in statistics. Emphasis is placed on the standard deviation as a measure of variability. This lesson also helps students to discover that the standard deviation is a measure of the density of values about the mean of a distribution. As such, students become more aware of how clusters, gaps, and extreme values affect the standard deviation.

This site contains 100 modules designed to introduce concepts in statistics. The modules are divided into categories such as Descriptive Statistics, Inferential Statistics, Related Measures, Enumeration Statistics, and ANOVA. Click the green button on the side to start the modules, then click "Main Menu" at the top to see a list of topics. Topics include Describing Numbers, Normal Curve, Sampling Distributions, Hypothesis Testing, Regression, and Chi-Square. The site also includes a glossary, statistical tables and simulations, and a personalized progress report. Key Words: Collection; Central Tendency; Spread; Correlation.

Legal proceedings are like statistics. If you manipulate them, you can prove anything. A quote by Bristish-born Canadian novelist Arthur Hailey (1920 - 2004). The quote is found in the novel "Airpot" (1968; Doubleday, p. 385). The quote also appears in "Statistically Speaking: A dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither.

This text based website provides an explanation of some coincidences that are often discussed. It gives an explanation of the birthday problem along with a graphic display of the probability of birthday matches vs. the number of people included. It also discussess other popular coincidences such as the similarities between John F. Kennedy and Abraham Lincoln. It goes on to discuss steaks of heads and tails along with random features of stocks and the stock market prices.

This lesson introduces the Central Limit Theorem and discusses it in terms of the normal distribution, binomial distribution, and Poisson distribution.

This lesson introduces confidence intervals and how to calculate them. A multiple choice test is given at the end.