Resource Library

This site gives a definition and an example of numerical summaries. Topics include mean, median, quantiles, variance, and standard deviation.

This site gives a definition and an example of normal distributions. Topics include assessing normality and normal probability plots.

This site gives a definition and an example of categorical data. Topics include two-way tables, bar graphs, and segmented bar graphs.

This site gives an explanation, a definition and an example of inference in linear regression. Topics include confidence intervals for intercept and slope, significance tests, mean response, and prediction intervals.

This is a basic web application that allows practice with matching points on a scatterplot to the appropriate correlation coefficient, r. Applet provides four scatterplots to match with four numeric correlations via radio buttons. After making selections, students click to see "correct" answers and keep a running total of proportion of correct matches, then may select four more plots.

This Java based applet gives students an opportunity to work through confidence interval problems for the mean. The material provides written word problems in which an individual must be able to correctly identify the given parts for a confidence interval calculation, and then be able to use this information to find the confidence interval. It gives step by step prompts to encourage students to choose the correct numbers and "cast of characters".

This online, interactive lesson on Bernoulli provides examples, exercises, and applets that cover binomial, geometric, negative binomial, and multinomial distributions.

This site provides a collection of applets and their descriptions. Some of the titles include the Monte Carlo Estimation of Pi, Can You Beat Randomness?, One-Dimensional Random Walk, Two-Dimensional Random Walk, The Anthill and Molecular Motion, Diffusion Limited Aggregation, The Self-Avoiding Walk, Fractal Coastlines, and Forest Fires and Percolation.

This is the description and instructions for the Monte Carlo Estimation of Pi applet. It is a simulation of throwing darts at a figure of a circle inscribed in a square. It shows the relationship between the geometry of the figure and the statistical outcome of throwing the darts.

This is the description and instructions for the Can You Beat Randomness?- The Lottery Game applet. It is a simulation of flipping coins. Students are asked to make conjectures about randomness and how certain strategies affect randomness. It strives to show the "growth of order out of randomness."