Resource Library

This site give a definition and an example of boxplots. Topics include outliers, medians, as well as lower and upper quartiles.

This site links to the article "Use of R as a Toolbox for Mathematical Statistics Exploration," to activities demonstrating the use of R programming language, and to the site where users can download R. Activities cover the following topics: calculation of a running variance, maximization of a non-linear function, resampling of a statistic, simple Bayesian modeling, sampling from multivariate normal, and estimation of power.

This site gives a definition and an example of scatterplots. Topics include positive and negative association.

This collection of applets simulate many different statistical concepts such as: distributions, correlation, hypothesis testing, regression, and ANOVA.

A good resource for problems in statistics in engineering. Contains some applets, and good textual examples related to engineering. Some topics include Monte Carlo method, Central Limit Theorem, Risk, Logistic Regression, Generalized Linear .Models, and Confidence.

Discusses Markov chains, transition probabilities, and the transition probability matrix.

Discusses the benefits of Taguchi methods applied to engineering.

The user is be able to change the mean and the standard deviation using the sliders and see the density change graphically. The check buttons (68, 95, 99) will help one realize the appropriate percentages of the area under the curve. An example of thiis "68-95-99.7" rule follows.

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".