Resource Library

This Flash based applet simulates data from a case study of treatments for tumor growth in mice. This simulation allows the user to place mice into a control and treatment groups. The simulation then compares the difference in the groups based on this haphazard selection to those of a truly random assignment (the user may also create multiple random assignments and examine the sampling distribution of key statistics). The applet may be used to illustrate three points about random assignment in experiments: 1) how it helps to eliminate bias when compared with a haphazard assignment process, 2) how it leads to a consistent pattern of results when repeated, and 3) how it makes the question of statistical significance interesting since differences between groups are either from treatment or by the luck of the draw. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and assessments. Key Note for Instructors: The data are drawn from a real experiment with an effective treatment but where the response is correlated with animal age and size (so tumor size will tend to be smaller in the treatment group when measured at the end of a randomized experiment but animal age and size should not be). Typically people choosing haphazardly will tend to pick larger/older animals for the treatment group and thus create a bias against the treatment.

This recording of a web seminar (webinar) provides a tour of the Assessment Resource Tools for Improving Statistical Thinking (ARTIST) web site. During this webinar, ARTIST team member Bob delMas guides you through the ARTIST website. The tour includes an overview of an online collection of literature on assessment in statistics education, much of which can be accessed online or downloaded. Resources for creating alternative forms of assessment such as student projects are also presented. You will also learn about efficient ways to create assessments from items from the ARTIST Item Database using a tool known as the Assessment Builder. By the end of the session, you will have learned how to select assessment items and download them in a format that can be edited with a word processor.

A cartoon to use at the end of a class period when the instructor was rushed to finish. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

This JAVA applet assists the user in developing skills to classify a problem as one of the various types of confidence intervals, hypethesis tests and Chi Squared tests. This is not an easy application, but the comprehensive hints provided will improve the users skills in making such classifications.

This tutorial exposes students to conducting chi-square tests in SPSS. This html based tutorial provides extensive screen shots and an example data set.

This tutorial exposes students to conducting multiple comparisons in SPSS. This html based tutorial provides extensive screen shots and an example data set. Topics covered in the tutorial include one way ANOVA, preplanned contrasts, Bonferroni, Post Hoc Tukey's HSD, and Scheffe's multiple contrasts.

I am not accustomed to saying anything with certainty after only one or two observations. is a quote by Flemish anatomist Andreas Vesalius (1514-1564). The quote is found in "Epistola rationem modumque propinandi radicis Chynae decocti".

This website serves as an online textbook for introductory statistics, covering topics such as summarizing and presenting data, producing data, variation and probability, statistical inference, and control charts.

The Decision Bonsai are a hybrid of concept maps and decision trees. They were originally developed to give introductory statistics students a map to inference procedures but have evolved to be used for other topics. The tree is 'grown' during the semester so that students build a picture of the relationships in their mind. Recent work is moving toward the development of more complete concept maps for introductory statistics, statistical quality methods and probability and stochastic processes courses. These Decision Bonsai would be then pointed to at appropriate points in the concept maps.

This introductory probability textbook, freely available here in pdf format, emphasizes the use of computing to simulate experiments and make computations. A set of programs that go with the book and the answers to the odd-numbered problems are also available from this site. Chapter headings include: Discrete Probability, Continuous Probability Densities, Combinatorics, Conditional Probability, Distributions and Densities, Expected Value and Variance, Sums of Random Variables, Law of Large Numbers, Central Limit Theorem, Generating Functions, Markov Chains, and Random Walks.