• ### Data Analysis

This resource gives 3 questions readers should ask when presented with data and why to ask them: Where did the data come from? Have the data been peer-reviewed? How were the data collected? This page also describes why readers should: be skeptical when dealing with comparisons, and be aware of numbers taken out of context.

• ### Sample Sizes

This resource discusses sample sizes and how they are chosen.
• ### Dataset Example: Student's T

This resource explains the t-distribution and hypothesis testing (informally) using an example on laptop quality.
• ### Webinar: Putting Your Spotlight on CAUSEweb

Submitting your spotlight presentation from USCOTS 2005 to CAUSEweb is an easy process, and you are in a prime position to submit your work! What better way to have your work showcased than in a peer-reviewed repository of contributions to statistics education? This Webinar from January 2006 provided an opportunity to talk about how to prepare your USCOTS spotlight for submission to CAUSEweb and to discuss the benefits of submission.

• ### Cartoon: Question Time

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.
• ### Mouse Experiment

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.
• ### SurfStat Australia

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.
• ### Stat-Attic Statistics Applets for Teaching Topics in Introductory Courses

This site contains links to and descriptions of over 600 applets that can be used for demonstrations or analysis of topics commonly covered in introductory statistics courses.

• ### Dataset Example: A Simple Dataset for Demonstrating Common Distributions

This dataset contains the time of birth, sex, and birth weight for 44 babies born in one 24-hour period at a hospital in Brisbane, Australia. The data can be used for studying some common distributions like the normal, binomial, geometric, Poisson, and exponential.
• ### Video: Statz Rappers

This video is a humorous refresher of statistics methodology. This rap video presents a parody with statistical references. It is quite entertaining.