Resource Library

Always expect to find at least one error when you proofread your own statistics. If you don't, you are probably making the same mistake twice. Quote of american demographer Cheryl Russell appearing in "Rules of Thumb" by Tom Parker (Houghton Mifflin, 1983) p. 124. Also to be found in "Statistically Speaking the dictionary of quotations" compiled by Carl Gaither and Alma Cavazos-Gaither p. 81

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 will be an opportunity to talk about how to prepare your USCOTS spotlight for submission to CAUSEweb and to discuss the benefits of submission. Please join us to discuss how to put the spotlight on CAUSEweb.

A cartoon that might be used in introducing scatterplots and correlation. 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.

The AIMS project developed lesson plans and activities based on innovative materials that have been produced in the past few years for introductory statistics courses. These lesson plans and student activity guides were developed to help transform an introductory statistics course into one that is aligned with the Guidelines for Assessment and Instruction in Statistics Education (GAISE) for teaching introductory statistics courses. The lessons build on implications from educational research and also involve students in small and large group discussion, computer explorations, and hands-on activities.

This pdf text file gives a short introduction to the methods of Bayesian inference. It gives a simple example that deals with jumping a paper frog. The topics listed in this document include: An example, comparison of frequentist and Bayesian methods, credible vs. confidence intervals, choice of prior and its effect on the posterior distribution.

A series of 19 songs used to teach Structural Equations Modeling (SEM) by Alan Reifman of Texas Tech University. A video of an in-class performance of the musical on April 27, 2007, is also available at the website. The Musical took second place in the 2007 A-Mu-sing competition.

This limerick was written by Columbia University professor of biostatistics, Joseph L. Fleiss (1938 -2003). It was published along with three other limericks by Dr. Fleiss in a letter to the editor of "The American Statistician" (volume 2; 1967, page 49). It was written while he worked as a biostatistician at the Department of Mental Hygiene of the State of New York just prior to receiving his Ph.D. and joining the faculty at Columbia.

Meditation on Statistical Method is a poem by American poet and Brandeis University professor James Vincent Cunningham (1911 - 1985). The poem was originally published in "The Exclusions of a Rhyme: Poems and Epigrams" (1960; Swallow Press) and may also be found in "The collected poems and epigrams of J.V. Cunningham" (1971; Swallow Press).

This site funded by the Kaiser Family Foundation provides information on health care and demographics for the 50 U.S. states. Users can use interactive maps or search by particular characteristics for each state. Tables can be created and copied and there is also direct data download (in Excel format) from this site. The site includes data on median income, gender, ethnicity, medical and drug spending, HIV/AIDS rates, and over 500 other variables at the state level

This in-class demonstration combines real world data collection with the use of the applet to enhance the understanding of sampling distribution. Students will work in groups to determine the average date of their 30 coins. In turn, they will report their mean to the instructor, who will record these. The instructor can then create a histogram based on their sample means and explain that they have created a sampling distribution. Afterwards, the applet can be used to demonstrate properties of the sampling distribution. The idea here is that students will remember what they physically did to create the histogram and, therefore, have a better understanding of sampling distributions.