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  • A cartoon to teach about issues in designing a well-controlled experiment. 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.

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  • November 14, 2006 webinar presented by Chrstine Franklin, University of Georgia, and Jessica Utts, University of California and hosted by Jackie Miller, The Ohio State University. In 2005 the American Statistical Association endorsed the recommendations of a report written by leading statistics educators, called "Guidelines for Assessment and Instruction in Statistics Education" (GAISE). The report had two parts - one for K-12 and one for the college introductory statistics course. In this webinar, two members of the report-writing team review the recommendations in the report, and provide suggestions for how to begin to implement them.

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  • October 10, 2006 webinar presented By John Holcomb, Cleveland State University, and hosted by Jackie Miller, The Ohio State University. This webinar presents a quick overview of assessment methods related to student writing assignments and data analysis projects. Beginning with short writing assignments, Dr. Holcomb progresses through a range of different approaches to projects at the introductory course level. On-line resources containing existing project ideas will be shown along with ideas for creating one's own projects. The webinar also discusses several approaches to evaluating the range of assignments.

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  • Webinar presented September 12, 2006 by Brian Jersky, St. Mary's College, and Robert Gould, UCLA, and hosted by Jackie Miller, The Ohio State University. This webinar discusses resources available to educators to assist them in crafting lesson plans that meet the GAISE. The presenters briefly explain the GAISE, which were endorsed by the American Statistical Association and also the National Council of Teachers of Mathematics, and demonstrate various resources offered through CAUSEweb and other channels.

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  • A song for teaching concepts about regression and correlation written by Alan Reifman, Department of Human Development and Family Studies, Texas Tech University. The lyrics may be sung to the tune of Tommy James and Bod King's 1971 song "Draggin' the Line." Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.

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  • This song describes the benefits of using a prior distribution to capture information already known about a topic under study. The lyrics are by Mark Glickman and may be sung to the tune of The Shocking Blue's 1969 song "Venus." The accomanying mp3 recording was produced on May 17, 2008 (Mark Glickman - vocal and guitar)

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  • A cartoon to teach the idea that sampling variability depends on the size of the sample, and not on the size of the population (as long as the sample is a small part of the population). Cartoon drawn by British cartoonist John Landers based on an idea from Dennis Pearl. Free to use in the classroom and for course websites.

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  • A cartoon to teach the idea that the mean is affected by outliers while the median is not. 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.

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  • This song describes the pitfalls of using a steep prior in a Bayesian analysis that is not based on an underlying understanding of the problem. The lyrics were written by Mark Glickman and may be sung to the tune of The Four Seasons' 1975 song "December, 1963 (Oh What a Night)" written by Bob Gaudio and Judy Parker. The mp3 was recorded July 9, 2008 (Mark Glickman - vocals).

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  • This song extols the value of Bayesian thinking. The song was written by Mark Glickman and may be sung to the tune of The Zombie's 1968 song "Time of the Season" written by Rod Argent. The mp3 was recorded on May 24 2008 (Mark Glickman - vocals). This song was first performed live in June 2006 at "Eighth Valencia World Meeting on Bayesian Statistics" in Benidorm, Spain, by Mark Glickman, Brad Carlin, Jennifer Hill, and David Heckerman.

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