Lecture/Presentation

  • Webinar recorded May 9, 2006 presented by Carl Lee of Central Michigan University and hosted by Jackie Miller of The Ohio State University. Do you use hands-on activities in your class? Would you be interested in using data collected by students from different classes at different institutions? Would you be interested in sharing your students' data with others? Does it take more time than you would like to spend in your class for hands-on activities? Do you have to enter the hands-on activity data yourself after the class period? If your answer to any of the above questions is "YES", then, this Real-Time Online Database approach should be beneficial to your class. In this presentation, Dr. Lee (1) introduces the real-time online database (stat.cst.cmich.edu/statact) funded by a NSF/CCL grant, (2) demonstrates how to use the real-time database to teach introductory statistics using two of the real-time activities and (3) shares with you some of the assessment activities including activity work sheets and projects.
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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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  • 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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  • 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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  • 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
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  • A cartoon to teach about one difficulty in conducting medical research compared to education research arising from problems in obtaining informed consent from subjects. 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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  • 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.
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  • 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.
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  • Using cooperative learning methods, this activity provides students with 24 histograms representing distributions with differing shapes and characteristics. By sorting the histograms into piles that seem to go together, and by describing those piles, students develop awareness of the different versions of particular shapes (e.g., different types of skewed distributions, or different types of normal distributions), and that not all histograms are easy to classify. Students also learn that there is a difference between models (normal, uniform) and characteristics (skewness, symmetry, etc.).
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  • This applet relates the pdf of the Normal distribution to the cdf of the Normal distribution. The graph of the cdf is shown above with the pdf shown below. Click "Move" and the scroll bar will advance across the graph highlighting the area under the pdf in red. The z-score is shown as well as the probability less than z (F(z)) and the probability greater than z (1-F(z)).
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