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  • August 24, 2010 Activity Webinar presented by Jackie Miller, The Ohio State University and hosted by Leigh Slauson, Capital University. Extra materials available for download free of charge. When Dr. Miller took a graduate course in College Teaching, she learned the jigsaw method. The jigsaw is a cooperative learning technique where students work together in a "home" group on a specific task and then are placed into "jigsaw" groups made up of one member from each home group. For example, if there are 25 students in the class, 5 students would be assigned to each of the A, B, C, D, E home groups, and each jigsaw group would each one member from A, B, C, D, and E. While in the jigsaw groups, the students teach each other what they learned in their home groups. Dr. Miller recalls bringing the idea back with her to one of the OSU elementary statistics courses where it has been used successfully since 1996. Recently a graduate teaching assistant (GTA) suggested to other GTAs that this might be good in another introductory statistics course, and the activity has been adopted successfully . As structured, the jigsaw can be used in an exam review in statistics by assigning students to, say, 5 exercises that they need to master before they go to their jigsaw groups to teach others about their exercise. During this webinar, the webinar presents how the jigsaw is done and address questions like: How do you budget your time for this class activity? How do you know that students are teaching the correct answer? How do you know that students are not just furiously writing down answers instead of listening to understand the concept? Can this work for you? By the end of the webinar, hopefully you will be as intrigued as Dr. Miller was to learn about the jigsaw method and will want to try it in your classroom.
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  • September 28, 2010 Activity webinar presented by Carolyn Cuff, Westminster College and hosted by Leigh Slauson, Capital University. Extra materials available for download free of charge. Students must confront their misconceptions before we can teach them new concepts. Naively, a census is an accurate method to quantify a population parameter. A very brief, memorable and easy to implement activity demonstrates that a census is at best difficult even for a small and easily enumerated population.
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  • Take nothing on its looks; take everything on evidence. There's no better rule. is a quote by English novelist Charles Dickens (1812 - 1870). The quote appears in chapter 40 of his popular novel "Great Expectations" written as a weekly serial from December 1860 to August 1861. The line was spoken in the novel by Mr. Jaggers to Pip.
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  • The quiet statisticians have changed our world - not by discovering new facts or technical developments but by changing the ways we reason, experiment and form our opinions about it. is a quote by Canadian science philosopher Ian Hacking (1936-). The quote is found on page 70 of his 1984 "Science" article "Trial by number" (volume 84 p. 67-70)
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  • This site includes several short tutorials that showcase different features of JMP 7. There is also another site with JMP tutorials at http://stat.fsu.edu/tutorials/
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  • This site contains several videos about how to use Mathematica and how to teach with Mathematica.
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  • This site contains a small collection of videos about how to use Minitab.
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  • This issue contains articles on: The predictive model used by the website FiveThirtyEight.com during the 2008 Presidential election, the design and implementation of an election day exit poll by statistics students, a description of the randomization measures taken to ensure fairness and transparency in the awarding of development grants to farmers in the Republic of Georgia, an explanation of the Item-Matching problem and the Coupon-Collecting problem, together with R code for simulating both problems, and a review of the book, Applied Spatial Statistics for Public Health Data.
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  • This issue contains articles about steroids in baseball; finding ways to make learning statistics fun; an interview with Joan Garfield about Statistics Education; an introduction to response surface methodology; and a look at the vocabulary used in experimental design.
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  • This issue contains articles about binomial confidence intervals; the team effect in stock car racing; using multiple tests (one-sample t-test and sign test); the "two-envelope exchange paradox" (similar to the Monty Hall problem) with discussions of expectation, likelihood, and inference; regression line vs. trend line; calculations of standard normal table values and pi; teaching at a small liberal arts college; modeling extreme events.
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