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  • October 26, 2010 Activity Webinar presented by Tisha Hooks, Winona State University and hosted by Leigh Slauson, Capital University. Extra materials available to download free of charge. The purpose of this webinar is to introduce an activity to enhance students' understanding of various descriptive measures. In particular, by completing this hands-on activity students will experience a visual interpretation of a mean, median, outlier, and the concept of distance-to-mean.
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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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  • A cartoon for use in discussions about the value of using a placebo in an experiment (especially if the results are to be analyzed using a t-test). The cartoon is the work of Theresa McCracken and appears as #6864 on McHumor.com Free for non-profit use in statistics course such as in lectures and course websites.
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  • This issue contains an article that provides an example of a paired samples test related to flying and gliding. It also includes an article about understanding confounding from lurking variables using graphs. Other articles include: a short description about what the t-tests actually tests, an interview with David Moore about why 30 is the "magic" number, a discussion about whether or not outliers should be deleted from a data set, a discussion of observational studies, and a simulation piece about random numbers from non-random arithmetic.
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  • This issue contains an interview with Sallie Keller-McNulty and an article about which came first -- the chicken or the egg. Other articles include a discussion related to an AP Statistics example of seeing the trees for the forest (this focuses on understanding variability between groups and within groups), a discussion of how high r can go, a simulation piece focused on shrinking students, poisoned children, and bootsraps, and an example of a permutation test of the Challenger O-Ring data.
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  • This issue contains articles about microarray data and the partnership between statisticians and biologists, ASA Stat Bowl at JSM 2005, an interview with Stat Bowl 2004 champion Jesse Frey, USCOTS 2005 plans, cluster sampling, an analysis of Civil War intelligence sleuth's Alan Pinkerton's incompetence.
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  • This issue contains articles about the birthday problem probabilities using simulation analysis using R; making money on eBay using multiple regression to estimate prices of violins; McDonald's French fry actual mass vs. industry standard mass student project; PC vs. Mac computers survey of Harvard students; EESEE electronic story and exercise encyclopedia; 12 types of variables used in statistical analysis; the history of probability in the Enlightenment for rational decisions in law, science, and politics.
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  • This issue contains articles about statistics in sports, including batting average, using scatterplots to predict the winners of long-distance races, regression analysis and the NFL, determining the greatest cyclist ever, simulation in public opinion polls, and determining the "best" athletes for cycling and baseball.
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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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  • 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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