High School

  • March 11, 2008 Teaching and Learning webinar presented by Deborah Nolan, University of California at Berkeley and hosted by Jackie Miller, The Ohio State University. Computing is an increasingly important element of statistical practice and research. It is an essential tool in our daily work, it shapes the way we think about statistics, and broadens our concept of statistical science. Although many agree that there should be more computing in the statistics curriculum and that statistics students need to be more computationally capable and literate, it can be difficult to determine how the curriculum should change because computing has many dimensions. In this webinar Dr. Nolan explores alternatives to teaching statistics that include innovations in data technologies, modern statistical methods, and a variety of computing skills that will enable our students to become active and engaged participants in scientific discovery.

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  • February 10, 2009 Teaching and Learning webinar presented by Andrew Zieffler, Bob delMas, and Joan Garfield, University of Minnesota, and hosted by Jackie Miller, The Ohio State University. This webinar presents an overview of the materials and research-based pedagogical approach to helping students reason about important statistical concepts. The materials presented were developed by the NSF-funded AIMS (adapting and Implementing Innovative Materials in Statistics) project at the University of Minnesota (www.tc.umn.edu/~aims).

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  • April 14, 2009 Teaching and Learning webinar presented by Beth Chance and Allan Rossman, Cal Poly, and John Holcomb, Cleveland State University, and hosted by Jackie Miller, The Ohio State University. This webinar presents ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. The webinar proposes that this approach leads to deeper conceptual understanding, makes a clear connection between study design and scope of conclusions, and provides a powerful and generalizable analysis framework. During this webinar arguments are presented in favor of such a curriculum, demonstrate some activities through which students can investigate these concepts, highlights some difficulties with implementing this approach, and discusses ideas for assessing student understanding of inference concepts and randomization procedures.
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  • March 24, 2009 Activity webinar presented by Nicholas Horton, Smith College, and hosted by Leigh Slauson, Otterbein College. Students have a hard time making the connection between variance and risk. To convey the connection, Foster and Stine (Being Warren Buffett: A Classroom Simulation of Risk and Wealth when Investing in the Stock Market; The American Statistician, 2006, 60:53-60) developed a classroom simulation. In the simulation, groups of students roll three colored dice that determine the success of three "investments". The simulated investments behave quite differently. The value of one remains almost constant, another drifts slowly upward, and the third climbs to extremes or plummets. As the simulation proceeds, some groups have great success with this last investment--they become the "Warren Buffetts" of the class. For most groups, however, this last investment leads to ruin because of variance in its returns. The marked difference in outcomes shows students how hard it is to separate luck from skill. The simulation also demonstrates how portfolios, weighted combinations of investments, reduce the variance. In the simulation, a mixture of two poor investments is surprisingly good. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and references (extra materials available for download free of charge)

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  • July 28, 2009 Activity webinar presented by Jo Hardin, Pomona College, and hosted by Leigh Slauson, Otterbein College. Based on an activity by John Spurrier, this webinar uses a baseball example to introduce students to Bayesian estimation. Students use prior information to determine prior distributions which lead to different estimators of the probability of a hit in baseball. The webinar also compares different Bayesian estimators and different frequentist estimators using bias, variability, and mean squared error. The effect that sample size and dispersion of the prior distribution have on the estimator is then illustrated by the activity.
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  • A cartoon to teach about the need to think carefully about the assumptions underlying a statistical model (also uses the idea that you can multiply chances for independent events to find the chance that they all occur). Drawn by British cartoonist John Landers based on an idea from Dennis earl. Free to use in the classroom and on course websites.

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  • A cartoon to teach ideas about sample surveys. 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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  • A cartoon suitable for a course website that makes use of a boxplot to display an outlier and also uses the term "statistically significant" in its punch line. The cartoon is number 539 (February, 2009) from the webcomic series at xkcd.com created by Randall Munroe. Free to use in the classroom and on course web sites under a creative commons attribution-non-commercial 2.5 license.

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  • A set of twenty statistics anagrams that might be used for an end of semester terminology review. This collection of anagrams appeared in the article "Even More Fun Learning Stats" by Lawrence M. Lesser in issue #49 (2007) of "Stats" magazine (pp.5-8,19, 27).

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  • A statistics scramble that might be used in teaching goodness-of-fit significance tests. A set of five anagrams must be solved to reveal the letters that provide the answer to the clue in the cartoon. The cartoon was drawn by British cartoonist John Landers based on an idea by Dennis Pearl. Free for use on course websites, or as an in-class, or out-of class exercise.

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