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Lecture/Presentation

  • June 9, 2009 Teaching and Learning webinar presented by Dalene Stangl, Duke University, and hosted by Jackie Miller, The Oho State University. This webinar presents the core materials used at Duke University to teach Bayesian inference in undergraduate service courses geared toward social science, natural science, pre-med, and/or pre-law students. During the semester this material is presented after completing all chapters of the book Statistics by Freedman, Pisani, and Purves. It uses math at the level of basic algebra.
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  • July 14, 2009 Teaching and Learning webinar resented by Margo Vreeburg Izzo, The Ohio State University Nisonger Center, and hosted by Leigh Slauson, Otterbein University. Teaching a diverse college population is a challenge that most college faculty face each day. Universal Design for Learning is an approach to teaching that takes into consideration different student experiences, different cultures, and other issues such as disability. By examining curriculum and instruction through the context of universal design, you can engage as many students as possible in your college classroom and increase achievement by engaging students through a variety of methods ranging from electronic voting machines during class lectures to podcasts to deliver/reinforce essential course content.
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  • April 28, 2009 Activity webinar presented by Herbert Lee, University of California - Santa Cruz, and hosted by Leigh Slauson, Otterbein College. Getting and retaining the attention of students in an introductory statistics course can be a challenge, and poor motivation or outright fear of mathematical concepts can hinder learning. By using an example as familiar and comforting as chocolate chip cookies, the instructor can make a variety of statistical concepts come to life for the students, greatly enhancing learning. As illustrated in this webnar, topics from variability and exploratory data analysis to hypothesis testing and Bayesian statistics can be illuminated with cookies.
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  • May 26, 2009 Activity webinar presented by Dennis Pearl, The Ohio State Unversity, and hosted by Leigh Slauson, Otterbein College. This webinar describes a computer lab activity using the Flash-based applet at www.causeweb.org/mouse_experiment to teach key principles regarding the value of random assignment. These include: 1) how it helps to eliminate bias when compared with a haphazard assignment process, 2) how it leads to a consistent pattern of results when repeated, and 3) how it makes the question of statistical significance interesting since differences between groups are either from treatment or by the luck of the draw. In this webinar, the activity is demonstrated along with a discussion of goals, context, background materials, class handouts, and assessments.
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  • June 23, 2009 Activity webinar presented and hosted by Leigh Slauson, Otterbein College. This webinar describes an activity that uses the playlist from an iPod music player to teach the concept of random selection, the various sampling techniques, and the use of simulation to estimate probability. The webinar includes a discussion of the background of this activity, the learning goals of the activity, how this activity can be adapted to different levels of technology, suggestions for assessment, and other supplemental reference materials. (handouts and other materials available for free download)
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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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  • Hypotheses like professors, when they are seen not to work any longer in the laboratory, should disappear. This is a quote by British chemist and chemistry education pioneer Henry Edward Armstrong (1848 - 1937). The quote is found in Sir Harold Hartley's chapter on Armstrong in his 1971 book "Studies in the History of Chemistry".
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  • I love pictures. Formulas and symbols - I don't especially like them. is a quote by American probabilist and Bayesian statistical theoretician David Blackwell (1919 - 2010). The quote may be found in the the book "Mathematical People: Profiles and Interviews" edited by D.J. Albers & G.L. Alexanderson (Birkhauser, 1985).
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  • A sketch by Anastasia Mandel reinterpreting "Full Cry" by Heywood Hardy (1892) with the statistical caption "Random noise." This is part of a collection of sketches by Anastasia Mandel and their accompanying statistical captions written by Stan Lipovetsky and Igor Mandel that took first place in the cartoon & art category of the 2009 A-Mu-sing contest sponsored by CAUSE. The collection and their accompanying statistical captions discussed in the paper "How art helps to understand statistics" (Model Assisted Statistics and Applications, 2009) by Stan Lipovetsky and Igor Mandel in volume 4 pages 313-324. Free to use in classrooms and on course websites.
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  • This webinar, presented by Larry Lesser of University of Texas at El Paso, provided a tour of the new CAUSEWeb fun page, showing some sample songs, jokes, and cartoons. Participants engaged in a discussion of the pedagogical issues involved in teaching with humor and were provided resources and a bibliography on the topic. Watch the webinar to learn how to make learning fun! (recorded April 11, 2006)
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