Faculty

  • February 13, 2007 webinar presented by Jim Albert, Bowling Green State University, and hosted by Jackie Miller, The Ohio State University. An introductory statistics course is described that is entirely taught from a baseball perspective. This class has been taught as a special section of the basic introductory course offered at Bowling Green State University . Topics in data analysis are communicated using current and historical baseball datasets. Probability is introduced by describing and playing tabletop baseball games. Inference is taught by distinguishing between a player's "ability" and his "performance", and then describing how one can learn about a player's ability based on his season performance. Baseball issues such as the proper interpretation of situational and "streaky" data are used to illustrate statistical inference.

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  • April 10, 2007 webinar presented by Maria C. Pruchnicki, The Ohio State University, and hosted by Jackie Miller, The Ohio State University. Distance education and online learning opportunities, collectively known as "e-learning", are becoming increasingly used in higher education. Nationally, online enrollment increased to 3.2 million students in 2005, compared to 2.3 million in 2004. Furthermore, nearly 60% of higher education institutions identify e-learning as part of their long-term education strategy. Newer educational technologies including course management systems and Internet-based conferencing software can be used to both deliver content and engage participants as part of a social learning community. However, even experienced faculty can face pedagogical and operational challenges as they transition to the online environment. This interactive presentation discusses a systematic approach to developing web-based instruction, with an Ohio State University experience as a case example.
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  • December 11, 2007 Teaching and Learning webinar presented by Mark L. Berenson, Montclair State University, and hosted by Jackie Miller, he Ohio State University. As we consider how we might improve our introductory statistics courses, we are constrained by a variety of environmental/logistical and pedagogical issues that must be addressed if we want our students to complete the course saying it was useful, it was relevant and practical, and that it increased their communicational, computational, technological and analytical skills. If not properly considered, such issues may result in the course being considered unsatisfying, incomprehensible, and/or unnecessarily obtuse. This Webinar focuses on key course content concerns that must be addressed and engages participants in discussing resolutions. Participants also had the opportunity to describe and discuss other content barriers to effective statistical pedagogy.

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  • September 9, 2008 Teaching and Learning webinar presented by Joan Garfield and Michelle Everson, University of Minnesota and hosted by Jackie Miller, The Ohio State University. This webinar discusses issues and challenges in preparing teachers of statistics at the secondary and college level. It then provides a case study of a graduate level course taught at the University of Minnesota that focuses on developing excellent teachers of statistics. The course is based on the GAISE guidelines and helps the students develop both knowledge of teaching (pedagogical knowledge) and specific knowledge about teaching statistics (pedagogical content knowledge). Topics, readings, activities, assessments, and discussions are described. In addition, the webinar discusses how the course was transformed from a face-to-face setting to an online environment.

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  • October 14, 2008 Teaching and Learning webinar presented by Daniel Kaplan, Macalester College and hosted by Jackie Miller, The Ohio State University. George Cobb describes the core logic of statistical inference in terms of the three Rs: Randomize, Repeat, Reject. Note that all three Rs involve process or action. Teaching this core logic is more effective when students are able to carry out these actions on real data. This webinar shows how to use computers effectively with introductory-level students to teach them the three Rs of inference. This is done with another R: the statistical software package. The simulations that are carried out involve constructing confidence intervals, demonstrating the idea of "coverage," hypothesis testing, and confounding and covariation.
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  • January 13, 2009 Teaching and Learning webinar presented by Jo Hardin, Pomona College and hosted by Jackie Miller, The Ohio State University. This webinar discusses the development and teaching of a freshman seminar course. In this course, students investigate the practical, ethical, and philosophical issues raised by the use of statistics and probabilistic thinking in realms such as politics, medicine, sports, the law, and genetics. Students explore issues from fiction, the mainstream media, and scientific articles in peer-reviewed journals. To do all of this, they must consider a wide range of statistical topics as well as encountering a range of uses and abuses of statistics in the world today.
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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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  • May 12, 2009 Teaching and Learning hour-long webinar panel discussion presented by Laura Kubatko, The Ohio State University; Danny Kaplan, Macalester College; and Jeff Knisley, East Tennessee State University, and hosted by Jackie Miller, The Ohio State University. National reports such as Bio2010 have called for drastic improvements in the quantitative education that biology students receive. The three panelists are involved in three differently structured integrative programs aimed to give biology students the statistics that are useful in learning and doing biology. The three programs have some surprising things in common for teaching introductory statistics. All three involve connecting calculus and statistics. All three reach beyond the mathematical topics usually encountered in intro statistics in important ways. All three aim to keep the mathematics and statistics strongly connected to biology. The panelists describe their different approaches to teaching statistics for biology and discuss how and why an integrated approach gives advantages. Important issues are how to tie statistics advantageously with calculus, how to keep "advanced" mathematical and statistical topics accessible to introductory-level biology students, and how to employ computation productively. The discussion contrasts a comprehensive "team" approach (at ETSU) with stand-alone courses (at Macalester and at OSU) and refers to the institutional opportunities and constraints that have shaped the programs at their different institutions.

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  • The idea that the examination of a relatively small number of randomly selected individuals can furnish dependable information about the characteristics of a vast unseen universe is an idea so powerful that only familiarity makes it cease to be exciting Is a quote from American Educational Statistician Helen Mary Walker (1891 - 1983). Helen Walker was the first women to serve as the president of the American Statistical Association and this quote is from her December 27, 1944 presidential address at the 104th annual meeting of the ASA in Washington, D.C. The full address may be found in the "Journal of the American Statistical Association" (1945; vol. 40, #229 p. 1-10).

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  • A cartoon to teach the idea that sampling variability depends on the size of the sample, and not on the size of the population (as long as the sample is a small part of the population). Cartoon drawn by British cartoonist John Landers based on an idea from Dennis Pearl. Free to use in the classroom and for course websites.

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