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Webinars

  • Sneaking in a few history lessons when teaching statistics

    Kirk Anderson, Grand Valley State University
    Tuesday, August 11, 2009 - 2:00pm
    Many of us, while teaching an introductory statistics course, have mentioned some of the history behind the methodology, perhaps just in passing. We might remark that an English chap by the name of R. A. Fisher is responsible for a great deal of the course content. We could further point out that the statistical techniques used in research today were developed within the last century, for the most part. At most, we might reveal the identity of the mysterious "Student" when introducing the t-test to our class. I propose that we do more of this. This webinar will highlight some opportunities to give brief history lessons while teaching an introductory statistics course.
  • Engaging Students with Disabilities through Universal Design for Learning

    Margo Vreeburg Izzo, The Ohio State University Nisonger Center
    Tuesday, July 14, 2009 - 2:00pm
    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.
  • Teaching Bayesian Inference in Undergraduate Service Courses

    Dalene Stangl, Duke University
    Tuesday, June 9, 2009 - 2:00pm
    This webinar will present the core materials I use 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.
  • Models for Integrating Statistics in Biology Education: A Panel Discussion

    Laura Kubatko, The Ohio State University; Danny Kaplan, Macalester College; and Jeff Knisley, East Tennessee State University
    Tuesday, May 12, 2009 - 2:00pm
    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 will 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 will contrast a comprehensive "team" approach (at ETSU) with stand-alone courses (at Macalester and at OSU) and will refer to the institutional opportunities and constraints that have shaped the programs at their different institutions.
  • Concepts of Statistical Inference: A Randomization-Based Curriculum

    Allan Rossman & Beth Chance, Cal Poly - San Luis Obispo; and John Holcomb, Cleveland State University
    Tuesday, April 14, 2009 - 2:00pm
    We present ideas and activities for helping students to learn fundamental concepts of statistical inference with a randomization-based curriculum rather than normal-based inference. We propose 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 we present arguments in favor of such a curriculum, demonstrate some activities through which students can investigate these concepts, highlight some difficulties with implementing this approach, and discuss ideas for assessing student understanding of inference concepts and randomization procedures. Watch Webinar Recording (FLASH)
  • Promoting active learning in introduction to statistics using personal response systems (clickers)

    Jennifer Kaplan, Michigan State University
    Tuesday, March 10, 2009 - 2:00pm
    Central to the recommendations for teaching introductory statistics made by the GAISE committee were the following: foster active learning in the classroom, use assessment to improve and evaluate student learning, and use real data (GAISE, 2006). This session will illustrate how personal response systems (clickers) can be used to address the realization of these three recommendations in large lecture classes (over 70 students). The session will discuss general issues of the implementation of clickers and then provide an example of each of the following three uses of clickers in the classroom: 1) questions designed to highlight common conceptual misunderstandings in statistics, 2) questions designed as review questions for topics already addressed, and 3) questions that were part of a class activity to help students learn a concept. Watch Webinar Recording (FLASH)
  • Aiming to Improve Students' Statistical Reasoning: An Introduction to the AIMS Materials

    Andrew Zieffler, Bob delMas, and Joan Garfield, University of Minnesota
    Tuesday, February 10, 2009 - 2:00pm
    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). Watch Webinar Recording (FLASH)
  • 9 out of 10 Seniors Recommend This Freshman Seminar: Statistics in the real world

    Jo Hardin, Pomona College
    Tuesday, January 13, 2009 - 2:00pm
    This webinar will discuss 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. Watch Webinar Recording (FLASH)
  • Teaching Ethics in Statistics Class

    John H. Walker, California Polytechnic State University
    Tuesday, December 9, 2008 - 2:00pm
    Ethics play an important role in statistical practice. How can we educate our students about statistical ethics--especially when our courses are already packed with so much...statistics? At the Joint Statistical Meetings in August, I was the discussant in a session on "Teaching Ethics in Statistics Class." First, I will briefly review the points raised by the speakers in that session. George McCabe (Purdue) contrasted the "old" introductory statistics course with its emphasis on methodology to the "new" course. Patricia Humphrey (Georgia Southern) spoke about how she covers ethical data collection in her introductory classes. Paul Velleman (Cornell) talked about the role of judgment in statistical model building and how it makes students (and sometimes us) uncomfortable. I will discuss each of these points in the context of the American Statistical Association's "Ethical Guidelines for Statistical Practice" as well as my own experiences in teaching statistical ethics in an undergraduate capstone course for statistics majors. I will close with an example of statistical ethics in the use of multiple comparison procedures. Watch Webinar Recording (FLASH)
  • Statistics 105 - Real-Life Statistics: Your Chance for Happiness (or Misery)

    Xiao-Li Meng, with Happy Team members: Yves Chretien, Paul Edlefsen, Kari Lock, and Cassandra Wolos; Department of Statistics, Harvard University
    Tuesday, November 18, 2008 - 2:00pm
    Statistics 105 is a team-designed course that has received local media attention (e.g., www.news.harvard.edu/gazette/2008/02.14/11-stats.html). Its course description promises the following: Discover an appreciation of statistical principles and reasoning via "Real-Life Modules" that can make you rich or poor (financial investments), loved or lonely (on-line dating), healthy or ill (clinical trials), satisfied or frustrated (chocolate/wine tasting) and more. Guaranteed to bring happiness (or misery) both to students who have never taken a previous statistics course, and to those who have taken statistics and want to see how statistical thinking applies to so many areas of life. This webinar will reveal its history, pedagogical motivation, innovations, and challenges along the way. Watch Webinar Recording (FLASH)

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