Resource Library

In this video (which lasts a little over 21 minutes), Oxford mathematician Peter Donnelly reveals the common mistakes humans make in interpreting statistics -- and the devastating impact these errors can have on the outcome of criminal trials.

Ellen Gundlach and Nancy Palaez (both of Purdue University) use Calibrated Peer Review, an online writing and peer evaluation program available from UCLA, to introduce statistical literacy to Nancy's freshman biology students and to bring a real-world context to statistical concepts for Ellen's introductory statistics classes in an NSF-funded project. CPR allows instructors in large classes to give their students frequent writing assignments without a heavy grading burden. Ellen and Nancy have their students read research journal articles on interesting subjects and use guiding questions to evaluate these articles for statistical content, experimental design features, and ethical concerns.

Statistics educators are keenly aware of the value of using real data to help students see the relevance and applicability of statistics. The federal statistical agencies have invested in significant efforts to make data accessible and available. In this webinar, Ron Wasserstein will point you to these resources, discussing their uses and limitations.

Certitude is not the test of certainty. We have been cock-sure of many things that were not so. is a quote of American Supreme Court Justice Oliver Wendell Holmes, Jr. (1841 - 1935). The quote is found in an article written by Justice Holmes in 1918 for the "Harvard Law Review" v. 32, page 40. The quote is also found in the book "Statistically Speaking, a Dictionary of Quotations" by Carl Gaither and Alma Cavazos-Gaither.

June 10, 2008 Teaching and Learning webinar presented by Robert delMas, University of Minnesota and Marsha Lovett, Carnegie Mellon University and hosted by Jackie Miller, The Ohio State University. There is a large body of research on the mechanisms underlying student learning. This webinar explores four principles distilled from this research - the role of prior knowledge, how students organize knowledge, meaningful engagement, and goal-directed practice and feedback - and illustrate their application in the teaching of statistics. A more detailed example is given to show how these principles can be integrated to develop and support our students' conceptual understanding.

August 12, 2008 Teaching and Learning webinar presented by Kathryn Plank, The Ohio State University; and Michele DiPietro, Carnegie Mellon University and hosted by Jackie Miller, The Ohio State University. There are many good reasons to incorporate thinking about diversity into a course, not the least of which is that it can have a real impact on student learning and cognitive development. This webinar explores both how the tools of statistics can help students better understand complex and controversial issues, and, in the other direction, how using these complex and controversial issues can help facilitate deeper learning of statistics.

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.

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.

November 18, 2008 Teaching and Learning webinar presented by Xiao-Li Meng, Harvard University and hosted by Jackie Miller, The Ohio State University. 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 reveals its history, pedagogical motivation, innovations, and challenges along the way

webinar illustrates 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 discusses general issues of the implementation of clickers and then provides 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.