Resource Library

Averages don't always reveal the most telling realities. You know, Shaquille O'Neal and I have an average height of 6 feet. is a quote from American political economist and former Secretary of Labor, Robert B. Reich (1946 - ). The quote was first published on October 6, 1994 in the Business section of "The Chicago Tribune". Robert Reich is 4 foot 10 inches tall. (Picture of Robert Reich is by Michael Collopy)

Data is the sword of the 21st century, those who wield it well, the Samurai. is a quote from American businessman Jonathan Rosenberg, the Senior Vice President of Product Management at Google Inc. The quote appeared in "The Official Google Blog" on February 16, 2009

Conducting data analysis is like drinking a fine wine. It is important to swirl and sniff the wine, to unpack the complex bouquet and to appreciate the experience. Gulping the wine doesn't work. is a quote by British quantitative cognitive psychologist Daniel B. Wright. The quote is found in his 2003 article "Making friends with your data: Improving how statistics are conducted and reported" in the "British Journal of Educational Psychology", volume 73 page 123-136.

An animated video for use in a biostatistics or consulting class to spark a discussion about collaborative research. The animation was created using the free software available at www.xtranormal.com and distributed here with permission for non-profit use by statistics teachers in their classes or course websites. The script for the animation was written August 4, 2010 by xtranormal user "JosiesJavaMoma". Requests for commercial use should be directed to xtranormal.com

This is short clip from a longer documentary shown on BBC. The BBC documentary takes viewers on a rollercoaster ride through the wonderful world of statistics to explore the remarkable power thay have to change our understanding of the world, presented by superstar boffin Professor Hans Rosling, whose eye-opening, mind-expanding and funny online lectures have made him an international internet legend. Rosling is a man who revels in the glorious nerdiness of statistics, and here he entertainingly explores their history, how they work mathematically and how they can be used in today's computer age to see the world as it really is, not just as we imagine it to be. Rosling's lectures use huge quantities of public data to reveal the story of the world's past, present and future development. Now he tells the story of the world in 200 countries over 200 years using 120,000 numbers - in just four minutes.

December 14, 2010 T&L webinar presented by Dianna Spence & Brad Bailey (North Georgia College & State University) and hosted by Jackie Miller (The Ohio State University). When instructors have their students implement "real-world" projects in statistics, a number of questions arise: Where can students locate real data to analyze? What kinds of meaningful research questions can we help students to formulate? What aspects of statistical research can be covered in a project? What are reasonable methods for evaluating the student's work? The presenters will share resources developed during an NSF-funded study to develop and test curriculum materials for student projects in statistics, using linear regression and t-test scenarios.

November 9, 2010 T&L webinar presented by Jiyoon Park and Audbjorg Bjornsdottir (University of Minnesota) and hosted by Jackie Miller (The Ohio State University). This webinar presents the development of a new instrument designed to assess the practices and beliefs of teachers of introductory statistics courses. The Statistics Teaching Inventory (STI) was developed to be used as a national survey to assess changes in teaching over time as well as for use in evaluating professional development activities. We will describe the instrument and the validation process, and invite comments and suggestions about its content and potential use in research and evaluation studies.

October 12, 2010 T&L webinar presented by George Cobb(Mount Holyoke College) and hosted by Leigh Slauson (Capital University). What's the best way to introduce students of mathematics to statistics? Tradition offers two main choices: a variant of the standard "Stat 101" course, or some version of the two-semester sequence in probability and mathematical statistics. I hope to convince participants to think seriously about a third option: the theory and applications of linear models as a first statistics course for sophomore math majors. Rather than subject you to a half-hour polemic, however, I plan to talk concretely about multiple regression models and methodological challenges that arise in connection with AAUP data relating faculty salaries to the percentage of women faculty, and to present also a short geometric proof of the Gauss-Markov Theorem.

September 14, 2010 T&L webinar presented by Thomas Moore(Grinnell College) and hosted by Jackie Miller(The Ohio State University). Permutation tests and randomization tests were introduced almost a century ago, well before inexpensive, high-speed computing made them feasible to use. Fisher and Pitman showed the two-sample t-test could approximate the permutation test in a two independent groups experiment. Today many statistics educators are returning to the permutation test as a more intuitive way to teach hypothesis testing. In this presentation, I will show an interesting teaching example about primate behavior that illustrates how simple permutation tests are to use, even with a messier data set that admits of no obvious and easy-to-compute approximation.

August 10, 2010 T&L webinar presented by Diane Fisher (University of Louisiana at Lafayette), Jennifer Kaplan (Michigan State University), and Neal Rogness (Grand Valley State University) and hosted by Jackie Miller(The Ohio State University). Our research shows that half of the students entering a statistics course use the word random colloquially to mean, "haphazard" or "out of the ordinary." Another large subset of students define random as, "selecting without prior knowledge or criteria." At the end of the semester, only 8% of students we studied gave a correct statistical definition for the word random and most students still define random as, "selecting without order or reason." In this session we will present a classroom approach to help students better understand what statisticians mean by random or randomness as well as preliminary results of the affect of this approach.