Michelle Everson, University of Minnesota
Tuesday, August 25, 2009 - 2:30pm
In a classroom setting, students can engage in hands-on activities in order to better understand certain concepts and ideas. Replicating hands-on activities in an online environment, however, can be a challenge for instructors. The purpose of this webinar is to present an applet that was created to replicate a "Post-it Note" activity we commonly use in classroom sections of an undergraduate introductory statistics course. The Post-it Note activity is meant to help students develop a more conceptual understanding of the mean and the median by moving a set of Post-it Notes along a number line. During the webinar, participants will have an opportunity to see and experience just how online students are able to interact with what we have named the "Sticky Centers" applet, and we will present the kinds of materials and assignments we have created to use in conjunction with this applet. The webinar will end with a preview a newer applet we are working on in order to replicate the famous "Gummy Bears in Space" activity (presented in Schaeffer, Gnanadesikan, Watkins & Witmer, 1996).
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.
Jo Hardin, Pomona College
Tuesday, July 28, 2009 - 2:30pm
Based on an activity by John Spurrier, we use 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. We also compare our different Bayesian estimators and different frequentist estimators using bias, variability, and mean squared error. We can see the effect that sample size and dispersion of the prior distribution have on the estimator.
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.
Leigh Slauson, Otterbein College
Tuesday, June 23, 2009 - 2:30pm
This webinar will describe 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 will include 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.
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.
Dennis Pearl, The Ohio State University
Tuesday, May 26, 2009 - 2:30pm
This webinar will describe 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:
how it helps to eliminate bias when compared with a haphazard assignment process,
how it leads to a consistent pattern of results when repeated, and
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 will be demonstrated along with a discussion of goals, context, background materials, class handouts, and assessments.
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.
Herbert Lee, University of California - Santa Cruz
Tuesday, April 28, 2009 - 2:30pm
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. Topics from variability and exploratory data analysis to hypothesis testing and Bayesian statistics can be illuminated with cookies.
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)