MAA Ancillary Workshops

For updated locations, click here; All locations are subject to change

Teaching Introductory Data Analysis through Modeling, presented by Daniel Kaplan, Macalester College, Sunday, January 4, 2009, 8:30 a.m. to 5:00 p.m. This hands-on workshop intended for teachers of introductory statistics in colleges and universities will present a new way of teaching introductory data analysis that gives a central role to modeling techniques. Modeling provides a strong unifying framework for statistics and at the same time ties statistics closely to the scientific method and the demands of realistic multi-variable data. The workshop will introduce the ways in which models can be used for description, the interpretation of models in terms of association, change, and partial change (that is, change in one variable while holding others constant). In place of the usual matrix-based theory of linear models, the workshop will present a geometrical approach to theory that is accessible to introductory students and fully illuminates important ideas in data analysis: fitting, confounding and Simpson's paradox, correlation and collinearity. Inference is introduced using resampling and simulation, from which it is straightforward to transition to a general framework for inference, analysis of covariance. Computation (using the free package R) will feature prominently in hands-on activities; participants should bring laptop computers if possible. Participants do not need to have previous experience with R or with statistical modeling. Our students can learn it and so can you!

There is no registration fee for this workshop. Note that it will be held the day before the Joint Mathematics Meetings actually begin in the Marriott Wardman Park Hotel. Workshop materials and lunch during the workshop will be provided. Workshop participants are encouraged to bring their own laptops. Workshop participants are responsible for their own transportation and lodging. Be sure to register for the JMM and book your hotel rooms early. Enrollment is limited to 40. For registration and additional details go to