Ways to incorporate innovative practices in an applied regression analysis course

Halvorsen, K. T., McKenzie Jr., J. D., & Sullivan, M. M.
Joint Mathematics Meetings, New Orleans, LA, 13 January 2001

The authors prepared a paper that described an example of a second course in applied regression analysis as part of the ASA Undergraduate Statistics Education Initiative (USEI) Symposium. They recommended that such a course include many practices that are not commonly integrated in a typical applied statistics course. Here the authors will give examples of such practices that they have used successfully (and can be effectively used in any introductory applied statistics course). Because data analysis must be the central theme of the course, examples of how the instructor and students can obtain interesting, real-world data will be given. These include novel activities to collect data in class, as well as web and text resources for data. The USEI paper strongly recommended that students should experience the entire data collection and analysis process. The USEI paper emphasized that active learning must be included in any such course. Activities that promote active learning such as the use of short talks to introduce concepts followed by class discussion and student presentations of examples will be given. Appropriate technology is an indispensable part of such a course. At a minimum this means that the course has suitable computational and conceptual software.

The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education