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Session 3B. Statistics as a Service Subject in Second Level Courses: Teaching Regression Models

Session Organizer(s)

Joachim Engel (Germany)

Session Abstract

Modeling functional relationships between two or more variables is a central topic of applied statistics. In this session we look at various approaches to teach regression models. This includes univariate non-linear regression as well as high dimensional linear and non-linear regression models, data smoothing and methods of dimension reduction. The focus should be on teaching understanding and concepts of various regression models, not on mathematical details. The technological aspect of using modern software as a tool to promote understanding (e.g. through simulation) is also covered.

Some specific questions:
* How to interpret the resulting curve?
* How to deal with outliers?
* What about diagnostics, variable selection, robust regression methods?
* Which technological tools are suitable and appropriate for teaching curve fitting?


Presentation 3B1 Interpretation of Regression Output: Diagnostics, Graphs and the Bottom Line Wesley O. Johnson (USA)
Presentation 3B2

Understanding Regression
Sudhakar Kunte (Botswana)
Presentation 3B3 Accessible Methodologies for Estimating Density Functions
Serge B Provost (Canada)
Presentation 3B4 Advanced Topics for a First Service Course in Statistics K. L. Weldon (Canada)

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