This course will provide an overview of the ideas ofregression graphics, which is a collection of methodological tools that are used to discover and understand dependence of a response on predictors primarily through the use of simple graphs in one, two and three dimensions. It will mostly follow the outline of the bookAn Introduction to Regression Graphics, published by Wiley in 1994.Prerequisite for this course is familiarity with standard regression methodology at the level of one of the major textbooks in this area. The course will also introduce the

R-code, which isXlisp-Statcomputer code that accompanies the book and allows the user to use all the methods described in the book and in the course. The program is very easy to use, and requires no knowledge oflisp.

- Introduction illustrating graphical issues.
- Foundations: Structural dimension, sufficient summary plots, linear predictors, first graphical inference
- Finding summary plots and exploring the importance of linear predictors.
- Illustrations, 3D plots, residual plots
- Graphics for regressions with a binary response
- Graphics for model assessment.