McMASTER UNIVERSITY STATISTICS SEMINAR

Week of November 13 - 17, 2000

SPEAKER:

Dr John Fox
Department of Sociology, McMaster University

TITLE:

"An R and S-Plus Companion to Applied Regression"

DAY:

Wednesday, November 15, 2000

TIME:

3:30 p.m. [Tea & cookies in BSB-202 at 3:00 p.m.]

PLACE:

BSB-108

SUMMARY

The S statistical programming language and computing environment, commercially available as S-Plus, has become a kind of lingua franca of statistical computing, at least among statisticians. The introduction of a nearly complete, free implementation of S - called R - should help to popularize S further, and is particularly attractive for use in teaching.

I'll describe a two-part project, undertaken in collaboration with Georges Monette of York University. One aspect of the project is to write a book introducing S, with a focus on applied regression analysis and closely related topics (such as linear and generalized linear models). The second, related, aspect of the project is to add to the capabilities of R and S-Plus, especially, but not exclusively, in the area of regression diagnostics. Much of the programming work has been completed in R.

ABOUT THE SPEAKER

 

John Fox is Professor of Sociology at McMaster University. He was previously Professor of Sociology and of Mathematics and Statistics at York University in Toronto, where he also directed the Statistical Consulting Service at the Institute for Social Research. Professor Fox earned a Ph.D. in Sociology from the University of Michigan in 1972. He has taught many workshops on statistical topics at such places as the summer program of the Inter-University Consortium for Political and Social Research and the annual meetings of the American Sociological Association. He has a long-standing interest in statistical graphics. John Fox's recent books include Applied Regression Analysis, Linear Models, and Related Methods (Sage, 1997), Nonparametric Simple Regression: Smoothing Scatterplots (Sage, 2000), and Multiple and Generalized Nonparametric Regression (Sage, 2000).

REFERENCES

The references below, suggested by the speaker as useful background for this talk, have been placed on reserve at Thode Library (STATS 770: Statistics Seminar).

[1] Fox, J. (1997). Applied Regression Analysis, Linear Models, and Related Methods. Thousand Oaks, California, Sage Publications, 597 pp.

[2] Paradis, E. (2000). R for Beginners. Available for download in pdf format, 31 pp.

You can try R for yourself - Download R for Windows or UNIX.


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