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Statistics 4C03/6C03 is offered by the Department of Mathematics & Statistics at McMaster University.
Any questions, comments or suggestions? Send an e-mail to me at pdmmac@mcmaster.ca.
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There will be no class on January 9 or 11.
I will be in Washinton, DC all next week on a Scientific Advisory Panel for the US EPA on Worker Exposure Assessment Methods. |
Statistical computing, statistical software packages; working with large data sets; exploratory data analysis; graphical methods; statistical consulting practice.
Tuesday 11:30-12:20, Thursday 11:30-13:20 in CNH-216
By appointment.
- Chatfield, C. (1988) Problem Solving: A Statistician's Guide, Chapman & Hall.
This book is more suited to self-study than lecturing, but we will be discussing assigned readings. There are good examples showing how to begin analyzing different kinds of data sets. There is good advice on report preparation.
You may find the optional texts useful.
- Cabrera, J. & McDougall, A. (2004) Statistical Consulting, Springer
- Lange, N. et al. (1994) Case Studies in Biometry, Wiley
- Venables, W.N. & Ripley, B.D. (2003) Modern Applied Statistics with S, Springer
All assignments must be submitted no later than noon on Friday April 27, 2007, the final day of the undergraduate examination period. Assignments submitted earlier may be revised and re-submitted for a higher grade.
Consider membership in herd 1 as a binary Y-variable. Split the data into training and validation samples, keeping the numbers from each herd equal in both samples. Fit tree and logistic regression models. Consider the complexity of the models, making sure you are not over-fitting. Give ANOVA tables, Hosmer-Lemeshow tests, box plots, ROC curves and other graphical summaries. Do your work in Splus or R, and in SAS Enterprise Miner. Write a report explaining your results.