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Office: |
HH-110 |
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Telephone: |
525-9140 x 23423 (24-hour Voice Mail) |
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e-mail: |
By appointment.
Don't hesitate to contact me by telephone, voice mail, or e-mail any time you need help. If you need to see me at any time and my office door is open, I will see you then if I can, or arrange a time to meet later.
The class will meet Tuesday 11:30-12:20 and Thursday 11:30-13:30 in CNH-216.
Statistical computing, statistical software packages, working with large data sets, exploratory data analysis, graphical methods, statistical consulting practice.
Learn statistical software packages, beginning with S-Plus, R and SAS, and continuing with any other systems the students wish to work with.
Learn exploratory data analysis, learn how to approach a large and complex data set.
Develop analytical skills using a broad range of statistical methods. Integrate and apply the techniques of statistical analysis learned in other courses. Improve understanding of linear models, generalized linear models and non-linear models and explore advanced multivariate methods.
Get some experience in consulting skills, and consultant-client interaction.
Learn how to document your work and write a report.
Statistical computing, statistical software packages, working with large data sets, exploratory data analysis, graphical methods, statistical consulting practice, linear and non-linear models, report writing.
We will work with the data sets chosen for the Case Studies Session at the Statistical Society of Canada 2007 Annual Meeting to be held at the Memorial University of Newfoundland, June 10-13, 2007. We hope that this year, as in past years, Statistics 4P03/6P03 students will be able to attend the meeting and present their results in the Case Studies Session. The Case Studies will be available from the Statistical Society of Canada web site by the end of January. Past Case Studies have been archived on that site.
- 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
There will be three assignments.
Students may install a licensed copy of Splus on their own computers. Students may download and install R on their own computers. SAS is available on the Department server redpine. SAS, MINITAB, SPSS, Excel, Splus, and R are available in the BSB Student Technology Centre.
There will be no written tests or final examination.
The assignments will be worth a total of 80 marks. All will be judged on content, creativity, validity and accuracy. At least one assignment will also be judged on the quality of writing (25% of the total marks for the assignment).
Students may work in groups of two or three and submit assignments jointly, in which case each student will receive the same mark on the assignment.
The remaining 20 marks will be awarded for class participation; a student who attends all classes and contributes regularly to class discussion will receive full marks.
I will review all "borderline" marks and possibly make further adjustments.
Graduate students taking Statistics 6P03 for graduate credit must give a 30-minute class presentation and submit a written report on one of the Case Studies. The presentation should be of a standard appropriate for a scientific meeting.
This additional work will count for 10% of the graduate student's final mark. The mark computed from assignments, tests and examinations by the grading scheme shown above will count for 90%.
Academic dishonesty consists of misrepresentation by deception or by other fraudulent means and can result in serious consequences, e.g. the grade of zero on an assignment, loss of credit with a notation on the transcript (notation reads: "Grade of F assigned for academic dishonesty"), and/or suspension or expulsion from the university. It is your responsibility to understand what constitutes academic dishonesty. For information on the various kinds of academic dishonesty please refer to the Academic Integrity Policy, specifically Appendix 3.