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Office: |
HH-210 |
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Telephone: |
905 525-9140 x 23423 (24-hour Voice Mail) |
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e-mail: |
Tuesday 10:30 & 13:30, Wednesday 10:30 & 13:30, Friday 10:30.
Please come at the start of the hour. Other times 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.
Learn how to apply statistical methods and the principles of experimental design to problems of practical interest. Learn enough about the underlying theory that you can appreciate when a given method may or may not be applicable.
Learn how to use the R environment for statistical analysis. Learn how to display data graphically and organize your results into reports.
Become skilled at the analysis of simple linear regression and one-factor and two-factor designs.
Lay the foundations for learning more advanced statistical theory and methods after you complete this course.
Devore, J.L. (2004) Probability and Statistics for Engineering and the Sciences, Sixth Edition, Brooks/Cole.
This book will be useful as a statistics and experimental design handbook in later courses and after you graduate. The Fifth Edition is also acceptable.
Dalgaard, P. (2002) Introductory Statistics with R, Springer.
Optional text.
After studying descriptive statistics and graphical methods for data exploration (Chapter 1) and reviewing STATS 2D03 material in Chapters 2-5, we will cover all the material on estimation and testing in Chapters 6-14, plus selected topics from Chapters 13-14. We will discuss the theoretical results on which these statistical methods are based and develop an understanding of the logic of statistical inference.
The most important topics will be covered in the final weeks: the design and analysis of single-factor (Chapter 10) and some multi-factor (Chapter 11) experiments, and simple linear regression with a lack-of-fit test (Chapters 12-13).
Copies of the lecture notes may be borrowed from the Instructor.
Check the course web site at http://www.math.mcmaster.ca/peter/s3mb3/s2mb3_0405 regularly for announcements, assignments, course notes, and answers to frequently-asked questions.
Students are expected to use computers in this course. Students will learn how to do statistical analysis in the R environment.
It is each student's responsibility to keep up to date with the course by working ahead in the text. Each chapter of the text has worked examples and lots of problems. I will give you some exercises to work on but not hand in, and I will provide solutions to these exercises.
Three assignments will be handed in for grading.
Test #1
2005-02-03 (Thursday)
19:00-21:00
BSB-244 Computer Lab*
Test #2
2005-03-03 (Thursday)
18:45-19:45
MDCL-1105
Test #3
2005-03-23 (Wednesday)
18:45-19:45
T29-101
Aids permitted: Any calculators, any mathematical or statistical tables, one sheet of notes (8.5" x 11", one side only).
*You must have a valid userid, password and laser printing account for the BSB computer lab when you write Test #1. Tests MUST be submitted on paper; electronic submission is NOT permitted.
If you are unable to write a test at the scheduled time, please e-mail me at least 3 days before to make special arrangements.
There will be a formal 3-hour examination scheduled by the Registrar in December.
Aids permitted: Any calculators; one sheet of notes (8.5" x 11", both sides); any mathematical or statistical tables. A photocopy of Tables A.3-A.11 from the course text is recommended.
All assignments will be counted, weighted in proportion to total marks. All tests will be counted, weighted equally. The best of the following four calculations will be used:
(A) 100% Exam; (B) 80% Exam + 20% Assignments; (C) 80% Exam + 20% Tests; (D) 60% Exam + 20% Assignments + 20% Tests.I will review all "borderline" marks and possibly make further adjustments.
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.