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Spring, 2004
Stat 310: Probability and Statistics
Instructor: David W. Scott 2095 Duncan Hall 713-348- [email protected] http://www.stat.rice.edu/∼scottdw/stat310/
Tuesday/Thursday: 1:00-2:20 BL 131
Office Hours: Mon/Wed 1:30-2: Appt./drop by/email
Grading:
15% homework: pledged, but you may discuss problems with others 28% 1st exam: not closed book take-home, liberal partial credit 29% 2nd exam: not closed book take-home, liberal partial credit 30% final exam: take-home, open book, liberal partial credit
The first exam will be handed out 2/12 (due 2/16). The second exam will be handed out 3/18 (due 3/22). The final exam will be handed out 4/22 (various due dates).
The course divides roughly into thirds: i) classical and modern probability ii) probability distributions and random variables iii) statistical methodologies (estimation and testing)
You are responsible for all lecture material in addition to assigned portions of textbook and handouts. Lecture material will not usually duplicate the text. Homework will be returned within one or two class periods, so late homeworks will not generally be accepted. While there will not be a computer lab, supplementary material will be posted on my web site when announced.
On Monday and Wednesday evenings, beginning at 5:30, there will be a help session with Brooke Lathram in Duncan Hall 1042. The session will end at 6:30 if homework is due the next day, otherwise, the session will end at 6:00.
On examinations, points over 100 are usually counted 1/5 (max 103 or 104). The homework contains an extra 2% (total of percentages is 102%). Thus, you can skip a homework and still receive full credit. The extra 2% is available as full bonus points.
The first few homework assignments will be on-line at the web site given above.
Text: Hogg and Tanis’ Probability and Statistical Inference, Prentice-Hall, 2001, 6th ed.
Order of Material Discussed in Lectures and Reading Assignments
Lecture Topics Read
1 general Chapter 1 (not review) 2 introduction probability, sets 2.1, 2.2, 2. 3 axioms, counting 2. 4 conditional prob, Bayes theorem, independence 2. 5 reliability, discrete random variables, Binomial 3.1, 3. 6 Poisson, continuous r.v.’s, negative exponential 3.5, 4.1, 4. 7 expectation, moment generating functions 4.1, 3.2, 3. 8 normal, chebychev 4.4, 6. 9 decision analysis notes 10 transformations, chi-squared 4.5, 4. 11 joint r.v.’s 5.1, 5.3, 5. 12 independence, correlation 5.1, 5. 13 bivariate c.o.v., box-m¨uller transformation 5. 14 sampling, central limit theorem 6.1, 6.4, 6. 15 sample statistics, regression 6.2,5. 16 other distributions 6.3, 4.3, 6. 17 estimation, approximation 1.1–1.4, 6. 18 likelihood, method of moments 7. 19 minimum distance estimation, histogram theory notes 20 confidence intervals 7.2, 7.3, 7. 21 polls 7.5, 7. 22 regression 7.8, 7. 23 testing 8. 24 testing 8. 25 TBA (includes review of exams) - 26 TBA (visualization research) - 27 TBA -
