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  CSE 312Wi '11:  Approximate Schedule
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Schedule details will evolve as we go; check back periodically to see the latest updates.

    Due Lecture Topic Reading
Week 1
M   Introduction                                                   Unless otherwise noted, all section of Ross marked "*" or "optional" may be omitted.
W   Counting: combinations, permutations, etc. Ross, Ch 1 (exclude 1.6)
F   Axioms of Probability Ross, Ch 2 (exclude 2.6)
Week 2
W   Conditional Probability & Independence Ross, Ch 3; (exclude the "stared" portion of 3.4 starting at the bottom of p86, except for "Gambler's Ruin," example 4l)
Week 3
M Holiday
W   Conditional Probability & Independence
F   Random Variables Ross, Ch 4; exclude 4.7 example 7d and all of 4.8 except 4.8.1 and 4.8.3
Week 4
F   Ross, Ch 5; exclude 5.5.1 and 5.6
Week 5
W   Random Variables/Midterm Review
F   Midterm  
Week 6
M   Analysis of Algorithms; Tails and Limit Theorems Ross, Ch 6: pp 250-251 (two "Remarks" & Ex 2j); pp 256-258 (Prop 3.2 & Ex 3c; omit proof of prop);
Ross, Ch 7: pp 300-301 (Ex 2c, 2e); pp 306-308 (Ex 2m, a different analysis than in lecture); pp 354-355 (omit Ex 7a, 7b). (FYI, pp 358-359 tables are useful summaries; omit the MGFs, the neg.-bin. & gamma distributions. See also here.)
Ross, Ch 8. Omit: proofs of Central Limit Theorem, Strong Law of Large Numbers, 8.5, 8.6.
Week 7
M   Max Likelihood Estimators, EM, Hypothesis Testing Weisstein, E.W. "Maximum Likelihood." From MathWorld--A Wolfram Web Resource, Wikipedia Likelihood-ratio test ("Background" and "Simple-versus-simple hypotheses"), Wikipedia Likelihood Function (through 2.1).
Week 8
M Holiday
W   Polynomial Time and NP-Completeness DPV: Preface, Chapter 0, 1.1, 2.1, (optional: 2.2), 2.3-2.5, 6.1-6.4, 6.6, Chapter 8.
Week 9
Week 10
F   Wrap up & Review
Week 11

Final Exam
2:30-4:20 Monday, Mar. 14, 2011



A First Course in Probability (8th edition), Sheldon M. Ross, Prentice Hall, 2009. (Available from U Book Store, Amazon, etc.)

Online. The last few weeks of the quarter will use the following, available free online:

Algorithms, by S. Dasgupta, C.H. Papadimitriou, and U.V. Vazirani

Reference. (No direct use of this, but if you already own a copy, keep it for reference. Some students have said they like its coverage of counting (Chapter 5 and 7.5, 7.6) and discrete probability (Chapter 6)):

Discrete Mathematics and Its Applications, (sixth edition) by Kenneth Rosen, McGraw-Hill, 2006. Errata. (Available from U Book Store, Amazon, etc.)

Supplementary Reading:

In addition to the assigned text, there are many supplementary resources available on the web and elsewhere that may be helpful. Here are a few. I welcome hearing about others that you discover.

  1. Rosen (above) covers counting (Chapter 5 and 7.5, 7.6) and discrete probability (Chapter 6).
  2. The "Chance Project".
  3. Introduction to Probability by Charles Grinstead and Laurie Snell
    The open access textbook for the Chance project. Roughly comparable in coverage to Ross, but with a different slant, of course.
  4. Wikipedia covers many of the same topics. Unfortunately, its coverage is often uneven and/or too advanced, but parts may be useful.
  5. Wolfram's MathWorld, (by E.W. Weisstein), also covers much of this ground, but again not always at the right level for beginners.
  6. Wikibooks: Probability
  7. Wikibooks: Statisitcs
  8. Wikiversity: Statistics
  9. Statistics Online Computational Resource
  10. Dinov, Ivo D. (2008). Expectation Maximization and Mixture Modeling Tutorial. UC Los Angeles: Statistics Online Computational Resource. Retrieved from:
  11. Your CSE 332 text contains brief sections on NP and NP-completeness, dynamic programming, and perhaps some of the other algorithmic topics we've covered in the last 3 weeks.

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