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  CSE 312,  Au '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
9/26-9/30		 W   Introduction                                                   Berteskas Ch 1
F Counting: combinations, permutations, etc.
Week 2
10/3-10/7		 M HW #1 (Due Th) Axioms of Probability
W Discrete Random Variables Bertsekas Ch 2
F
Week 3
10/10-10/14		 M HW #2 (Due Th)
W
F
Week 4
10/17-10/21		 M HW #3 (Due Th) Continuous Random Variables Bertsekas Ch 3
W
F
Week 5
10/24-10/28		 M HW #4 (Due Th)
W
F Midterm Review  
Week 6
10/31-11/4		 M   Midterm
W Analysis of Algorithms; Tails and Limit Theorems Bertsekas Ch. 5
F
Week 7
11/7-11/11		 M HW #5 (Due Th)
W
F Holiday
Week 8
11/14-11/18		 M HW #6 (Due Th) Analysis of Algorithms; Tails and Limit Theorems
W Max Likelihood Estimators, EM, Hypothesis Testing Bertsekas, 9.1 (excluding "confidence intervals"), 9.3
F
Week 9
11/21-11/25		 M  
W
F Holiday
Week 10
11/28-12/2		 M HW #7 (Due Th) Polynomial Time and NP-Completeness DPV: Preface, Chapter 0,6.1-6.4, Chapter 8.
W
F
Week 11
12/5-12/9		 M HW #8 (Due Th)
W
F Wrap up & Review  
Week 12
12/12-12/16		 M

Final Exam
2:30-4:20 Monday, Dec. 12, 2011

Textbooks:

Required:

Introduction to Probability (2nd edition), Dimitri P. Bertsekas and John N. Tsitsiklis, Athena Scientific, 2008(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. Some previous versions of this course used A First Course in Probability (8th edition), Sheldon M. Ross, Prentice Hall, 2009. (Available from Odegaard reserves QA273 .R83 2010, Amazon, etc.) Ross has many good examples, exercises, reasonable level of math; perhaps a little less good on overview/intuition. See a previous quarter's web page for detailed readings approximately corresponding to this quarter's coverage.
  3. The "Chance Project".
  4. Introduction to Probability by Charles Grinstead and Laurie Snell
    The open access textbook for the Chance project. Roughly comparable in coverage to Ross or Bertsekas, but with a different slant, of course.
  5. Wikipedia covers many of the same topics. Its coverage can be uneven and/or too advanced, but much is useful.
  6. Wolfram's MathWorld, (by E.W. Weisstein), also covers much of this ground, but again not always at the right level for beginners.
  7. Wikibooks: Probability
  8. Wikibooks: Statistics
  9. Wikiversity: Statistics
  10. Statistics Online Computational Resource
  11. Your CSE 332 text contains brief sections on NP and NP-completeness, dynamic programming, and perhaps some of the other algorithmic topics we cover in the last few weeks.
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