Probability: Difference between revisions
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A probability study group was proposed on the noisebridge-discuss list and cc'ed to the [[Machine Learning]] mailing list. | A probability study group was proposed on the noisebridge-discuss list and cc'ed to the [[Machine Learning]] mailing list. | ||
The goal is to go through the | The goal is to go through the stuff covered in the 7 chapters of [http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041-probabilistic-systems-analysis-and-applied-probability-spring-2006/related-resources/ Fundamentals of Applied Probability Theory]. We were originally using that book, but decided to switch to the Bertsekas and Tsitsiklis book (see [https://www.noisebridge.net/wiki/Probability#Resources resources]) which covers the same topics and to the problems/solutions available online for [http://ocw.num.edu.mn/OcwWeb/Electrical-Engineering-and-Computer-Science/6-041Spring-2006/Assignments/index.htm MIT OCW Course 6.041]. | ||
Approximate meeting format: | |||
* 30 min - a volunteer presents the material in the chapter | * 30-45 min - a volunteer presents the material in the chapter | ||
* 30-45 min - | * 30-45 min - people discuss, solve problems, go over solutions | ||
=== Resources === | === Resources === | ||
Revision as of 23:43, 23 November 2010
Mailing List
http://groups.google.com/group/noisebridge-probability
Next Meeting
- Quick review of 1st half of ch 2 (discrete random variables). 1 example problem. Finish presentation of chapter 2 (continuous random variables). Another example problem. (will post the example problems over the weekend so people can try them).
- When: Tuesday (11/30) 7:30 to 8:45pm
- Where: Noisebridge (2169 Mission St.) - back corner classroom
List of Problems
List of Problems (on Google Docs) - anyone who has this link can edit/add problems.
These are problems that 1 or more people thought were interesting enough to try solving.
Each problem should include:
- the problem (or pointer to the problem)
- names of people who've worked through the problem
- (optional) what concepts are required for the solution (eg. conditional independence, continuous random variables, etc.)
General
A probability study group was proposed on the noisebridge-discuss list and cc'ed to the Machine Learning mailing list.
The goal is to go through the stuff covered in the 7 chapters of Fundamentals of Applied Probability Theory. We were originally using that book, but decided to switch to the Bertsekas and Tsitsiklis book (see resources) which covers the same topics and to the problems/solutions available online for MIT OCW Course 6.041.
Approximate meeting format:
- 30-45 min - a volunteer presents the material in the chapter
- 30-45 min - people discuss, solve problems, go over solutions
Resources
- MIT OCW - 6.041 / 6.431 Probabilistic Systems Analysis and Applied Probability - the text book(s) we're using are from this course.
- Fundamentals of Applied Probability Theory by Al Drake (pdf) - written in 1967 and used for several decades to teach the above course. From the preface: "This is a first textbook in applied probability theory, assuming a background of one year of calculus."
- Introduction to Probability by Bertsekas and Tsitsiklis - this is the book written and used by the current professors - it appears to be identical in terms of the layout and the topics covered.
- Fifty Challenging Problems by Frederick Mosteller (~ 15 of the problems are viewable in amazon's preview). Monte-carlo simulations of these: Josh Myer's blog
Past Meetings
- 11/23/2010 - did some problems covering chapter 1 (slides)
- 11/16/2010 - chapter 2. Recommended problems 2.04, 2.07, 2.11, 2.17, 2.26, 2.27, 2.28, 2.30 (slides)
- 11/09/2010 - chapter 1. Recommended problems 1.03, 1.08, 1.09, 1.12, 1.13, 1.21, 1.24, 1.30 (slides)
Statistical Computing
Teaching Volunteers
- Kai
- Mike S
- Ben W
- Sara N
Misc
Conditional Risk (from http://xkcd.com/795/ )
