Probability: Difference between revisions

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=== Next Meeting ===
* Go through chapter 1 and problems 1.03, 1.08, 1.09, 1.12, 1.13, 1.21, 1.24, 1.30 (recommended by Drake in the preface)
* When: Tuesday (11/9)  7:30 to 8:45pm
* Where: Noisebridge - 2169 Mission St. (back corner classroom)
=== General ===
=== General ===
* When: Tuesdays 7:30 to 8:45pm starting 11/9/2010
* Where: back classroom


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.
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* 30-45 min - discussion and problem solving (those who solved the problems at home can compare answers, those who didn't can work on the problems together)
* 30-45 min - discussion and problem solving (those who solved the problems at home can compare answers, those who didn't can work on the problems together)


=== Next Meeting ===
* Go through chapter 1 and problems 1.03, 1.08, 1.09, 1.12, 1.13, 1.21, 1.24, 1.30 (recommended by Drake in the preface)
* When: Next Week (TBD)
* Where: Noisebridge - 2169 Mission St. (back corner classroom)


=== Resources ===
=== Resources ===

Revision as of 10:27, 6 November 2010

Next Meeting

  • Go through chapter 1 and problems 1.03, 1.08, 1.09, 1.12, 1.13, 1.21, 1.24, 1.30 (recommended by Drake in the preface)
  • When: Tuesday (11/9) 7:30 to 8:45pm
  • Where: Noisebridge - 2169 Mission St. (back corner classroom)

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 7 chapters of Fundamentals of Applied Probability Theory at a pace of 1 chapter per week.

Proposed meeting format (to be discussed at 1st meeting):

  • 30 min - a volunteer presents the material in the chapter (this will be for people who didn't have time to read the chapter at home, and for those who want to teach)
  • 30-45 min - discussion and problem solving (those who solved the problems at home can compare answers, those who didn't can work on the problems together)


Resources

Statistical Computing

R

Teaching Volunteers

  • Kai
  • Mike S
  • Ben W


Misc

Conditional Risk (from http://xkcd.com/795/ )


Conditional risk.png