Probability

From Noisebridge
Revision as of 00:58, 1 December 2010 by Weisburd (Talk | contribs)

Jump to: navigation, search

Contents

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 posted under 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

Past Meetings

  • 11/30/2010 - discrete random variables - chapter 2 of Bertsekas & Tsitsiklis (random variables 2.ppt slides).
  • 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

R

Teaching Volunteers

  • Kai
  • Mike S
  • Ben W
  • Sara N

Misc

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


Conditional risk.png

Personal tools