MIT6_042JS10_lec34

# MIT6_042JS10_lec34 - 1 Albert R Meyer, April 30, 2010 lec...

This preview shows pages 1–3. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: 1 Albert R Meyer, April 30, 2010 lec 12F.1 Conditional Probability &amp; Independence Mathematics for Computer Science MIT 6.042J/18.062J lec 12F.1 Albert R Meyer, April 30, 2010 A lec 12F.2 S B 1 B 3 B 2 Law of Total Probability B 2 ! A B 3 ! A B 1 ! A lec 12F.2 Albert R Meyer, April 30, 2010 lec 12F.3 Law of Total Probability Pr{A} = Pr{B 1 ! A} + Pr{B 2 ! A} + Pr{B 3 ! A} A = (B 1 ! A) (B 2 ! A) (B 3 ! A) lec 12F.3 Albert R Meyer, April 30, 2010 lec 12F.4 Conditional Probability: A Fair Die knowledge changes probabilities: Pr{roll 1 knowing rolled odd} lec 12F.4 Albert R Meyer, April 30, 2010 lec 12F.5 Conditional Probability Pr{A|B} is the probability of event A , given that event B has occurre d: lec 12F.5 Albert R Meyer, April 30, 2010 lec 12F.8 {1,2,3,4,5,6} {1,3,5} {2,4,6} Yes No 1/2 1/2 2/3 1/3 {1} {3,5} Yes No No {2,4,6} 1 Pr{one | odd)} = Pr: 1/6 1/3 1/2 Conditional Probability: A Fair Die Pr{not one | odd} = Pr{not one | even} = Rolled 1 Rolled odd lec 12F.8 2 Albert R Meyer, April 30, 2010 lec 12F.9 Product Rule lec 12F.9 Albert R Meyer, April 30, 2010 lec 12F.10 Law of Total Probability...
View Full Document

## This note was uploaded on 05/27/2011 for the course CS 6.042J taught by Professor Prof.albertr.meyer during the Spring '11 term at MIT.

### Page1 / 5

MIT6_042JS10_lec34 - 1 Albert R Meyer, April 30, 2010 lec...

This preview shows document pages 1 - 3. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online