This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: STATISTICS 420 RECITATION  Winter 2008 Jan 10, 2008 TA : Soma Roy ([email protected]) Office Hours : Fridays 9:18 to 11:18 am OR by appointment, MA 422 Chapter 2: Key Ideas • Sample Space: is the set of all possible outcomes of an experiment. • Mutually Exclusive: Two events A and B are mutually exclusive when they have no outcomes in common (or cannot both happen.) • Some Rules of Probability: 1. P ( A ) = 1 P ( A ) . 2. P ( ∅ ) = 0 . 3. If A and B are events in a sample space S and A ⊂ B, then P ( A ) ≤ P ( B ) . 4. 0 ≤ P ( A ) ≤ 1 for any event A . • General Addition Rule: P ( A ∪ B ) = P ( A ) + P ( B ) P ( A ∩ B ) This can be generalized. For example, for 3 events A, B, and C : P ( A ∪ B ∪ C ) = P ( A )+ P ( B )+ P ( C ) P ( A ∩ B ) P ( A ∩ C ) P ( B ∩ C )+ P ( A ∩ B ∩ C ) • Conditional probability: P ( B  A ) is the conditional probability of the event B given the event A has occured. Then, provided P ( A ) 6 = 0, P ( B  A ) = P ( A ∩ B ) P ( A ) • Multiplication Rule: (from the definition of conditional probability)...
View
Full
Document
This note was uploaded on 12/16/2011 for the course CS cs102 taught by Professor Rsharma during the Spring '11 term at IIT Kanpur.
 Spring '11
 rsharma

Click to edit the document details