Lecturenotes4

Lecturenotes4 - STAT 430/510 Lecture 4 STAT 430/510...

Info iconThis preview shows pages 1–5. Sign up to view the full content.

View Full Document Right Arrow Icon
STAT 430/510 Lecture 4 STAT 430/510 Probability Hui Nie Lecture 4 June 1st, 2009
Background image of page 1

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

View Full DocumentRight Arrow Icon
STAT 430/510 Lecture 4 Review Properties of Probability P ( E c ) = 1 - P ( E ) If E F , then P ( E ) P ( F ) P ( E S F ) = P ( E ) + P ( F ) - P ( EF )
Background image of page 2
STAT 430/510 Lecture 4 Inclusion-exclusion Identity Inclusion-exclusion Identity P ( E 1 [ E 2 [ ··· [ E n ) = n X i = 1 P ( E i ) - X i 1 < i 2 P ( E i 1 E i 2 ) + ··· + ( - 1 ) r + 1 X i 1 < i 2 < ··· < i r P ( E i 1 E i 2 ··· E i r ) + ··· + ( - 1 ) n + 1 P ( E i 1 E i 2 ··· E i n )
Background image of page 3

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

View Full DocumentRight Arrow Icon
Example A diagnostic test for the AIDS virus has probability of 0.005 of producing a false positive. If the 140 employees of a medical clinic are tested and all are free of AIDS, what is the probability that at least one false positive will occur? It is reasonable to assume that the test results for different individuals are independent. The probability of a negative=1-0.005=0.995
Background image of page 4
Image of page 5
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 06/28/2009 for the course STAT 430 taught by Professor Krieger during the Summer '08 term at UPenn.

Page1 / 14

Lecturenotes4 - STAT 430/510 Lecture 4 STAT 430/510...

This preview shows document pages 1 - 5. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online