29h - Discrete Mathematics Integers 29-2 Previous Lecture...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
Introduction Finite Probability (cntd) Discrete Mathematics Andrei Bulatov Discrete Mathematics - Integers 29-2 Previous Lecture Experiment, outcomes, sample space Events Classic probability Likelihood of outcomes Discrete Mathematics – Integers 29-3 More General Probability Sample space: Any set S Event: `Any’ subset of S Probability: A measure, that is a function Pr: P(S) [0,1], such that - Pr( ) = 0 - Pr(S) = 1 - Pr(A) 0 for all A S - for any disjoint A,B S, Pr(A B) = Pr(A) + Pr(B) Discrete Mathematics – Integers 29-4 More General Probability: Crooked Dice Suppose we made a loaded dice S = {1,2,3,4,5,6} Pr(1) = 1/16, Pr(2) = Pr(3) = Pr(4) = Pr(5) = 1/8 Pr(6) = 7/16 Pr({i,j,…,m}) = Pr(i) + Pr(j) + … + Pr(m) Find Pr({1,3,5}) Discrete Mathematics – Integers 29-5 More General Probability: Geometric Probability How to measure the area of an island? Draw a rectangle around the island and drop many random points Then Sample space: Points in the rectangle Events: Measurable sets of points
Background image of page 1

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

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 05/18/2010 for the course MACM MACM 101 taught by Professor Andreibulatov during the Spring '10 term at Simon Fraser.

Page1 / 3

29h - Discrete Mathematics Integers 29-2 Previous Lecture...

This preview shows document pages 1 - 2. Sign up to view the full document.

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