Lecture10_updated

Lecture10_updated - A = set of possible values for the...

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Lecture 10 25 th  May 2011
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Discrete Random Variables and  Probability Models Random Variables and Probability  Functions: Probability models are used to describe  outcomes associated with random  processes. (Flipping a coin, rolling a die e.t.c ) So far we have used sets in sample  spaces to describe such outcomes. 
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Now we introduce numerical-valued  variables X, Y, … to describe outcomes. These numerical-valued variables are  called Random Variables (r.v.)   Every r.v. is associated with a range, 
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Unformatted text preview: A = set of possible values for the variable. • Definition: A Random Variable is a function that assigns a real number to each point in a sample space S • Random Variables are denoted by capital letters: X, Y, … • And the possible values/ outcomes are denoted by: x, y, … X Discrete Continuous R.V. R.V. Range consists of Range consists of a finite set of values. an infinite set of values. • Examples Discrete r.vs Continuous r.vs...
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This note was uploaded on 07/26/2011 for the course STAT 230 taught by Professor Various during the Spring '06 term at Waterloo.

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Lecture10_updated - A = set of possible values for the...

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