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Unformatted text preview: Statistics 528 - Lecture 17 1 Statistics 528 - Lecture 17 Prof. Kate Calder 1 Rules for Means of Random Variables Rule 1 If X is a random variable and a and b are fixed numbers, then & a+bx = a+b & X Rule 2 If X and Y are random variables, then & X+Y = & X + & y Statistics 528 - Lecture 17 Prof. Kate Calder 2 Variance of a Discrete Random Variable Suppose that X is a discrete random variable whose distribution is Value of X x 1 x 2 x 3 x k Probability p 1 p 2 p 3 p k and that & X is the mean of X. The variance of X is 2 X = (x 1- & X ) 2 p 1 + (x 2- & X ) 2 p 2 + +(x- & X ) 2 p k (x i- & X ) 2 p i The standard deviation of X is the square root of the variance. Statistics 528 - Lecture 17 2 Statistics 528 - Lecture 17 Prof. Kate Calder 3 Example: Free-Throw (Lecture 16) What is the standard deviation of shots made by a 58% shooter who shoots three shots?...
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This note was uploaded on 07/26/2011 for the course STA 528 taught by Professor Calder during the Winter '09 term at Ohio State.
- Winter '09