lecture17_2slides

lecture17_2slides - Statistics 528 - Lecture 17 1...

Info iconThis preview shows pages 1–3. Sign up to view the full content.

View Full Document Right Arrow Icon

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

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

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?...
View Full Document

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.

Page1 / 5

lecture17_2slides - Statistics 528 - Lecture 17 1...

This preview shows document pages 1 - 3. Sign up to view the full document.

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