STAT 213 Lecture 23: lec_23

• School: University of Calgary
• Department: Statistics
• Course: STAT 213
• Professor: Anatoliy Swishchuk

Document Summary

We write the variance of a random variable x as 2. The variance is an average of the squared deviation (x x)2 of the variable x from its mean x. This is similar to the di nition of the sample variance s2 given in chapter 1. Below is the de nition of the variance for discrete random variable. Suppose that x is a discrete random variable whose distribution is: Value of x : x1, x2, , xn; X = (x1 x)2p1 + (x2 x)2p2 + + (xk x)2pk =! (xi x)2pi. The standard deviation x of x is the square root of the variance: Let us nd the mean and variance of x by arranging the calculation in the form of a table. X are sums of columns in this table. If x is a random variable and a and b are xed numbers, then. If x and y are independent random variables, then a+bx = b2 2.