measuring variance we usually refer to variance as sigma squaredand you'll find out why momentarilybut for nowjust know that variance is the average of the squared differences from the mean to compute the variance of datasetyou first figure out the mean of it let' say have some data that could represent anything let' say maximum number of people that were standing in line for given hour in the first houri observed person standing in linethen then then then the first step in computing the variance is just to find the meanor the averageof that data add them alldivide the sum by the number of data pointsand that comes out to which is the average number of people standing in line ( + + + + )/ now the next step is to find the differences from the mean for each data point know that the mean is so for my first data pointi have so - the next data point is so - - and so on and so forth okso end up with these both positive and negative numbers that represent the variance from the mean for each data point (- - - now what need is single number that represents the variance of this entire dataset sothe next thing ' going to do is find the square of these differences ' just going to go through each one of those raw differences from the mean and square them this is for couple of different reasonsfirsti want to make sure that negative variances count just as much as positive variances otherwisethey will cancel each other out that' be bad secondi also want to give more weight to the outliersso this amplifies the effect of things that are very different from the mean while stillmaking sure that the negatives and positives are comparable (