population variance versus sample variance there is little nuance to standard deviation and varianceand that' when you're talking about population versus sample variance if you're working with complete set of dataa complete set of observationsthen you do exactly what told you you just take the average of all the squared variances from the mean and that' your variance howeverif you're sampling your datathat isif you're taking subset of the data just to make computing easieryou have to do something little bit different instead of dividing by the number of samplesyou divide by the number of samples minus let' look at an example we'll use the sample data we were just studying for people standing in line we took the sum of the squared variances and divided by that is the number of data points that we hadto get ( if we were to look at the sample variancewhich is designated by it is found by the sum of the squared variances divided by that is ( this gives us the sample variancewhich comes out to ( so againif this was some sort of sample that we took from larger datasetthat' what you would do if it was complete datasetyou divide by the actual number okaythat' how we calculate population and sample variancebut what' the actual logic behind itthe mathematical explanation as for why there is difference between population and sample varianceit gets into really weird things about probability that you probably don' want to think about too muchand it requires some fancy mathematical notationi try to avoid notation in this book as much as possible because think the concepts are more importantbut this is basic enough stuff and that you will see it over and over again