>> In general, samples underestimate the amount of variability in a population,
because samples tend to be values in the middle of the population. Especially in
a normal distribution, most of the values are centered here in the middle. So
when we take samples from it, most of our values are going to be around here,
since most of the values are in this area. Therefore the variability in this
sample will be less than the variability of the entire population. To correct
for this, we use something called Bessel's correction, where instead of dividing
by n, we divide by n minus 1. Same within the variance. So what will dividing by
n minus 1 do to the original standard deviation and variance? Will it make them
bigger, or will it make them smaller?