1 00:00:00,012 --> 00:00:05,092 >> Here's another way to look at it. Let's say you have a bag of jellybeans. 2 00:00:05,092 --> 00:00:10,789 There's only one licorice, but there are four strawberries and four blueberries. 3 00:00:10,789 --> 00:00:16,320 There's also only one cherry and two lime, or lemon, I don't know, you decide. 4 00:00:16,320 --> 00:00:21,656 If we take a sample of, say, four Jelly Bellies, most likely, we're not going to 5 00:00:21,656 --> 00:00:26,926 get the licorice one. Say we just get these in our sample. This sample doesn't 6 00:00:26,926 --> 00:00:32,125 show the whole range of Jelly Belly flavors that we have, including cherry and 7 00:00:32,125 --> 00:00:37,117 licorice. So our sample underestimates the variability in our Jelly Belly 8 00:00:37,117 --> 00:00:42,200 population. Hopefully, this example lends a little more insight into why we 9 00:00:42,200 --> 00:00:47,005 divide by n minus 1 when calculating the standard deviation of a sample. But 10 00:00:47,005 --> 00:00:51,936 please let's discuss it in the forums. There, we could go into a lot more depth. 11 00:00:51,936 --> 00:00:56,344 For the purposes of this class though, as long as you have a basic intuitive 12 00:00:56,344 --> 00:01:01,385 understanding of the difference between sample standard deviation and population 13 00:01:01,385 --> 00:01:03,930 standard deviation, then you'll be fine.