Or at least initially it's counterintuitive, but hopefully you'll appreciate this over time. This we've already talked about in some depth. People have even created simulations to show that this is an unbiased estimate of population variance when we divide it by n minus 1. And that's a good starting point if we're going to take the square root of anything. But it actually turns out that because the square root function is nonlinear, that this sample standard deviation, and this is how it tends to be defined, sample standard deviation, that this sample standard deviation, which is the square root of our sample variance, so from i equals 1 to n of our unbiased sample variance, so we divide it by n minus 1. This is how we literally divide our sample standard deviation. Because the square root function is nonlinear, it turns out that this is not an unbiased estimate of the true population standard deviation.