83. Standard error.

In the previous lesson we show that no matter the underlying distribution of the data set to abuse of the sample means would be normal with a mean equal to the original mean and a variance equal to the original variance divided by the sample size. All right. This lecture will be very short and has the sole purpose of defining what a standard error is. The standard error is the standard deviation of the distribution formed by the sample means. In other words the standard deviation of the sampling distribution. So how do we find it. We know it's variance. Sigma squared divided by n. Therefore the standard deviation is Sigma divided by the square root of n done like a standard deviation. The standard error shows variability. In this case it is the variability of the means of the different samples we extracted. You can guess that since the term has its own name it is widely used and very important. Why is that im