The standard deviation formula may look confusing, but it will make sense after we break it down. In the coming sections, we'll walk through a step-by-step interactive example.

The formula we use for standard deviation depends on whether the data is being considered a population of its own, or the data is a sample representing a larger population.

Standard deviation measures how far apart numbers are in a data set. Variance, on the other hand, gives an actual value to how much the numbers in a data set vary from the mean.

The standard deviation formula may look confusing, but it will make sense after we break it down. In the coming sections, we'll walk through a step-by-step interactive example.

To find the z-score of the sample mean, you use the formula: Z = X - μ / (σ / sqrt (n)), where X is the sample mean, μ is the population mean, σ is the population standard deviation, and n is …

Finally, we'll take the square root of the variance to get the standard deviation. The complete step-by-step method is also explained. Created by Ashish Gupta.

In this video, we demonstrate how to apply the alternative formula for calculating standard deviation. We'll work through an example with discrete data, constructing a table to find N …

Think about it: remember how the standard deviation squared is the sum of all the points minus the mean squared? Since it is squared, there is no negative numbers, and only the distance …

Practice calculating sample standard deviationWelcome to Khan Academy! So we can give you the right tools, let us know if you're a...

See how distributions that are more spread out have a greater standard deviation.