Everyday utility

Standard Deviation Calculator

Enter five values to compare average spread for a full population versus a sample taken from a wider population.

Last reviewed May 18, 2026 by ToolSpilo Editorial Team.

Review method: Reviewed against the implemented standard-deviation formulas and spread examples, displayed formulas, and worked examples.

Calculator tool

How this calculator works

Use the explanation to understand the formula, assumptions, and practical limits behind the calculator result.

What Standard Deviation Measures

Standard deviation tells you how spread out values are around their average. If most values stay close to the mean, the standard deviation is small. If they are far apart, it is larger.

A Simple Comparison

The sets 9, 10, 11 and 2, 10, 18 both average to 10, but the second set is much more spread out. Standard deviation captures that difference.

Population and Sample Versions

This calculator reports both forms:

σ=(xμ)2N\sigma = \sqrt{\frac{\sum (x-\mu)^2}{N}}
s=(xxˉ)2n1s = \sqrt{\frac{\sum (x-\bar{x})^2}{n-1}}

Use the population version when you have the whole group. Use the sample version when your values are only a sample from a larger group.

How to Read It

Standard deviation is easier to understand beside the mean and the raw data. A single extreme value can pull it upward because deviations are squared.

Frequently asked questions

When should I use population versus sample standard deviation?

Use population standard deviation when the values are the entire group of interest. Use sample standard deviation when the values are only a sample from a larger group.

Why does the sample formula use n - 1?

Dividing by n1n-1 corrects for the fact that a sample tends to underestimate population spread when it uses its own mean.

Can two data sets have the same mean but different spread?

Yes. The average tells the center, while standard deviation tells how tightly or loosely the values cluster around that center.

Why are outliers influential?

Because deviations are squared before averaging, unusually distant values have a larger effect on variance and standard deviation.