How spread out is your data?
The standard deviation measures how far the values in a data set typically sit from the mean. A small standard deviation means the numbers are clustered tightly; a large one means they are spread widely.
There are two versions. Use the population standard deviation (divide by n) when your data is every member of the group. Use the sample standard deviation (divide by n − 1) when your data is only a sample drawn from a larger group, which is the usual case.
How it is calculated
Worked example
Data: 10, 12, 23, 23, 16, 23, 21, 16
- Mean
- 18
- Sum of squared deviations
- 192
- Sample SD (n − 1)
- 5.2372
- Population SD (n)
- 4.899
Reading the number
- In a bell-shaped data set about 68% of values lie within one SD of the mean, 95% within two and 99.7% within three.
- Standard deviation is in the same units as the data, while variance is in squared units.
- The coefficient of variation (SD ÷ mean) lets you compare spread between data sets on different scales.

