BCBetter Calculators

Standard Deviation Calculator

Calculate the population standard deviation and variance for up to six numbers.

🧮

Enter your values and click Calculate

How It Works

The calculator starts by computing the arithmetic mean of all six values by summing them and dividing by six. It then finds each value's deviation from the mean (value − mean), squares each deviation to make all values positive and to penalise larger deviations more heavily, and sums those squared deviations. Dividing that sum by the count of values (n) gives the population variance — the average squared distance from the mean. Finally, the square root of the variance is taken to bring the measure back to the same units as the original data, producing the population standard deviation. This calculator uses the population formula (÷ n) rather than the sample formula (÷ n−1), which is appropriate when the six values represent the complete dataset rather than a sample drawn from a larger group.

Examples

Evenly spaced values
Values 10, 20, 30, 40, 50, 60.
Result: Mean = 35, Variance = 291.67, Std Dev ≈ 17.08.
All equal values
Six values all equal to 25.
Result: Std Dev = 0, Variance = 0 (no spread).
Test scores with moderate spread
Six student scores: 70, 75, 80, 85, 90, 95.
Result: Mean = 82.5, Variance = 72.92, Std Dev ≈ 8.54.

Frequently Asked Questions

What is the difference between population and sample standard deviation?
Population standard deviation divides the sum of squared differences by N (the total number of values), and is used when your dataset represents the entire group you care about. Sample standard deviation divides by N−1 to correct for the fact that a sample tends to underestimate the true population spread. This calculator uses the population formula.
What is variance?
Variance is the average of the squared differences from the mean. Standard deviation is the square root of variance and is expressed in the same units as the original data, making it easier to interpret. Variance is more commonly used in statistical formulas and tests, while standard deviation is more intuitive for describing data spread.
How do I interpret the standard deviation result?
A low standard deviation means your values are tightly clustered near the mean, while a high standard deviation means they are spread out widely. For example, test scores with a mean of 75 and an SD of 2 are much more consistent than scores with the same mean but an SD of 15, which indicates wide variation across students.

Related Calculators