Math calculator

Free standard deviation calculator

Calculate population or sample standard deviation and variance from a dataset — enter your numbers to see all descriptive stats, updated live, as you type.

InputsLive
Type
Numbers (comma-separated)
Enter numbers separated by commas or spaces. Minimum 2 values.
Result
Sample std dev (s)
2.1381
Mean = 5, N = 8
Count (N)8
Mean5
Variance4.5714
Std deviation2.1381

Sample std dev divides by N−1 (Bessel's correction); population divides by N. Source: NIST/SEMATECH e-Handbook of Statistical Methods.

Results are estimates. Consult a professional.

How it's calculated

How the standard deviation calculator works

Standard deviation measures how spread out values are around the mean. A low standard deviation means values cluster tightly near the mean; a high value means they are widely scattered. The formula differs slightly depending on whether the data is a complete population or a sample drawn from a larger population.

Mean: μ = (Σxᵢ) / N
Population std dev: σ = √(Σ(xᵢ μ)² / N)
Sample std dev: s = √(Σ(xᵢ x̄)² / (n 1))
Variance: σ² (population) or s² (sample) = std dev²
Weisstein, E. W. Standard Deviation. MathWorld.
Example

Worked example: {2, 4, 4, 4, 5, 5, 7, 9}

Example: 8 values with mean = 5

Data set: {2, 4, 4, 4, 5, 5, 7, 9}. Calculate the mean, then the sum of squared deviations, and finally both the population and sample standard deviations.

μ = (2+4+4+4+5+5+7+9) / 8 = 40 / 8 = 5
Σ(xᵢμ)² = 9+1+1+1+0+0+4+16 = 32
Population σ = √(32/8) = √4 = 2
Sample s = √(32/7) ≈ √4.571 ≈ 2.14
σ = 2 / s ≈ 2.14
The values typically fall within 2 units of the mean of 5.
Quick reference

The empirical rule (68–95–99.7 rule)

For data that follows a normal (bell-curve) distribution, the empirical rule tells you what percentage of values fall within 1, 2, or 3 standard deviations of the mean.

RangePercentage of dataApproximate coverage
μ ± 1σ68.27%About 2 in 3 values
μ ± 2σ95.45%About 19 in 20 values
μ ± 3σ99.73%Almost all values
Beyond μ ± 3σ0.27%Rare outliers

Source: empirical rule for normal distributions (Gauss, 1809).

Practical tips

Tips for standard deviation

Choosing between population and sample standard deviation — and interpreting the result correctly — are the two most important skills.

  • Population vs sample — use σ (divide by N) when you have every value in the group; use s (divide by n−1) when your data is a random sample and you want to estimate the population spread.
  • Check the units — standard deviation is in the same units as the original data; variance is in squared units. Use std dev for interpretation, variance for further calculations.
  • Outliers inflate std dev — a single extreme value can dramatically increase standard deviation. Consider the median absolute deviation (MAD) for robustness against outliers.
  • Low n makes s unreliable — with fewer than ~30 data points, sample standard deviation is a rough estimate; collect more data when precision matters.
  • Compare with the mean — the coefficient of variation (CV = σ/μ × 100%) lets you compare spread across data sets with different units or scales.
Accuracy & limits

Accuracy and limitations

Standard deviation is calculated using a two-pass algorithm (mean first, then deviations) to minimise floating-point cancellation errors. Results are accurate to approximately 14 significant digits for typical data. Standard deviation does not fully describe non-normal distributions — asymmetric or multi-modal data requires additional measures (skewness, kurtosis, interquartile range). The empirical rule applies only to approximately normal distributions; do not apply it to skewed data.

Glossary

Key terms

The arithmetic average of a data set: sum of all values divided by the count.
The average of squared deviations from the mean; std dev squared.
Standard deviation computed using all N members of a population; denominator is N.
Standard deviation computed from a sample; uses n−1 (Bessel's correction) in the denominator.
Dividing by n−1 instead of n when computing sample variance, to produce an unbiased estimate of the population variance.
For normal distributions: ≈68% of data within 1σ, ≈95% within 2σ, ≈99.7% within 3σ.
About

About this calculator

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Questions

Frequently asked questions about the free standard deviation calculator

A standard deviation calculator is a free online tool that helps you measure how spread out a set of numbers is, with both sample and population modes. Standard deviation measures how spread out values are around the mean. Larger σ means more variability; smaller means values cluster tightly. It runs entirely in your browser with instant results and no sign-up.
Use sample mode unless you have data for the entire population. Sample mode divides by n − 1 (Bessel's correction), which makes the result an unbiased estimator of the true population variance. Population mode divides by N — use this only when you literally have every value in the population (rare in practice).
Variance is the average squared deviation from the mean (σ²). Standard deviation is its square root (σ). They convey the same information; we use standard deviation more often because it's in the original units instead of squared units.
Because there's no spread — every value equals the mean, so every (x − μ) is zero. Standard deviation = 0 only when all values are identical.

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