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Unit Converters · Free tool

Standard Deviation Calculator

Calculate sample (n−1) and population (n) standard deviation and variance side by side. Paste any list of numbers. Free, instant, browser-only, no sign-up.

Updated June 2026

n

8

Mean (x̄)

23.125

Min / Max

12 / 34

Range

22

Sample (divide by n−1)

σ ≈ 7.7908

Variance: 60.6964

Use when your data is a subset of a larger population.

Population (divide by n)

σ = 7.2876

Variance: 53.1094

Use only when you have the entire population — rare in real research.

Why two different formulas

Sample variance divides by n − 1 (Bessel's correction) because the sample mean is itself an estimate — it slightly underestimates the true population variance, so you compensate by using a smaller divisor.

For most inferential work (hypothesis tests, confidence intervals), use the sample formula. The population formula is only correct when your data is literally the entire population — e.g. every student in a 30-person class.

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What it does

Compute mean, variance, and standard deviation for any list of numbers — with both the sample (n−1) and population (n) formulas shown side-by-side, so students can pick the right one for their assignment without second-guessing.

For a full summary including median, mode, and range see the average calculator. To check whether your variance is significant, use the p-value calculator.

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Paste this snippet into any page. Loads on-demand (lazy), no tracking scripts, and sized to most dashboards. Replace the height to fit your layout.

<iframe src="https://freetoolarena.com/embed/standard-deviation-calculator" width="100%" height="720" frameborder="0" loading="lazy" title="Standard Deviation Calculator" style="border:1px solid #e2e8f0;border-radius:12px;max-width:720px;"></iframe>
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How to use it

  1. Paste your numbers — comma, space, or newline separated.
  2. Read the sample (n−1) standard deviation for inferential work.
  3. Use the population (n) version only if you have the entire population.
  4. Variance is the squared standard deviation — both are shown.

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