Find how spread out a set of numbers is. Enter your data set and this calculator works out the mean, variance and standard deviation step by step.

Standard Deviation Calculator

Compute sample standard deviation (s) or population standard deviation (σ), variance, mean, standard error of the mean (SEM), and 95% confidence interval from any dataset.

Sample (s) & Population (σ) Variance, Mean & SEM Save PDF · PNG · Share Step-by-step Σ(x − x̄)²

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TinyExe · Std Dev Result

Dispersion, variance, mean & confidence interval

Calculated on
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– Std Dev
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Name

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Mean (x̄) & Count

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Variance

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Std. Error (SEM)

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How this was calculated

    What to do next

      TinyExe · tinyexe.com — Sample mode uses Bessel's correction (dividing by n − 1) to produce an unbiased estimator of population variance.

      TinyExe PDF & PNG exports carry the TinyExe logo and tinyexe.com header & footer.

      Sample mode uses Bessel's correction (dividing by n − 1) to produce an unbiased estimator of population variance.

      Embed this tool

      Add this Standard Deviation Calculator to your own page — copy the code below and paste it where you want the tool to appear.

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      Works in WordPress (Custom HTML block), HTML pages, and most site builders.

      Sample vs. Population Standard Deviation

      Choosing the right denominator depends on whether your data is a sample or the entire population.

      Statistic Symbol Divisor & Use Case
      Sample Standard Deviation s Divides by (n − 1). Used in experiments, surveys, and subsets.
      Population Standard Deviation σ Divides by n. Used when every member of the group is measured.
      Variance s² or σ² Average squared deviation from the mean before taking √.
      Standard Error (SEM) s ÷ √n Measures how precisely the sample mean estimates the true mean.

      The formula

      The two standard deviation formulas in statistics.

      Sample Standard Deviation (s)

      s = √[ Σ(xᵢ − x̄)² ÷ (n − 1) ]

      Subtract the sample mean x̄ from each value, square each difference, sum them up, divide by n − 1, and take the square root.

      Population Standard Deviation (σ)

      σ = √[ Σ(xᵢ − μ)² ÷ N ]

      Divides the sum of squared deviations by the full population size N.

      Worked examples

      Worked dispersion calculations.

      Example 1 · Sample (n=8)

      10, 12, 23, 23, 16, 23, 21, 16

      Mean x̄ = 18.0, Σ(x − x̄)² = 192.

      CalculationSteps
      s² = 192 ÷ 7 = 27.4286Divide by n − 1 = 7.
      s = √27.4286 ≈ 5.2372Sample standard deviation.

      s = 5.2372

      Example 2 · Population (N=8)

      Same dataset as full population

      Mean μ = 18.0, Σ(x − μ)² = 192.

      CalculationSteps
      σ² = 192 ÷ 8 = 24.0Divide by N = 8.
      σ = √24 ≈ 4.8990Population standard deviation.

      σ = 4.8990

      Example 3 · Zero Spread

      5, 5, 5, 5, 5

      Identical observations.

      CalculationSteps
      Σ(x − 5)² = 0Every deviation from the mean is 0.
      s = 0, σ = 0Zero dispersion.

      SD = 0

      How to use this calculator

      Choose Sample (s) or Population (σ)

      Use Sample (s) for almost all scientific, survey, and classroom datasets.

      Paste or type your numbers

      Separate values with commas or spaces.

      Press Calculate Standard Deviation

      Get the standard deviation, variance, mean, SEM, and 95% confidence interval.

      Empirical Rule (68–95–99.7): For bell-shaped normal distributions, about 68% of data falls within ±1 SD of the mean, 95% within ±2 SD, and 99.7% within ±3 SD.

      Frequently asked questions

      Why do we divide by n − 1 for sample standard deviation?

      Dividing by n − 1 (Bessel's correction) corrects for the fact that deviations around a sample mean are slightly smaller on average than deviations around the true unknown population mean.

      What does a high standard deviation mean?

      A larger standard deviation means values are spread out widely from the mean; a standard deviation near 0 means data points cluster tightly around the mean.

      Standard Deviation Calculator — descriptive statistics & dispersion solver. Supports Sample (n − 1) and Population (n).