Standard Deviation Calculator (Sample & Population Variance)
Calculate sample and population standard deviation, variance, and mean with step-by-step steps.
TL;DR: Standard Deviation Calculator measures data dispersion by calculating population standard deviation ($\sigma$) and sample standard deviation ($s$), variance, and mean.
What Is the Difference Between Sample and Population Standard Deviation?
Population standard deviation (σ) is used when analyzing an entire dataset, dividing by N: σ = √[Σ(x - μ)² / N]. Sample standard deviation (s) is used when estimating population variance from a sample, applying Bessel's correction by dividing by (n - 1): s = √[Σ(x - x̄)² / (n - 1)].
How to Use the Standard Deviation Calculator
Our Standard Deviation Calculator performs high-precision mathematical operations directly in your browser with zero latency and complete client-side privacy.
- Paste or type your numbers separated by commas, spaces, or line breaks.
- Select dataset type: 'Sample (n - 1)' OR 'Population (N)'.
- Click 'Calculate Statistics' to compute standard deviation and variance.
- Review the step-by-step deviations from the mean and sum of squared differences.
- Inspect summary statistics: Mean, Median, Mode, Range, and Standard Error.
Mathematical Formula & Equations
Measures data dispersion, variance, standard error of the mean, and confidence intervals.
Calculation Example
For dataset [10, 12, 23, 23, 16, 23, 21, 16]: Mean = 18.0, Sample Variance = 26.57, Sample Standard Deviation $s = 5.15$.
100% Client-Side Privacy & Data Security
All calculations, amortization schedules, variables, and sensitive numerical datasets execute 100% locally in your web browser memory. Your financial, medical, and personal values are never transmitted, logged, or uploaded to any external server.
Frequently Asked Questions
- Standard deviation measures the average distance of data points from their mean. A low standard deviation indicates values cluster close to the mean; a high value indicates data is spread over a wide range.
- Bessel's correction divides by `n - 1` instead of `n` in sample standard deviation to correct for bias, preventing underestimation of the true population variance.
- Variance is standard deviation squared (`Variance = σ²`). Standard deviation is the square root of variance, returning dispersion back to the original units of measurement.
- In a normal distribution, approximately 68% of data falls within 1 standard deviation of the mean, 95% falls within 2 standard deviations, and 99.7% falls within 3 standard deviations.
- Standard deviation measures variability among individual data points. Standard error measures how accurately the sample mean represents the true population mean (`SE = s / √n`).
- Use sample standard deviation (Bessel's correction dividing by n-1) when analyzing a subset of data to infer whole-group properties. Use population standard deviation when you have measured the entire universe.
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