Standard Deviation Calculator

Compute mean, variance, and standard deviation of a list of numbers — both sample (n−1) and population (n) versions.

Count (n)
Mean (x̄)
Sum
Sample variance (s²)
Sample SD (s, n−1)
Population variance (σ²)
Population SD (σ, n)
Min
Max
Range

What is Standard Deviation Calculator?

The standard deviation calculator measures how spread out a set of numbers is. A small standard deviation means values cluster near the mean; a large one means they're spread out.

This calculator returns both versions: sample standard deviation (divides by n−1, used when your data is a sample of a larger population) and population standard deviation (divides by n, used when you have the whole population).

Formula

Mean: x̄ = Σx ÷ n

Sample variance: s² = Σ(x − x̄)² ÷ (n − 1)

Sample standard deviation: s = √s²

Population variance: σ² = Σ(x − x̄)² ÷ n

Population standard deviation: σ = √σ²

Worked example

Data: 4, 8, 15, 16, 23, 42 (n = 6)

  • Mean ≈ 18.0
  • Sample SD ≈ 13.65
  • Population SD ≈ 12.46

Sample SD is always slightly larger than population SD on the same data because it divides by a smaller number (n−1).

How to use this calculator

  1. Paste or type your numbers, separated by commas, spaces, or new lines.
  2. The calculator returns count, mean, both standard deviations, range, and min/max.

Frequently asked questions

Sample vs population — which one should I use?

If your data represents the entire population, use population (σ, n). If it's a sample drawn from a larger population, use sample (s, n−1). Most real-world stats and AP Statistics homework use the sample version.

Why divide by n−1 for the sample?

It's called Bessel's correction. Dividing by n underestimates the true population variance because the sample mean tends to be closer to the sample's own values than the true population mean. The n−1 correction is unbiased.

What's a "high" standard deviation?

It's relative — high or low compared to the mean. The coefficient of variation (SD ÷ mean) gives a scale-free measure: above 0.3 is often called highly variable.

How does this connect to the normal distribution?

For a normal (bell-shaped) distribution: ~68% of values fall within 1 SD of the mean, ~95% within 2 SD, and ~99.7% within 3 SD. This is the 68–95–99.7 rule.