Calculate mean, standard deviation, and variance for any dataset — supports both population and sample standard deviation.
The Standard Deviation Calculator computes the mean, standard deviation, and variance of a set of numbers. Standard deviation is a fundamental statistical measure that quantifies how spread out values are around the average (mean). A low standard deviation means values are clustered close to the mean; a high standard deviation means values are widely spread.
This calculator supports both Population Standard Deviation (σ) and Sample Standard Deviation (s). The distinction matters: use population SD when you have data for the entire population (all values). Use sample SD when you have a sample drawn from a larger population and want to estimate the population's variability.
How to Enter Data
Type your numbers separated by commas in the input field. For example: "10, 20, 30, 40, 50" or "4.5, 3.2, 7.8, 2.1". The calculator handles any count of values.
Where Standard Deviation Is Used
- Finance and investing: Standard deviation of stock returns measures investment risk/volatility. A high SD stock is more volatile. Portfolio management, mutual fund performance comparison, and risk assessment all rely on SD.
- Quality control: Manufacturing companies use SD to monitor consistency. If a machine is supposed to produce bolts of 10mm length, the SD of actual bolt lengths tells engineers how consistent the machine is.
- Academic grading: Teachers use mean and SD to understand class performance distribution. A mean of 70% with SD of 5% means most students are between 65–75%.
- Medical research: Clinical trials use SD to describe how consistent patient responses are to a treatment.
- Weather data: Standard deviation of daily temperatures shows how variable the weather is in a region.
- Sports analytics: SD of a cricket batsman's scores shows consistency — a low SD means consistently good/bad; a high SD means unpredictable.
1. Enter your numbers: Type all values separated by commas (e.g., 5, 10, 15, 20, 25). You can also separate by spaces.
2. Select type: Choose Population SD (σ) if your data represents the entire group, or Sample SD (s) if your data is a subset of a larger population.
3. View Results: The calculator shows mean, standard deviation, variance, count, and sum.
Mean (μ or x̄) = Σxᵢ / N
Population Variance (σ²) = Σ(xᵢ − μ)² / N
Population SD (σ) = √(σ²)
Sample Variance (s²) = Σ(xᵢ − x̄)² / (N − 1)
Sample SD (s) = √(s²)
The N−1 divisor in sample SD is Bessel's correction — it corrects for the bias introduced when estimating population variance from a sample.
Example: Dataset {2, 4, 4, 4, 5, 5, 7, 9}
Mean = 40/8 = 5
Variances from mean: {9,1,1,1,0,0,4,16} → Sum = 32
Population Variance = 32/8 = 4
Population SD = √4 = 2
Example 1: {10, 20, 30, 40, 50} → Mean = 30. Deviations²: {400, 100, 0, 100, 400}. Population Variance = 1000/5 = 200. SD = √200 ≈ 14.14.
Example 2 — Finance: Monthly stock returns (%): {5, -2, 8, 3, -1, 6} → Mean = 19/6 ≈ 3.17%. Sample SD ≈ 3.49%. This measures the stock's monthly volatility.
Example 3 — Identical values: {5, 5, 5, 5} → Mean = 5. SD = 0. Zero standard deviation means all values are identical.