Standard Deviation Calculator
Calculate sample and population standard deviation (σ).
GCD & LCM Calculator
About Standard Deviation Calculator
The Standard Deviation & Variance Calculator computes sample standard deviation (s), population standard deviation (σ), variance (s²), arithmetic mean (μ), median, range, and sum of squares for any dataset with step-by-step statistical tables.
How to Use Standard Deviation Calculator
Step 1
Paste or type numbers separated by commas, spaces, or line breaks.
Step 2
Select Sample (n-1) or Population (N) mode.
Step 3
Inspect the calculated Standard Deviation, Variance, and Mean cards.
Step 4
Review the step-by-step calculation table below.
Practical Use Cases for Standard Deviation Calculator
Data Science & Statistical Analysis
Analyze data dispersion, variance, and volatility in experimental research, machine learning features, and A/B test metrics.
Finance & Stock Volatility Modeling
Measure the risk and price volatility of equity assets, investment returns, and crypto portfolio benchmarks.
Input & Output Examples
Calculating Standard Deviation for Dataset: 10, 12, 23, 23, 16, 23, 21, 16
Data: 10, 12, 23, 23, 16, 23, 21, 16
Mean (x̄): 18.0 | Sample Std Dev (s): 5.237 | Population Std Dev (σ): 4.899 | Sample Variance (s²): 27.429
Key Features & Performance
- ✓Calculates both Sample Standard Deviation (n - 1) and Population Standard Deviation (n).
- ✓Computes Mean, Median, Mode, Variance, Range, and Sum of Squares (SS).
- ✓Step-by-step statistical deviation table shows (x - μ) and (x - μ)² for every data point.
- ✓Flexible data entry: Accepts comma, space, or newline-delimited numbers.
- ✓100% Client-Side memory execution guarantees data confidentiality.
- ✓1-Click Copy statistical summary.
Key Terminology & Definitions
Standard Deviation (σ / s)
A measure of the amount of variation or dispersion of a set of values from its arithmetic mean.
Sample vs Population Variance (Bessel's Correction)
Sample variance divides by (n - 1) to correct for bias when estimating population parameters from a limited sample.
