How it works
Standard deviation measures the average distance of data points from the mean.
Step 1: Calculate the Mean
Add all values together and divide by the number of values.
Formula:
Mean (x̄) = Σx / n
Example dataset:
10, 15, 18, 22, 30
Mean:
(10 + 15 + 18 + 22 + 30) ÷ 5 = 19
Step 2: Find Deviations from the Mean
Subtract the mean from each value.
10 - 19 = -9
15 - 19 = -4
18 - 19 = -1
22 - 19 = 3
30 - 19 = 11
Step 3: Square Each Deviation
Squaring removes negative values and emphasizes larger differences.
81, 16, 1, 9, 121
Step 4: Calculate Variance
For a population:
Variance = Σ(x - μ)² / N
For a sample:
Variance = Σ(x - x̄)² / (n - 1)
The sample formula uses n − 1, known as Bessel's correction, to provide a more accurate estimate of the population variance.
Step 5: Calculate Standard Deviation
Take the square root of the variance.
Standard Deviation = √Variance
The resulting value indicates how much variation exists within the dataset.
Interpreting Standard Deviation
Low Standard Deviation
A low standard deviation means data points are clustered closely around the mean.
Example:
48, 49, 50, 51, 52
High Standard Deviation
A high standard deviation means values are spread farther from the mean.
Example:
10, 25, 50, 75, 90
Sample vs Population Standard Deviation
Use Sample Standard Deviation When
- Analyzing a subset of a larger population
- Conducting surveys
- Working with research samples
- Estimating population characteristics
Use Population Standard Deviation When
- You have the complete dataset
- Analyzing all employees, customers, or records
- Evaluating full populations
Additional Statistics Provided
This calculator also computes:
- Mean
- Median
- Variance
- Minimum value
- Maximum value
- Range
- Coefficient of variation (CV)
- Number of observations
These statistics provide a more complete understanding of your dataset's distribution and variability.