Variance Calculator
Use this variance calculator to find the variance of a population or sample set of numbers.
The calculator will also calculate the standard deviation, mean, sum of squares, count, and sum of the data set.
Choose Population or Sample
Enter a list of numbers separated by commas, spaces, and/or line breaks to find the variance. The calculator will automatically remove invalid values (such as letters, words, and symbols).
Variance
Standard Deviation
Mean
Sum of Squares
Count
Sum
How to Use This Calculator
To use this calculator, first, choose whether your data set represents a population or sample.
Next, delete the example set of numbers and enter your data set.
Your data set should be separated by commas:
1,5.8,-50.98,18926,7509.6506832
or spaces:
1 5.8 -50.98 18926 7509.6506832
or line breaks:
1
5.8
-50.98
18926
7509.6506832
or a combination of commas, spaces, and line breaks:
1,5.8 -50.98
18926 20.2
7509.6506832
As you enter your data, the calculator will automatically compute the variance, standard deviation, sum of squares, mean, count, and sum of your data.
What is Variance?
Variance is one way to measure the dispersion of values in a data set from the mean.
More specifically, variance is the average squared difference from the mean.
Low variance means the values in a data set tend to be close to the mean, while a high variance indicates that the values are more widely spread out.
Population vs Sample
The goal of calculating variance is to measure the dispersion of data points in a population. However, we often only have access to a sample set of data.
When we only have a sample, we must use Bessel's correction to correct for bias in the estimation of population variance.
How to Calculate Variance
Population variance is calculated by finding the sum of the squared differences between each data point and the mean (sum of squares), divided by the count of the data set (n).
Sample variance is calculated by finding the sum of the squared differences between each data point and the mean, divided by the count of the data set minus 1 (n - 1).
Variance and Standard Deviation
Calculating variance is crucial for finding the standard deviation of a data set.
Standard deviation is the square root of the variance.