The Variance function estimates the sample variance of a column or group. This statistical measure determines the spread of distribution or degree to which the column or grouped values deviate from the mean. A small variance indicates the values are close to the mean (little variability), while a large variance indicates the values are dispersed farther from the mean (greater variability).

Variance assumes your dataset is a sample of a larger population. If the dataset represents an entire population, use the VariancePop function to calculate actual variance.


Sigma calls the underlying CDW or DBMS function that uses the statistical sample variance definition. Refer to your CDW or DBMS provider’s documentation for details about the called function.



Function argument:

(required) The column to reference when estimating sample variance.

Underlying formula

βˆ‘( xi – xΜ„ )2
n – 1
  • xi = each sample value
  • xΜ„ = the mean of all sample values
  • n = the total number of sample values (sample size)


A table contains a sample of customer ratings for specific products. If the data is grouped by product, you can use the following formula to measure and compare the ratings variability for each product.

Variance([Customer rating (0-5)])

When you calculate the formula in the Product grouping, the function returns the sample variance for each product. This example indicates a broader range of customer ratings for Product B.

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