The variance of a set of values attempts to measure the spread in values around the mean. A variance of zero means that all values are the same, and a small variance means that the values are closely bunched together. A high value for variance indicates that the numbers are spread out widely. Variance is always a positive value.

Var(X) = [Sum ((X - mean(X))²)] / Count(X)

Variance comes in two flavors: population variance and sample variance.

• Population variance computes the variance from all possible values.
• Sample variance computes from a subset or sample of all values.
• Since

  D s product
  r true

   has access to all available values, the computation for population variance is used across the entire dataset.

The square root of variance is standard deviation, which is used to measure variance under the assumption of a bell curve distribution. See STDEV Function.

If a row contains a missing or null value, it is not factored into the calculation.

For a version of this function computed over a rolling window of rows, see ROLLINGVAR Function.

Output: Generates a new table containing the unique values of the postal_code column and the variance of the group of values from the myRating column for the postal_code value. The limit parameter defines the maximum number of output columns.

For more information on the group and limit parameters, see Pivot Transform.

function_col_ref

Name of the column the values of which you want to calculate the variance. Column must contain Integer or Decimal values.

• Literal values are not supported as inputs.
• Multiple columns and wildcards are not supported.