This function estimates the variance of a sample based on the numerical values in a column within a list or database that match the specified conditions.
Syntax
DVAR(database; field; criteria)
Arguments
- database (required): The cell range that constitutes your list or database.
- field (optional): Indicates which column the function will use.
- criteria (required): The cell range containing the field names and the filter criteria.
Background
The most commonly used measures of spread in statistics are variance and standard deviation. The variance is calculated as the sum of the squared deviations of each value from the mean, divided by the number of values, with an adjustment made for the sample size.
Example
Since the sample variance measures the spread of data, it is frequently used in descriptive statistics.
Assume you are a wholesaler and want to use the DVAR() function to explain the variation in your sales orders. Let’s use the same example as for the DSTDEV() function. The objective here is to calculate the variance instead of the standard deviation, based on a sample with criteria defining the product and country/region selection (see Figure below).
To analyze the data, you will also need to calculate the mean, as shown in Figure below.
The result of the variance calculation, based on a sample and the set criteria, shows an average squared deviation of $90,680.52 from the arithmetic mean. If you take the square root of this variance, the result will be the standard deviation (as described earlier in this chapter, under the DSTDEV() function).