Syntax. DVAR(database,field,criteria)

Definition. This function estimates the variance of a sample based on the numbers in a column in a list or database that match the specified conditions.

Arguments

Background. The most commonly used spreads in statistics are the variance and the standard deviation. The variance is the sum of the squared deviation of each value from the mean divided by the number of values with an adjustment for the sample.

Example. Because the sample variance measures the spread of data, it is often used in descriptive statistics.

Assume that you are a wholesaler and want to use the DVAR() function to explain variation in your sales orders. Let’s use the example for the DSTDEV() function. The goal 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 13-31).

Figure 13-31. Calculating the variance based on a sample.

To analyze the data, you need to calculate the mean, as shown in Figure 13-32.

Figure 13-32. The mean of the sales of Longlife Tofu in the United States.

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 the variance, the result is the standard deviation (see the DSTDEV() function, described earlier in this chapter).