What does variance measure in descriptive statistics?

Variance is a statistical measure that quantifies the degree to which data points in a dataset differ from the mean of that dataset. By calculating variance, you can understand how much the individual data points vary or spread out around the average value. A higher variance indicates that the data points are more spread out from the mean, while a lower variance suggests that they are closer to the mean. This is essential for interpreting data in various fields, as it provides insights into the diversity and consistency of the data set.

Other options highlight useful statistical concepts but do not accurately define variance. The frequency of different values relates to the distribution of data rather than its variability. The middle value indicates the median of the dataset, and the most common value points to the mode; neither of these addresses the concept of dispersion represented by variance. Thus, the focus on the spread of data points around the mean is what makes the correct choice pivotal in understanding variance in descriptive statistics.