What does variance measure in a set of data?

Variance is a statistical measure that reflects the degree to which data points in a dataset differ from the mean of that dataset. Specifically, it quantifies how spread out the numbers are. When calculating variance, each data point's deviation from the mean is measured, squared, and then averaged, providing a comprehensive measure of the data's dispersion.

Understanding variance helps in determining the consistency or variability within the dataset. A low variance indicates that the data points tend to be close to the mean, while a high variance shows that the data points are spread out over a wider range of values. This concept is essential in fields such as health sciences, where understanding the spread of data can inform decision-making and research conclusions.

The other options refer to different statistical concepts: the average value refers to the mean, the largest value pertains to the maximum in the dataset, and the relationship between two variables would be addressed through correlation or regression analysis. These aspects do not convey the specific measure of spread that variance encapsulates.