What does a measure of variability quantify?

A measure of variability is fundamentally focused on the spread or dispersion of data points within a dataset. It provides insight into how much the individual data points differ from each other and from the central tendency (like the mean or median). By quantifying variability, researchers can assess the consistency, reliability, and predictability of the data.

For instance, a dataset with low variability indicates that the values are close to each other and to the central value, suggesting consistency. Conversely, high variability suggests that the data points are spread out over a wide range, indicating diversity or inconsistency within the data. This aspect is critical in statistical analysis, as it informs us not only about the average values but also about the degree of uncertainty or variability in the dataset, which affects the interpretation of results and conclusions drawn from the data.