Measures of central tendency are best described as:

• A. The most extreme values
• B. Typical or expected values
• C. The variance around the mean
• D. The range of data

Answer: (B)

Central tendency is about where the data tend to cluster—the typical or expected value of a data set. Measures like the mean, median, and mode summarize this central point, giving a single value that represents the data’s center.

That’s why describing measures of central tendency as typical or expected values fits best. The other ideas focus on different aspects: the most extreme values point to the tails and extremes of the distribution, not its center; the variance around the mean captures how much scores vary around that center, i.e., dispersion; and the range reflects the spread from the smallest to the largest value, also about distribution shape rather than the central point. For example, in a set of test scores, central tendency tells you the score around which most students cluster, not how far scores vary or how high the furthest score is.