Which Statistical Measure Shows Student Score Distribution?

Why the Answer Is Correct

Standard deviation is the standard CompTIA Data+ answer for measuring the distribution or spread of a data set relative to its mean. For an administrator asking whether class scores are tightly clustered or widely scattered, standard deviation directly answers that in the same units as the scores themselves, so a result of, say, 8 points is immediately interpretable. It is derived from the variance by taking the square root, which restores the original measurement scale and makes it the practical measure of distribution.

Why the Other Options Are Wrong

Option D, variance, is a legitimate spread metric but it is the square of the standard deviation, so its values are in squared units and it is harder to interpret as a distribution summary; when both appear, CompTIA expects standard deviation. Option C, a t-test, is an inferential hypothesis test used to compare the means of two groups, not a descriptive measure of how one class's scores are distributed. Option B, geometric progression, is a mathematical sequence in which each term is multiplied by a constant ratio; it has no role in summarizing a score distribution.

Community Comment Notes

Amelia233 selected A and correctly framed standard deviation as measuring "the spread or distribution of scores around the mean," while noting that variance "also measures spread" but is not the intended pick. That reasoning aligns with the CompTIA objective wording, and the comment's dismissal of the t-test as a between-group comparison is accurate. When variance and standard deviation both appear as distractors, default to standard deviation unless the question explicitly asks about squared dispersion.