Test users who treat ordinal data as if they were interval data must be constantly alert to the possibility of
A) a highly skewed standard error.
B) gross inequality of intervals.
C) extreme kurtosis in a graphed distribution of test scores.
D) legal challenges from the ACLU.

Question

Quizplus · Accepted Answer

Treating ordinal data as interval data assumes equal distance between categories, which is not always true. This can result in gross inequality of intervals, leading to inaccurate interpretations and conclusions. The other options are not relevant in this context.

Test Users Who Treat Ordinal Data as If They Were