Parametric and non parametric tests – UGC NET Question

Statements A, B, C and D correctly distinguish parametric and non-parametric tests. Parametric tests rest on stronger distributional assumptions and are suited to interval or ratio data, while non-parametric tests are more flexible and can be used for ordinal data or when assumptions are violated. Statement E is false because the appropriateness and accuracy of a test depend on how well its assumptions fit the data; non-parametric tests are not automatically superior. Thus, the set containing A, B, C and D is the only correct combination.

Option A:
Option A includes A, B and C but omits D, failing to note that non-parametric procedures are particularly useful when parametric assumptions do not hold or when dealing with ordinal data. Without D, the practical role of non-parametric tests is understated.

Option B:
Option B lists B, C and D but omits A, so it does not explicitly state that parametric methods assume particular distributions such as normality. This omission weakens the conceptual contrast between the two types of tests.

Option C:
Option C contains A, C and D but leaves out B, thereby not acknowledging that non-parametric tests make fewer assumptions about population form. Since B is a central descriptive point, its absence makes this combination incomplete.

Option D:
Option D is correct because it combines all four accurate statements and excludes E, which exaggerates the superiority of non-parametric methods. It presents a balanced view of when each class of tests is appropriate.