Parametric tests are characterized by which of the following?

Parametric tests are characterized by which of the following?

• A. They make no assumption about the distribution of data.
• B. They are always more robust than nonparametric tests.
• C. They assume specific distributions and conditions such as normality and homogeneity of variance.
• D. They are always derived from nonparametric distributions.

Answer: (C)

Parametric tests rely on specific distributional assumptions about the data, typically that the populations are normally distributed and that variances are equal across groups (homogeneity of variance). Because these tests use distributional parameters like the mean and variance to calculate probabilities, they are most powerful when these conditions hold, which is why they’re preferred in those cases. Saying they impose no distributional assumptions is incorrect, and claiming they are always more robust than nonparametric tests ignores how violations of these assumptions can undermine results. They are also not derived from nonparametric distributions, so that statement doesn’t fit.

Parametric tests rely on specific distributional assumptions about the data, typically that the populations are normally distributed and that variances are equal across groups (homogeneity of variance). Because these tests use distributional parameters like the mean and variance to calculate probabilities, they are most powerful when these conditions hold, which is why they’re preferred in those cases. Saying they impose no distributional assumptions is incorrect, and claiming they are always more robust than nonparametric tests ignores how violations of these assumptions can undermine results. They are also not derived from nonparametric distributions, so that statement doesn’t fit.