Which statement about non-parametric tests' data requirements is true?

Which statement about non-parametric tests' data requirements is true?

• A. They require normally distributed data.
• B. They require interval data only.
• C. They require ratio data only.
• D. They can use ordinal or nominal data without assuming normality.

Answer: (D)

Non-parametric tests are designed for data that don’t meet the assumptions of parametric tests, especially normality, and they don’t require interval or ratio measurements. Instead of relying on means and standard deviations, these methods use the data’s order or frequency counts, so they work with ordinal data and, in many cases, nominal data as well, all without assuming a normal distribution. This flexibility is why using ordinal or nominal data with non-parametric tests is appropriate and why normality isn’t required.

Non-parametric tests are designed for data that don’t meet the assumptions of parametric tests, especially normality, and they don’t require interval or ratio measurements. Instead of relying on means and standard deviations, these methods use the data’s order or frequency counts, so they work with ordinal data and, in many cases, nominal data as well, all without assuming a normal distribution. This flexibility is why using ordinal or nominal data with non-parametric tests is appropriate and why normality isn’t required.