Parametric tests are appropriate for which data types?

Parametric tests are appropriate for which data types?

• A. Ordinal data
• B. Interval or ratio data that are normally distributed
• C. Nominal data
• D. Categorical data only

Answer: (B)

Parametric tests assume data are measured on an interval or ratio scale and come from a population that is approximately normally distributed. This lets us use means and variance in the analysis and rely on distributional assumptions to compute p-values and confidence intervals. When data meet these conditions, tests like the t-test or ANOVA are appropriate. If data are ordinal or nominal, they do not satisfy the required measurement scale or distribution assumptions, so nonparametric methods are typically used instead. Therefore, the appropriate data type for parametric tests is interval or ratio data that are normally distributed.

Parametric tests assume data are measured on an interval or ratio scale and come from a population that is approximately normally distributed. This lets us use means and variance in the analysis and rely on distributional assumptions to compute p-values and confidence intervals. When data meet these conditions, tests like the t-test or ANOVA are appropriate. If data are ordinal or nominal, they do not satisfy the required measurement scale or distribution assumptions, so nonparametric methods are typically used instead. Therefore, the appropriate data type for parametric tests is interval or ratio data that are normally distributed.