What is a characteristic of the data required for performing a parametric test?

For a parametric test to be valid, one of the key characteristics of the data is that it must come from populations that are normally distributed. This means that the underlying assumption is that the data follows a bell-shaped curve when plotted, which allows for the application of specific statistical techniques that rely on this distribution pattern. Normality ensures that the statistical properties and the behavior of the test statistics are reliable and interpretable.

Parametric tests often have additional assumptions as well, such as homogeneity of variance and interval or ratio measurement scales, but the essential characteristic that distinguishes parametric tests is indeed the reliance on the assumption of normality. This assumption allows for the use of the central limit theorem and provides the mathematical foundation for making inferences about population parameters based on sample statistics.