What kind of data do parametric tests require?

The correct response identifies the necessity for parametric tests to utilize normally distributed interval or ratio data. Parametric tests, such as t-tests or ANOVA, rely on certain assumptions, one of which is that the data should be normally distributed. This means that the values are spread in a bell-shaped curve, which allows for the application of various statistical techniques that assume the underlying distribution of the population from which the samples are drawn.

Moreover, data measured on interval or ratio scales provide a higher level of information, allowing for meaningful mathematical operations such as addition and multiplication, unlike nominal or ordinal data. The analysis of interval or ratio data enables parametric tests to produce more powerful statistical inferences due to the use of means and variances, which are central to their calculations.

Understanding the nature of data that is appropriate for parametric analyses is crucial in the context of Evidence-Informed Practice, as selecting the right statistical method contributes to the validity and reliability of study findings and conclusions.