How can we determine if a test is parametric or non-parametric?

In order to determine whether a test is parametric or non-parametric, it is essential to consider the underlying assumptions and characteristics of the data being analyzed. Parametric tests assume that the data follows a specific distribution or a known population parameter, such as a normal distribution or a specific mean. These tests require these assumptions to be met in order to yield accurate results. On the other hand, non-parametric tests do not rely on any specific distribution or population parameter, making them more versatile and less restrictive. They are suitable for data that may not meet the assumptions of parametric tests, such as data with outliers or non-normal distributions. By evaluating the nature of the data and assessing the assumptions necessary for parametric tests, one can determine whether a test should be parametric or non-parametric.

This mind map was published on 13 October 2023 and has been viewed 121 times.