There is a lot of confusion about parametric vs. non-parametric statistics and tests. Some of the literature that explains the difference gets pretty technical. Here is a layman’s description that might not be 100% technically accurate but that will let you understand the difference.A *parameter* is a characteristic of a *population*. We often estimate parameters with *statistics* that come from *samples*. Some common parameters and statistics are the mean, the median, the standard deviation and so on.

Some tests use these parameters. For example, every variety of the t-test uses means and standard deviations. Therefore, the t-test is called a* parametric* test. On the other hand, some tests do not use these parameters. For example, the Mann Whitney U test uses no parameters. Therefore, it is called a non-parametric test.

If you want to tell if a test is parametric or not, look at the formulas used in calculating it. Do they contain parameters/statistics?

pls i want to ask if it is justifiable to use likert scale questionaires on logistic regression

If it’s the dependent variable, you may want ordinal logistic regression or multinomial logistic. If it is an IV, then you can treat it as categorical or continuous

Peter