Is there such a thing as similarities between parametric and nonparametric statistics?
I've been doing a research on the subject, spoiler alert: I'm a noob on this. So far, I've been able to find lots of information about the differences between the two, but nothing about the similarities, except for this:
Differences & Similarities between Parametric & Non-Parametric Statistics
.. but the article never touches the subject of similarities.
Can anyone throw me some light on the subject? Thanks.
EDIT: May I politely ask why was my question downvoted? I've done my research (as best as my abilities and understanding of the subject have allowed me to), I've searched on the site, I've found similarly written questions (and getting answered without any issues), I've read the tour and help pages, so I'd love a heads up so I can keep up the quality of the content on the StackExchange sites. Thanks.
Best Answer
Their general similarity is in their approach. Most non-parametric methods are rank methods in some form. Nonparametric methods are, generally, optimal methods of dealing with a sample reduced to ranks from raw data. The logic behind the testing is the same, but the information set is different. Their similarity is in the logic of their construction.