I find there are some questions about sets, but there isn't any tag about it.

I would like to ask questions about them and learn more about them. Thus I thought about creating a new tag to group the questions.

Currently most questions I see are about different similarity metrics between sets or about rank based analysis of sets like gene set enrichment analysis.

Proposed tag wiki excerpt:

For questions about analysis of groups of nominal variables

Prototype of a full tag wiki :

A set (See definition) can be defined as a group of elements:
set1 = element1, element2, element3
Questions might be about similarity indices, or analysis on them.

PS: Are here some knowledge on operations and tests?

  • 3
    $\begingroup$ What would be the utility for such tag? Why would it be helpful? Who would benefit from it? Notice that there is 15,237 questions in your query, nobody will tag them by hand, so creating the tag would not change anything for those questions. $\endgroup$
    – Tim
    Commented Jan 2, 2019 at 11:56
  • $\begingroup$ I will use it, it would help to users interested in analyse sets. I would retag those question that fit as I found them (and I hope new questions will use the tag too) $\endgroup$
    – llrs
    Commented Jan 2, 2019 at 12:14
  • 2
    $\begingroup$ Tags grow out of the needs of users. We have found that it is rare that a retrospective application of a tag is helpful. In this case, if not a single one of the thousands of users who had questions related to sets elected to create this tag, it's unlikely it will help to apply it to their questions now, no matter how appropriate it might seem to be. $\endgroup$
    – whuber Mod
    Commented Jan 2, 2019 at 22:25

1 Answer 1


It seems to me that this will lead to potential problems because:

1 - it might encourage people to ask questions about set theory which are better on another site

2 - the proposed scope is too broad as the analysis of groups of categorical variables might cover many different techniques like item response theory, various forms of principal component analysis, logistic regression, log-linear models, latent class analysis, ...


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