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 2 added 147 characters in body edited Apr 7 at 0:52 gung♦ 114k22 gold badges6161 silver badges111111 bronze badges Do we really need two tags for [parametric] and [nonparametric]? I propose that we have a single tag that covers both. Given that existing usage has favored np, we could make that the master, but also update the excerpt / usage guidance Given that existing usage has favored np, we could make that the master, but also update the excerpt / usage guidance and full wiki. Updated suggestion: We create a new tag and full wikimap both of the original tags to it. To wit: nonparametric $$\leftarrow$$ parametric $$\rightarrow$$ parametric-nonparametric $$\leftarrow$$ nonparametric [nonparametric] 1,290 threads, an excerpt & wiki [parametric] 252 threads (of which 95 have both), an excerpt, but no wiki The current excerpts are, [nonparametric]: Procedures that rely on relatively few assumptions about underlying probability distributions. [parametric]: Statistical models described by a finite number of real-valued parameters. Often used in contrast to non-parametric statistics. I'm certainly open to discussion about the new excerpt / usage guidance, but the kind of thing I have in mind might be: Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters. Note that this excerpt has 312 characters, which is longer than the typical excerpt, but well within the limits, and would not be the longest excerpt, even among the top tags. Do we really need two tags for [parametric] and [nonparametric]? I propose that we have a single tag that covers both. Given that existing usage has favored np, we could make that the master, but also update the excerpt / usage guidance and full wiki. To wit: nonparametric $$\leftarrow$$ parametric [nonparametric] 1,290 threads, an excerpt & wiki [parametric] 252 threads (of which 95 have both), an excerpt, but no wiki The current excerpts are, [nonparametric]: Procedures that rely on relatively few assumptions about underlying probability distributions. [parametric]: Statistical models described by a finite number of real-valued parameters. Often used in contrast to non-parametric statistics. I'm certainly open to discussion about the new excerpt / usage guidance, but the kind of thing I have in mind might be: Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters. Note that this excerpt has 312 characters, which is longer than the typical excerpt, but well within the limits, and would not be the longest excerpt, even among the top tags. Do we really need two tags for [parametric] and [nonparametric]? I propose that we have a single tag that covers both. Given that existing usage has favored np, we could make that the master, but also update the excerpt / usage guidance and full wiki. Updated suggestion: We create a new tag and map both of the original tags to it. To wit: parametric $$\rightarrow$$ parametric-nonparametric $$\leftarrow$$ nonparametric [nonparametric] 1,290 threads, an excerpt & wiki [parametric] 252 threads (of which 95 have both), an excerpt, but no wiki The current excerpts are, [nonparametric]: Procedures that rely on relatively few assumptions about underlying probability distributions. [parametric]: Statistical models described by a finite number of real-valued parameters. Often used in contrast to non-parametric statistics. I'm certainly open to discussion about the new excerpt / usage guidance, but the kind of thing I have in mind might be: Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters. Note that this excerpt has 312 characters, which is longer than the typical excerpt, but well within the limits, and would not be the longest excerpt, even among the top tags. 1 answered Apr 5 at 17:05 gung♦ 114k22 gold badges6161 silver badges111111 bronze badges Do we really need two tags for [parametric] and [nonparametric]? I propose that we have a single tag that covers both. Given that existing usage has favored np, we could make that the master, but also update the excerpt / usage guidance and full wiki. To wit: nonparametric $$\leftarrow$$ parametric [nonparametric] 1,290 threads, an excerpt & wiki [parametric] 252 threads (of which 95 have both), an excerpt, but no wiki The current excerpts are, [nonparametric]: Procedures that rely on relatively few assumptions about underlying probability distributions. [parametric]: Statistical models described by a finite number of real-valued parameters. Often used in contrast to non-parametric statistics. I'm certainly open to discussion about the new excerpt / usage guidance, but the kind of thing I have in mind might be: Use this tag to ask about the nature of nonparametric or parametric methods, or the difference between the two. Nonparametric methods generally rely on few assumptions about the underlying distributions, whereas parametric methods make assumptions that allow data to be described by a small number of parameters. Note that this excerpt has 312 characters, which is longer than the typical excerpt, but well within the limits, and would not be the longest excerpt, even among the top tags.