I want to study orthographical variants, for example:

Can firefighter, fire-fighter and fire fighter be considered orthographical variants (the difference in frequency in a corpus is not statistically/practically significant), or should one or more of these orthographical forms be considered "wrong"/"irregular" (the difference in frequency is statistically/practically significant)?

In a corpus of 926,766,504 words, I get the following frequency counts (on lemmas):

  • firefighter = 3,349
  • fire-fighter = 336
  • fire fighter = 1,338

What statistical measure(s) can I use to say, for example, that there is not a large enough difference between firefighter and fire fighter to consider the latter "irregular", but that the difference between firefighter and fire-fighter is significant?

One specific sub-question:

If I work with probabilities (e.g. firefighter = 0,667; fire-fighter = 0,067; fire fighter = 0,266), is there a way to measure if the difference is significant? (Beyond just stating the obvious that the one occurs with a higher probability than the other.)

  • $\begingroup$ A corpus cannot tell you if an orthographic variant is correct or not. Typically a panel of native speakers is used to rate correctness. $\endgroup$ – Anonymous Physicist Nov 28 '16 at 8:23
  • $\begingroup$ I used "wrong" specifically between inverted commas, because that is not the real issue here. It is more about whether a certain form occurs so frequently that it could be considered a viable spelling alternative. Such statistical information would typically inform a panel of experts, as you mentioned. $\endgroup$ – Gerhard Van Huyssteen Nov 28 '16 at 14:27
  • $\begingroup$ What is the difference between "correct" and "viable spelling alternative?" I do not think there is one. I disagree with you about the "real issue." The real issue is that a corpus does not contain correctness information. $\endgroup$ – Anonymous Physicist Nov 28 '16 at 23:21

This might answer your question: Statistical significance between letter frequencies in different corpora

You can use a chi square test of independence.

  • $\begingroup$ As I understand it, this is specifically not an option, because I draw frequencies from the same corpus. Hence, the assumption of independence is violated. Please correct me if I'm wrong. (I'm a statistics virgin!) $\endgroup$ – Gerhard Van Huyssteen Nov 28 '16 at 14:31

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