I systematically chose rare words from three groups of texts (#1, #2 and #3) (the rare words within each group are different, but some rare words may appear in more than one group).
Then, for each rare word, I attempted to found out how frequent it is in one corpus (a large, systematic aggregation of texts), called Corpus P, and how frequent it is in another (Corpus B). Using the frequencies, I found out the log-likelihood statistic for each ratio of frequencies. This is a common statistic in corpus linguistics, and the bigger it is, the bigger the measure of "surprise" in the frequency ratio.
I was particularly interested in the rare words that were more significantly more frequent in Corpus P than in Corpus B. I want to see if the scores of rare words which meet this requirement significantly differ by text group (#1-3).
The scores for this set of rare words can be found, by text group and in descending order, in this dataset:
- Group #1 (n = 1362)
- Group #2 (n = 285)
- Group #3 (n = 112)
I looked at Q-Q plots at each of the series and they certainly are not normally distributed. Then, based on a literature review, I reached the hypothesis that these statistics have a chi-square distribution, I believe with one degree of freedom.
I wish to examine this assumption, and then find out if these are three significantly different series, i.e. if the rare words from each group have significantly different scores. (I tried to see if they were different without this assumption by applying a non-parametric Wilcoxon rank sum test, but the result was not significant.)
How do I see if each column in the data has a distribution similar to chi square, 1 d.f.? If I see that they are each a good fit to the model, how do I find out if the series are different from eachother?
Thanks in advance.