Where can I find a study on the amount of different word frequencies in a corpus? I need to know how many different values the frequency of a certain word in a corpus can there be for a natural language processing problem. Is there any study or site that has such estimation?
What you're asking directly refers to Information Retrieval. Information Retrieval directly creates models for such things as frequency of words in a corpus and so on.

In a corpus, different indicators are estimated in order to create a score. Two indicators are predominant in those models :


Inverse document frequency (idf)


This model aims at attenuating words that appear too often and considered irrelevant to judge the score of a word.

$ idf_{t} = log\frac{N}{df_{t}}$ where $N$ stands for the total of document in a collection and $df_{t}$  the number of documents in a collector that contain the term $t$


Term frequency (tf)


This is the most basic way to modelize word frequency in a corpus. It can be computed by saying that:

$tf_{t,d} = \frac{t_{occ}}{N}$ where $t_{occ}$ is the occurence of the term divided by the number of words in the document.

More information on this subject can be found here :

Scoring, term weighting and the
vector space model