# [Corpora-List] "normalizing" frequencies for different-sized corpora

Eric Atwell eric at comp.leeds.ac.uk
Mon Sep 12 11:21:00 CEST 2005

Jenny,

I may be missing something, but I think the way to find a per-thousand
figure is simply:

( (freq of word) / (no of words in text) ) * 1000

eg (200/4000) * 1000 = 50

or (2646/55166) * 1000 = 48 (to nearest whole number)

- of course it's up to you whether to round to nearest whole n7umber,
or give the answer to 2 decimal palces (47.96) or some other level
of accuracy; but since generally a text is only a sample or
approximation of the language you are studying, it is sensible not to
claim too much accuracy/significance.

eric atwell

On Mon, 12 Sep 2005, Jenny Eagleton wrote:

> Hello Corpora and Statistics Experts,

>

> This is a very simple question for all the

> corpora/statistics experts

> out there, but this novice is not really

> mathematically inclined. I

> understand Biber's principle of "normalization,

> however I am not sure

> about how to calculate it. I want frequency counts

> normalized per

> 1,000 words of text. I can see how to do it if the

> figures are even,

> i.e. if I have a corpus of 4,000 words and a

> frequency of 200,&#160;

> I would have a normalized figure of 50.

>

> But for mixed numbers, how would I calculate the

> following: For

> example if I have 2,646 instances of a certain

> kind of noun in a

> corpus of 55,166 how would I calculate the

> normalized figure per

> 1,000 words?

>

> Regards,

>

> Jenny

> Research Assistant

> Dept. of English & Communication

> City University of Hong Kong

>

>

>

--
Eric Atwell, Senior Lecturer, Language research group, School of Computing,
Faculty of Engineering, University of Leeds, LEEDS LS2 9JT, England
TEL: +44-113-2335430 FAX: +44-113-2335468 http://www.comp.leeds.ac.uk/eric