I am wondering if there is a reference for the Pearson's chi-squared test suitable for technically-sophisticated audience that simply presents when the test (in its various forms) is appropriate and how it is carried out (i.e., construction of the test statistic, etc.)
The reason I ask is that I am using Pearson's chi-squared tests for independence (in a simpe 2×2 contingency table) and homogeneity in a paper that describes some experimental results in physics. The tests are used to confirm the "minor" phenomena and are thus relegated to the footnotes. However, I would still like to provide a reference in case the audience wants to look up the test and confirm my claims (either on my data or their own data).
Many of the stats books that I looked at either don't discuss Pearson's chi-square, or have a very limited discussion of it (I saw relegated to a homework problem in one of the books I looked at). However, I think that "A Guide to Chi-Squared Testing" by Greenwood and Nikulin is very hard to read. Is there a better text? Perhaps a chapter or two in a good textbook? Any suggestions?
One possible reference might be to section 2.4 of Alan Agresti's "An Introduction to Categorical Data Analysis". It might be worth checking if that has enough of what you need.
: Agresti, A. (2007),
An Introduction to Categorical Data Analysis,
John Wiley & Sons Hoboken, NJ