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?

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#### Best Answer

One possible reference might be to section 2.4 of Alan Agresti's "An Introduction to Categorical Data Analysis"[1]. It might be worth checking if that has enough of what you need.

[1]: Agresti, A. (2007),

*An Introduction to Categorical Data Analysis,*

John Wiley & Sons Hoboken, NJ