The Chi-Square Test
[Table of Critical
In combination with discussion of fundamentals,
note in the above especially the concepts of Model,
Categorical (Count) Data, Degrees of
Freedom, & Significance Level.
Consult the Table of Critical Values for a
discussion of that concept.
HOMEWORK: The Power of a
statistical test is related to the sample size
necessary to detect what may be a small but
significant deviation from expectation. The numbers
presented show that with n = 50, an outcome of
29:21 is insufficient to demonstrate a
significant deviation from equality. This begs the
question, what outcome would be significant,
or stated another way, what is the minimum
deviation from expectation that could be
detected with a sample of 50? From the formula above,
and given a critical value of X2
= 3.84, show algebraically what
that minimum deviation is for this simple case.
If you are feeling energetic, use Excel
to calculate a table of the range of such values
over a range of sample sizes 50, 100, 200, 500, and
1000. What does this tell you about the importance of
sample size in testing biological hypotheses?
Customization of the Chi-Square Test for Nucleotide data
Box © 2013
Sinauer Associates; Text material © 2022 by Steven M. Carr