The Chi-Square Test
[Table of Critical Values]
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?
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