The **critical value** of a
statistical test is the value at which, for any per-determined **probability
(***p*), the test indicates a result that
is less probable than **p**. Such a result is
said to be **statistically ****significant
**at that probability. Under most circumstances in
experimental biology, the pre-determined **p ****= 0.05**,
which indicates that the result that would happen by chance
only once in twenty trials. Under some circumstances, **p =
0.01** or **0.001**, that is, the result would occur
only once in a hundred or a thousand trials; **p**
may also be reported as the upper bound of the probability of
the observed result.

For a typical**test of genotype
frequencies in a two-allele mode**l, there are *three
*possible genotypes but only *one ***degree of freedom**, because
the value of **q** automatically determines **p =****
****(1 - q)**. For example, if a chi-square
comparison of the expected versus observed numbers of
genotypes in a two-allele model (**d**** ****=
1**) gave a value of 2.0, the result would *not *be
significant, and would be reported as **p**_{[0.05,
df=1]} = 2.0^{ns}, where **ns
**means *not significant*. A result of 5.0 would be
reported as significant at **p
< 0.05**, a result of 8.0 significant at **p <
0.01**, and a result of 20.0 as **p <** or <<
**0.001**. The last three values might also be marked as
5.0*****, 8.0******, and 20.0*******, to indicate the level of
significance.

For a typical

Table rearranged from © 2013 by Sinauer; Text material © 2019 by Steven M. Carr