Most types of hypothesis
test require that the population
conforms to a particular distribution, usually
the normal distribution. Where this is not
the case a nonparametric test can be used.
Nonparametric tests make no assumptions
about the type of distribution (although
they may require symmetry, or some other
property). The disadvantage is that nonparametric
tests are not as efficient; for a given
data set the nonparametric test will give
a higher pvalue.
Nonparametric Tests include:
Parametric
tests include ANOVA,
the t test,
the F test
and the chisquare
test.
