You are working with the text-only light edition of "H.Lohninger: Teach/Me Data Analysis, Springer-Verlag, Berlin-New York-Tokyo, 1999. ISBN 3-540-14743-8". Click here for further information.
| You are working with the text-only light edition of "H.Lohninger: Teach/Me Data Analysis, Springer-Verlag, Berlin-New York-Tokyo, 1999. ISBN 3-540-14743-8". Click here for further information.
|
Table of Contents  Statistical Tests Non-parametric Tests Randomization Tests |
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| See also: rank randomization tests, distribution-free tests |   |
Most non-parametric tests are based on the principle of randomization. The idea behind this is that the probability of a particular value of a test statistic is calculated by evaluating all possible values of the test statistic. Since the number of possible values of a test statistic can be huge, even for small samples sizes, it is often impractical (or even impossible) to calculate the probability directly.
A possible strategy to reduce the amount of required computations is
called resampling: instead of calculating all possible combinations, one
could draw numerous random samples and calculate the probability from these
samples.
Last Update: 2005-Jän-25