Common tests

On the preceding page, we described the concept of "test".

Below is a short list of some of the most popular tests. The distinction between "parametric" and "non-parametric" tests is adressed here.

 

 

 

SOME COMMON TESTS

 

 TEST

PURPOSE

 

Parametric

 

 

 

 

t tests

Testing mean(s) of 1 or 2 normal populations.

 

ANOVA

Testing equality of means of more than 2 normal populations.

 

Hotelling's T ² test

Testing equality of means of 2 multinormal populations.

 

Bartlett's test

Testing equality of variances of more than 2 normal populations.

 

Dunnett's test

post hoc test for comparing groups to a reference group.

 

Newman-Keuls test

post hoc test for fair pairwise multiple comparisons.

 

Fisher-Irwin test

Testing the identity of 2 Bernoulli populations.

 

 

 

 

Non parametric

 

 

 

 

Chi-square tests

 

 

 

 

Goodness of fit of a distribution to a sample.

 

 

Identity of 2 probability distributions.

 

 

Independence of two categorical variables.

 

 

 

 

 

Kolmogorov

Goodness of fit of a distribution to a sample.

 

Kolmogorov-Smirnov

Identity of 2 probability distributions.

 

Mann-Whitney

Identity of 2 probability distributions.

 

Kruskal-Wallis

Identity of 3 or more probability distributions.

 

Friedman

Identity of 3 or more probability distributions (matched samples)

 

 

See also two generic methods for building tests :

    * The Neyman-Pearson lemma .

    * Likelihood ratio tests  .

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