Comparing

Comparing means

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The following tables provide guidance to the selection of the proper parametric or non-parametric tests for a given data set.

1 Is there a difference ?
2 Sources
3 See also
4 External links

Is there a difference ?

**Ordinal and numerical measures**
1 group		N ≥ 30		One-sample t-test
		N < 30	Normally distributed	One-sample t-test
		N < 30	Not normal	Sign test
2 groups	Independent	N ≥ 30		t-test
		N < 30	Normally distributed	t-test
		N < 30	Not normal	Mann-Whitney U or Wilcoxon signed-rank test
	Paired	N ≥ 30		paired t-test
		N < 30	Normally distributed	paired t-test
		N < 30	Not normal	Wilcoxon signed-rank test
3 or more groups	Independent	Normally distributed	1 factor	One way anova
		Normally distributed	≥ 2 factors	two or other anova
		Not normal		Kruskal-Wallis one-way analysis of variance by ranks
	Dependent	Normally distributed		Repeated measures anova
	Dependent	Not normal		Friedman two-way analysis of variance by ranks

**Nominal measures**
1 group		np and n(1-p) ≥ 5	z-approximation
1 group		np or n(1-p) < 5	binominal
2 groups	Independent	np < 5	fisher exact test
	Independent	np ≥ 5	chi-square test
	Paired		McNemar or Kappa
3 or more groups	Independent	np < 5	collapse categories for chi-square test
	Independent	np ≥ 5	chi-square test
	Dependent		Cochran´s Q

Sources

Dawson-Saunders, Beth; Robert G. Gapp (1994). Basic & Clinical biostatistics. Lange medical book. ISBN 0-8385-0542-2.

Contents

Is there a difference ?

Sources

See also

External links