The selection of the correct test requires knowlegde of the data's nature and the kind of question.
{| table title="Statistical test" !Parametric methods|||| |- |Kind of study||Test||Conditions |- |Cross sectional study||t-Test for unpaired samples||s & n, nearly Gaussian distribution |- |||ANOVA||s & x*n |- |||F-Test||s & n |- |- || |- |Longitudinal study||t-Test for paired samples||2*s |- !Non-parametrical methods|||| |- |Kind of study||Test||Conditions |- |Cross sectional study||Kolmogoroff-Smirnoff-Test||s & n (2 groups) |- |||Kruskall-Wallis-Test||s & n (3 levels) |- |||U-Test (Mann-Whitney-Test)||s & n (2 levels) |- |||Wald-Wolfowitz-Test||s & n (2 groups) |- |||Chi-Quadrat-Test||x*x (frequencies) |- |||Fisher-Yates-Test||x*x (frequencies, 2 groups, respectively) |- |- |- || |- |Longitudinal study||Wilcoxon-Test||2*s |- |||Paired sign test||2*s |- |||Friedman-Test||x*s, x>=3 |}
Legend: s: continuous data, n: nominal data, x: frequency.
Examples: s & n: Continuous data, nominal criterion; 2*s: Two groups with continuous data
Web Link
SISA: Simple Interactive Statistical Analysis
