To measure the association between two continuous variables, we generally use the correlation coefficient. Its drawbacks and its qualities are well known.
When we want to characterize the association for nominal variables, the correlation coefficient is not suitable. We must use other indicators. The most widespread is certainly the chi-square test, it enables to evaluate the absence of relation. We see in this tutorial that other measures are available. We show how to use them with TANAGRA.
Keywords: association between nominal variables, contingency table, chi-square test, tschuprow's t, cramer's v, asymmetrical association, pre measures (proportional reduction in error), goodman and kruskal's tau, theil's u, partial association, partial theil's u
Components: Contingency Chi-Square, Goodman-Kruskal Tau, Theil U, Partial Theil U, Discrete select examples
Tutorial: en_Tanagra_Measures_of_Association_Nominal_Variables.pdf
Dataset: fuel_consumption.xls
Reference:
D. Garson, « Measures of association », in Statnotes : Topics in Multivariate Analysis.
