The assumption of equal intervals says that all distances between adjacent answer categories are equal in the repondents’ perception. This assumption is an attempt to justify treating ordinal variables as if they were metric variables. Doing so enables one to compute means, standard deviations and Pearson correlations on ordinal variables. This is simpler than using more appropriate techniques. Assumption of Equal […]
If you’d like to know if 2 groups of people score similarly on 1 dichotomous variable, you’ll compare 2 independent proportions. There’s two basic ways to do so: the chi-square independence test and; the z-test for 2 independent proportions. These tests yield identical significance levels but the z-test approach allows you to compute a confidence interval for the difference between […]
Measurement levels refer to different types of variables that imply how to analyze them. Standard textbooks distinguish 4 such measurement levels or variable types. From low to high, these are nominal variables; ordinal variables; interval variables; ratio variables. The “higher” the measurement level, the more information a variable holds. The simple flowchart below shows how […]
