I have a dataset with two variables that measure subjective self-definition of class. One is categorical (categories working class, middle class, upper class) while the other is quantitative (self-location in a 1-5 scale)
Is there a statistical test that I can perform to analyze the convergence and divergence between the two measures? I also have a relevant independent variable, so I could see wich dependent performs better in terms of the independent. What test could I use for that given that one is categorical and the other is quantitative?
Rodolfo - A categorical variable is one that has two or more categories, but there is no intrinsic ordering to the categories. For e.g., sex is a categorical variable having two categories (male and female) and there is no intrinsic ordering to the categories, while variables that are measured on a numeric or quantitative scale are quantitative e.g., Ordinal, interval and ratio scales etc.
Give your case - I think that Spearman correlation and Chi-square test will work. Spearman correlation tests for the strength of the association between two ordinal variables (does not rely on the assumption of normally distributed data) and Chi-square tests for the strength of the association between two categorical variables
- Badges
- Science topic