To begin with, when we want to determine the relationship between two variables, we should use the proper correlation test. This choice depends on the type of data and the kind of relationship we want to explore. Pearson correlation is used when both variables are quantitative and continuous (for instance, exam scores), normally distributed, and meet the assumption of homoscedasticity. It helps identify the strength and direction of a proportional relationship. When data are ordinal (for example, surveys that ask about education level: primary < secondary < higher education) or not normally distributed, Spearman’s rho is used, since it analyzes monotonic relationships (not necessarily proportional) that don’t require strict assumptions. Finally, the Chi-square test is used to examine relationships between categorical variables, helping us determine whether frequency distributions differ from a theorical one by chance.