Pearson's correlation coefficient is used when we have two continuous variables with a regular distribution. It analyzes the linear correlation between the two variables, that is, whether they increase or decrease proportionally. It is crucial that the data fit the normal range and are at the interval or ratio level. In contrast, Spearman's rho is optimal when the data are not normal or ordinal. Instead of using the original values, it is based on ranges, making it resistant to extreme values and beneficial for monotonic relationships (which always increase or decrease, even if not linearly).Finally, the Chi-square test is used when working with categorical variables. It allows us to verify whether there is a significant correlation between the categories of two variables by comparing the detected frequencies with the projected ones. It is essential to identify the measurement level of our variables and verify whether they meet certain assumptions in order to select the appropriate analysis and obtain valid results.