Pearson's correlation is based on the numerical measurement of two values, which can increase or decrease following a straight line. To apply this test correctly, it is necessary that the data present a normal distribution, that is, that they follow a pattern similar to the Gaussian bell. On the other hand, Spearman's rho is used when the data do not follow a normal distribution or when working with rankings or ranges. This test makes it possible to analyze numerical data and verify whether values increase or decrease consistently, although not necessarily in a linear fashion. Finally, the chi-square test is applied to qualitative variables and although it is quantitative, its main function is to identify whether two groups or categories are related. Therefore, when choosing the appropriate test, it is essential to take into account whether the level of measurement is numerical or categorical and in the case of normality whether these have normal or constant patterns. Both conditions are key to finding relationships between variables and making informed decisions within an investigation.