In our field, education, it is important to develop interventions in student groups to compare improvements or setbacks. In related groups showing negative or positive trends, comparing differences in means before and after an intervention is not enough. For this reason, statistical tests are crucial for interpreting patterns. T-tests or analyses of variance, ANOVA, help determine whether those changes are statistically significant or not. For instance, a negative trend may reflect a decline in performance, while a positive trend suggests improvement. In the case of independent groups with bivariate trends, these statistical tests evaluate how two or more independent variables influence a dependent variable. All in all, by using these tools, researchers are able to determine whether observed differences in means and variances are statistically significant or due to chance, supporting this way the validity and reliability of conclusions in experimental and quasi-experimental designs applied to the observed groups.