You provided a clear and well-organized explanation of when to use each test. I especially liked how you mentioned homoscedasticity in relation to Pearson's correlation, which is often ignored. The question that comes to mind: When the data violates both normality and homoscedasticity, would you consider transforming the data (such as a log conversion) before using the Pirson test, or would you go directly to Spearman Rho? It would be interesting to hear your views on when it's better to adjust the data than to change the parametric method. Amazing!