The one-size-fits-all unwitting assumptions (Part 1)
In the echoing chambers of research and analysis, the choice of statistical tools is not just a matter of convenience; it's a pivotal decision that can shape the very essence of our discoveries. Unfortunately, it is often in this crucial choice that many falter, unwittingly assuming that Pearson's correlation coefficient is a ‘one-size-fits-all’ solution. It is a grave misconception; a shortcut that threatens to undermine the integrity of our findings. Pearson correlation, or simply "r," is a statistical measure that quantifies the strength and direction of a linear relationship between two continuous variables. It ranges from -1 to 1, where: -1 indicates a perfect negative linear relationship (as one variable increases, the other decreases linearly). 0 indicates no linear relationship. 1 indicates a perfect positive linear relationship (as one variable increases, the other increases linearly). This means If you were to graph the data points, a linear relationship w...