Correlation Doesn’t Equal Causation: Crash Course Statistics #8

Today we’re going to talk about data relationships and what we can learn from them. We’ll focus on correlation, which is a measure of how two variables move together, and we’ll also introduce some useful statistical terms you’ve probably heard of like regression coefficient, correlation coefficient (r), and r^2. But first, we’ll need to introduce a useful way to represent bivariate continuous data – the scatter plot. The scatter plot has been called “the most useful invention in the history of statistical graphics,” but that doesn’t necessarily mean it can tell us *everything.* Just because two data sets move together doesn’t necessarily mean one CAUSES the other. This gives us one of the most important tenets of statistics: correlation does not imply causation.