This kind of article is right up my alley. It's important to understand the differences and how you can move from correlation to actual causation.
From the page: "One of the most common mistakes people make when looking at data is to jump to conclusions about the data. We all live in a world of cause and effect. It is only natural that when we see data that appears to show cause and effect, we assume that it does. But it often doesnâ€t. This article shows the difference between cause and effect relationships and correlated data."
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