How to Think about Correlation?
The article&#x27;s question: &quot;Why are correlations meaningful?&quot; Here&#x27;s a simplified answer.<p>Correlations are meaningful because they indicate how strongly variables can predict other variables, in some circumstances. This is valuable because some variables are easier to use than others.<p>A positive correlation between two variables means they tend to move in the same direction (relative to their mean).<p>A negative correlation between two variables means they tend to move in opposite directions.<p>A strong correlation between two variables means that they tend to change in much the same kinds of relative magnitudes, and also that either variables can be used to generally predict the other.<p>A weak correlation between two variables means that the two variables tend to change in somewhat the same kinds of relative magnitudes, sometimes with some kinds of exceptions, and also that either variable can be used to somewhat predict the other.<p>Thus a strong positive correlation means that variables can predict each other effectively, and also move in the same direction. This is especially valuable for projects where one variable is easy to obtain, yet the other variable is hard to obtain.<p>And it turns out that a strong positive correlation can be a good place to hunt for possible causality, such as hunting for something that causing both variables to change together. However, correlation doesn&#x27;t imply causation.<p>A strong positive correlation can be good evidence that a hypothesized causality is likely to be true. For example an experiment can test if X causes Y, by varying X, and discovering that X and Y tend to change together.<p>Edit: the replies below are great-- thank you-- well worth reading. I&#x27;m editing my post to make it clearer that it&#x27;s a simplified answer, and to add suggestions by the replies.