Use scatterplots to explore causes

Scatterplots are great tools for exploratory data analysis, which is the term statisticians use to describe looking around in a set of data for hypotheses to test.

Analysts like to use scatterplots when searching for causal relationships, where one variable is affecting the other. As a general rule, the horizontal x-axis of the scatterplot represents the independent variable (the variable we imagine to be a cause), and the vertical y-axis of a scatterplot represents the dependent variable (which we imagine to be the effect).

You don’t have to prove that the value of the independent variable causes the value of the dependent variable, because after all we’re exploring the data. But causes are what you’re looking for.