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In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables. It commonly refers to the degree to which a pair of variables are related in a linear fashion.

One of the most common errors is the confusion between correlation and causation. In theory, these are easy to distinguish — an action or occurrence can cause another, or it can correlate with another. If one action causes another, then they are most certainly correlated. But just because two things occur together does not mean that one caused the other, even if it seems to make sense.

One way to get a general idea about whether or not two variables are related is to plot them on a scatter plot. A direct or positive relationship between two variable would produce a graph with the dots on the scatter plot tend to go from the lower left to the upper right it means that as one variable goes up the other variable tends to go up also. If the dots on the scatter plot tend to go from the upper left corner to the lower right corner of the scatter plot, it means that as values on one variable go up values on the other variable go down would be called an indirect or negative relationship.

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