Question

What is one an example from your own academic or professional experience where correlation has been confused with causation? What other variable(s) might explain the apparent relationship? Knowing what you know now about correlation and causation, how would you interpret the apparent relationship between the variables in your example?

Answer 1

Correlation is a measure of degree and direction of relation between two variables. It describes the relative change in one variable when there is a change in the other. The range of the correlation is -1 to 1. -1 represents a high degree of negative relationship (i.e. both variables move in different direction, increase in one variable results in decrease in the other and vice-versa). 0 represents no correlation, i.e. the two variable are not at all related. . +1 represents a high degree of positive relationship (i.e. both variables move in the same direction, increase in one variable results in increase in the other or decrease results in decrease ). Correlation between two variables might exist but this does not necessarily mean that one variable is dependent on the other. This dependency of one variable on the other is measured by Causation. The term itself implies that one variable is the cause of other.

Now consider this. People in the States spend more in shopping when it is cold and less when it is hot. There is a very high degree of correlation between the seasons and the amount spent on shopping. But this does not imply that this increase/decrease is caused by seasons. Though they are related but one is not being explained by the other. May be we can say that the winter season coincides with the holidays, for instance Christmas or New Year, and also with the sales during the season. This holiday or the sale can be a Cause of the spending on shop but not the season. This dependency between the amount spent on shop and holiday/sale can be studied through Causation, one being the cause for the other. Hence we can see that, though the season and the amount spent in shop is correlated, one is not a cause for the other.