Question

Correlation, Causality, and Spurious Relationship

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Let’s discuss correlation and causality. To explain this, we can use an example of illness. When doctors see some symptoms in the patient, they may or may not be clear what disease the patient has. If doctors know what disease the patient has, they can cure the disease. However, often doctors treat symptoms without curing the disease. They are dealing with a correlation, not causality. Do you see the difference between correlation and causality? Next, let’s discuss spurious relationship. Can you give an example of it? In this thread, provide an example that illustrates the difference between correlation and causality. Provide also an example of spurious relationship. Make sure to come up with your own example. If it’s used by someone else, do not use it. Post early to get your original ideas in!

Answer 1

Example that shows difference between correlation and causality:

In causal relationship, one variable is proved to cause a particular effect. For example, suppose that a study reveals that as population increased in City X, crime rates also increased. Here, the relationship is correlational, as one increased, the other also increased. We cannot conclude that population increase is the reason for increase in crime rate. On the other hand, there are factors like poverty, unemployment, lack of education, inefficient law mechanisms, etc that would have led to the crime rate increase. They are causal factors.

Spurious relationship:

Here, two variables will seem to be associated, but they do not share a causal relationship and their association may be explained using an unseen third factor or mere coincidence. For example, suppose that a study revealed that the higher the number of religious institutions in a locality, the higher the rate of illiteracy. Here, both illiteracy and number of religious institutions may be a result of high population which is an unseen factor here. We cannot thus conclude that religious institutions cause illiteracy.