Question

If two variables are observed to have a relationship, must it be Cause-Effect?

Describe and give an example of what it means to say variables may be confounded.

Answer 1

1) If the occurrence of an event causes the other, a Cause-Effect relation exists. The first event causing the other is called the cause and the second event is called the effect. The correlation or the relationship between the two variables does not imply Cause-Effect.

In the majority of cases correlation, exist because of the coincidences. Since it seems that one factor influence the other, it not always means that it actually does.

Lemonade sales are correlated with murder in New Delhi (Study)

As the sales of lemonade goes up and down, so do the number of murders.

Does the sale of lemonade cause the murders?

The answer is no. If two things are correlated, it doesn’t mean one causes the other.

Correlation does not mean cause-effect in our example.

2)

For example, if you are conducting research on whether doing less cardio exercise leads to weight gain. Thus lack of cardio exercise is your explanatory variable and weight gain is your response variable. Another variable that also has an effect on your response variable is the Confounding variable. Here the two variables are cofounded by another variable which is age, which can be big reason for weight gain and less physical exercise.