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Sometimes, with two variables, X and Y, you may have a causal relationship which means that a change in one variable, X, will cause a change in the other, Y, but there is no causal relationship in the other direction.

In such a case X is the independent variable and Y is the dependent. For example, if you are studying the age and height of young children, both variables increase together: the older the child is the taller it is. The causal relationship is clear: the age of the child affects its height. Even though there is a clear correlation, the height of a child does not cause it to become older.

Sometimes you can have two variables that are interdependent so that neither is independent. One possible example, from economics, is profit and capital investment. Higher profits should result in higher investment while higher investment should result in higher profits. Which one is the cause and which one the effect?

You can also have a situation where two variables, which are correlated, but neither is dependent on the other: both are dependent on some other variable. For example, in the UK, sales from ice cream vans are correlated with seaside swimming accidents. Eating ice cream does not cause swimming accidents, nor do people who have had swimming accidents console themselves with ice cream. These two dependent variables are associated with the [hidden] independent variable: warm weather (or temperature).

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Q: How can you find the independent and dependent variable?
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