In statistics, a confounding variable or factor is that which affects both the dependent variable and other independent variables included in the model. In the model in the example, there are 3 explanatory or independent variables: income, tv, internet.
From the options listed, these are the ones that can possibly be the cause behind the variables in the model acting as confounding factors:
- People with lower incomes might not own tvs or computers (the opposite is not likely to generate a pattern).
- People with higher incomes likely will have high-speed internet access, which will lead to spending more time on-line.
- People who spend time at home on the internet never watch tv.
There are several ways in which the explanatory variables in the model can affect each other, apart from the dependent one.