(at least 200 words) In multiple regression, we enter all our variables into the same model to test the associations between independent and dependent variables by also controlling for other potentially confounding variables. Why is it important to consider all the independent variables together in one model, rather than in separate simple linear regression models? What problems can occur when the independent variables are correlated with each other