Question

6. True, False, Explain. Adding a variables to a regression that are highly correlated with the independent variables already included but not with the dependent variable will increase your chance of committing type II errors when conducting tests of statistical significance on the estimated coefficients.

Answer 1

True.

Type II errors occurs when you do not reject a false null hypothesis. When you add variables to a regression equation that are highly correlated with the independent variables but not with the dependent variable, then it means that the variable should not be added. This is because in regression the ideal variables which should be taken are corrrelated with the dependent variable and are not correlated with the independent variables. When variables are taken which are correlated with the independent variables, the problem of multicollinearity arises.

Here, you should reject those variables which are highly correlated with the independent variable but not with the dependent variable. Since, you are not rejecting it and instead accepting the variables, it results in Type II error when conducting test of statistical significance on the estimated coefficients.