In: Statistics and Probability
Please explain what the term collinearity (or multicollinearity in the multiple regression context) means. Does it affect our regression estimates (i.e., betas) or their variances? If so, please explain how? Does multicollinearity affect the chances of making either a Type I or Type II error? If so, how so?
Because
of consequence 2 there are chances of type 2 error. Since we are
going to accepet Ho every time because of large variance.