Consider the following simple linear regression model.
\(yi = \beta1 + \beta2xi + ei, i = 1,..., n\)
PART I: We are trying to find the ordinary least squares (OLS) estimators for 1 and 2 which we will denote as b1 and b2.
(a) Write down the function that you are minimizing.
(b) What are the OLS normal equations (1rst order conditions)?
(c) Derive OLS estimators, b1 and b2, from the normal equations.