Ordinary Least Squares (OLS) & the R2 and the adjusted R2.

Consider the following model: ???? = ???????? + ????, known as the Classical Linear Regression Model (CLRM), where y is the dependent variable, X is the set of independent variables, ???? is the vector of parameters to be estimated and ???? is the error term. c)In what sense can decisions based upon the OLS framework be regarded as rational? What are the warnings of using the OLS approach for hypothesis testing? Discuss. d)Present and discuss the R2 and the adjusted R2. Why should the adjusted R2 be regarded as a “soft rule”? Discuss. Note: 1?