Compare the following two regressions

1) Yᵢ = B^0 + B^1Xᵢ + eᵢ
2) Yᵢ = B^0 + B^1(2Xᵢ) + eᵢ

(B^0= beta hat 0) (ᵢ is subscript i)

Equation i. is exactly the regression we’ve been working with thus far, so all the formulas we’ve derived thus far apply. In equation ii the independent variable has been multiplied by 2. How does this change, if at all, the values of B^0 , B^1, S² subscript B^1(sample variance of B hat 1) , R², and SSE?