I specifically need help with the steps of deriving part B, I'm very lost with it.

1. Consider the Simple Linear Regression (SLR) model yi = Bo+ Bili+ Ei, where the &is have zero mean, variance o and are uncorrelated. Sometimes it is convenient to write the SLR model in the following way: yi = Bo + Bili + Ei = Bo+ Bixi - Bix + Bix+ Ei = (Bo + Bix) +B1 (xi - x) tsi = at B1 (xi -x) +Ei :=0 where we have defined a := Bo + Bit, with x = (Et_, xi). (a) What is the meaning of the parameter o? (b) Derive the least-squares estimators for a and B1