Please help me out with this question. I'm stuck and it's a practise problem I'm doing in preparation for my midterm.

5. Suppose K- : 10 + lxi + 63:, 6.- ~ N(0, 0'2), ei's are independent. for i = 1, . . . ,n. Let be and b] be the least squares estimates of g and 51, respectively. The residuals from this regression: 13:2}: b0b]_I. (a) We want to prove that the estimates 51 = E;1($i 5X3}: ) Eam- a2 ' are the minimizers of the least squares loss: :1 Loo. 6:) = Zhs b0 boa-)2- i=1 We will solve the two equations 6L(bo,b1) _0 6% _ 8L(b0!bl) :0 651 (i) Compute the two partial derivatives. (ii) Show that 8L5???\" = 0 yields the equation on = g Elli (bl is still unkow'n.) (iii) Substitue the expression for be in the equation a}? = 0, and show that this yields the equation E?=1(yg g 61(335 f))$ : 0. (iv) Explain why the above equation is equivalent to 2:10;,- 51(31 )) (3:,- ) 2 0, and obtain the formula for bl. (b) Derive EM]. Show your work. (Remember that ()0, bl are unbiased.)