Linear Regression

Could you please assist me with this question? I gathered the data in the first picture, but struggle with the questions on the 2nd picture. I would be very grateful if you can help me.

8. n IMS (xinyi ) . Exi a ) bo = i =1 2 X i 2 - xi ) 1 =1 1=1 = 75 739 . 368, 886-9213. 112. 2967 - 60375. 45 _ 2. 1140 49287 120. 75739 - (2867) 2 285591 6, = n . E ( X , . y : ) - EXi . 2 9 : REL n Ex, 2 - (2 x ; ) 2 i =1 120.9213. 112- 2967 368. 386 = 110 88.678 - 0.038 827127 120 . 75739 - ( 2967)2 285591 J = 2 . 1 1 40 4 9 28 7 + 0 . 0 3 8 8 2 7 127 x SPA ACT b ) r= no; Exiti - Exi . = 1105 573, 44- 109 4484. 762 = 0.26 9481803 285 591 . 592. 654 444 irl indicates that ACT& GPA have a little if any linear correlation . c ) y = 2 . 1 14 0 4 9287 + 0.03 8827127 - 30 5 = 3. 27 8863097 2) The change is the slope.5. Refer to \"Grade point average\" data in HWl {\"CHDIPRIQ\" ). {a} Set up the ANOVA table {b} What is estimated by MSR in your ANOVA table? by MSE? Under what condition do MSR and M SE estimate the same quantity? {c} Conduct an F test of whether or not .31 = . Control the a risk at Illl. State the alternatives, decision rule, and oonelusion. {d} What is the absolute magnitude of the reduction in the variation of Y when X is introduced into the regression model?I What is the relative reduction? What is the name of the latter measure