Question

Construct a linear regression model that uses a person's BMI to predict their LDL level. Round the model's coefficients to three decimal places; add trailing zeros as needed.

The regression model is ŷ = + x

BMI    LDL

20.14   213   ""
19.62   88   ""
22.26   174   ""
29.04   121   ""
22.14   124   ""
20.48   99   ""
38.45   114   ""
23.8   122   ""
20.82   112   ""
17.27   67   ""
26.46   108   ""
34.45   94   ""
20.37   69   ""
25.61   77   ""
33.89   120   ""
28.17   84   ""
33.21   86   ""
20.34   77   ""
29.4   201   ""
26.33   196   ""
29.71   179   ""
29.46   140   ""
20.52   117   ""
21.65   117   ""
17.84   87   ""
26.6   78   ""
28.21   159   ""
27.96   113   ""
36.75   155   ""
21.79   85   ""
32.38   90   ""
33.27   104   ""
30.95   154   ""
26.45   114   ""
27.86   156   ""
27.08   103   ""
32.28   145   ""
25   135   ""
26.13   123   ""
29.83   170   ""

Answer 1

The filted Reguession equation is gives as a Wis A minum where the fitted values of a Euß are obtained using principle of heast squares her by minimising error sume of squares Zei?ie. 1 min E = mis {ei²= Elyi-ko - pri) ? The nesinal eq ns for solning & and ß are : © Sigi--pri) = 0 @ Exi Cy'- x-px) = 0 On sonning ♡ and @ we get Å= {cui-a cyi- g) scxi-x)2 cs Scared years and  = 1 + $ *

Plovo , B = 416 41 • 202 5 : 1:4654 41 44 • 4386 18 how, y = 121.75 od X= 264 594 25 °, d = 121.15 - tr•46.5чч x 26•34425) 4 = 82-70ч) Sо, алайд Roulim ta also i aa ad ; у - 82» 330 + 1*46 5 x (cs Scanned with CamScanner