Question

II. Consider the following data for 15 subjects with two predictors. The dependent variable, MARK, is the total score for a subject on an examination. The first predictor, COMP, is the score for the subject on a so called compulsory paper. The other predictor, CERTIF, is the score for the subject on a previous exam. Fit a model for predicting y (MARK) from x1(COMP) and x2 (CERTIF) COMP 111 COMP CERTIF 117 92 CERTIF Candidate MARK 68 645 46 10 556 634 59 12 637 94 Candidate MARK 476 457 540 551 575 698 545 574 130 118 390 107 98 150 118 91 118 1 14 562 560 109 110

Candidate	MARK	COMP	CERTIF
1	476	111	68
2	457	92	46
3	540	90	50
4	551	107	59
5	575	98	50
6	698	150	66
7	545	118	54
8	574	110	51
9	645	117	59
10	556	94	97
11	634	130	57
12	637	118	51
13	390	91	44
14	562	118	61
15	560	109	66

Answer 1

EXCEL (Data Analysis) output: SUMMARY OUTPUT Regression Statistics Multiple R 0.763629631 R Square 0.583130213 Adjusted R Square 0.513651915 Standard Error 54.46317078 Observations 15 ANOVA Significance F 0.005248105 Regression Residual Total 2 12 14 SS MS F 49791.15634 24895.58 8.392984 35594.84366 2966.237 8 5386 Intercept COMP CERTIF Coefficients Standard Error Stat p-value Lower 95% Upper 95% 124.0641189 113.2422102 1.095564 0.294771 -122.6694613 370.7976991 3.512036508 0.897465883 3.913281 0.00206 1.55662633 5.467446686 0.834632387 1.134643763 0.73559 0.476113 -1.637543998 3.306808773 The regression equation is = 124.0641+3.5120x4 +0.8346x).