Fit a multiple linear regression on Maintenance cost using age and miles. Copy a
ID: 3246426 • Letter: F
Question
Fit a multiple linear regression on Maintenance cost using age and miles. Copy and paste the Excel output here and use the output to answer the following questions.
List the coefficient of determination and interpret the value.
Conduct a global test on the model: List the hypotheses (null and alternative) and State the conclusion for global test of the model.
Conduct individual tests on the coefficients: state the conclusion for each coefficient.
I have the first part, can anyone help with the last 3 questions.
Maintenance Age Miles 329 7 853 503 10 883 505 10 822 546 8 870 433 9 848 561 12 838 357 8 760 329 3 741 489 9 858 455 7 828 503 8 857 380 9 803 432 6 819 478 6 821 471 9 815 444 2 757 493 10 1008 452 9 831 461 6 849 496 8 839 469 8 812 442 9 809 459 11 859 457 2 815 462 6 799 570 9 844 390 2 792 381 9 882 501 7 874 392 5 774 441 1 823 448 8 790 468 4 800 478 6 830 515 14 895 504 9 842 392 8 851 423 10 835 410 7 866 477 2 802 540 11 847 450 6 856 390 5 799 424 4 827 433 7 817 428 7 842 494 7 815 458 4 817 493 6 816 476 10 827 403 4 806 492 10 836 426 4 757 466 10 865 359 7 751 427 5 780 474 9 857 382 3 818 422 8 869 474 10 845 558 10 885 497 10 859 459 8 826 355 3 806 436 2 785 514 11 980 406 3 798 414 4 864 439 9 832 369 5 842 469 9 775 432 6 837 467 7 827 411 6 804 504 8 866 529 4 846 396 6 784 475 9 816 337 6 819 449 4 817Explanation / Answer
List the coefficient of determination and interpret the value.
= 0.27522
27.522 % of the variation in the depndnet variable is explained by the model
Conduct a global test on the model: List the hypotheses (null and alternative) and State the conclusion for global test of the model.
since p-value of F = 0.00000415 < 0.05
we reject the null and conclude that the model is significanr
Conduct individual tests on the coefficients: state the conclusion for each coefficient.
if p-value is less than 0.05 ,we reject the null hypothesis ,and conclude that the variable is significant
here both Age and Miles have p-value less than 0.05
hence both are significant
SUMMARY OUTPUT Regression Statistics Multiple R 0.52461784 R Square 0.275223878 Adjusted R Square 0.256398525 Standard Error 46.29465279 Observations 80 ANOVA df SS MS F Significance F Regression 2 62666.38198 31333.191 14.61985157 4.15E-06 Residual 77 165026.0055 2143.19488 Total 79 227692.3875 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 105.8990967 112.9472829 0.93759756 0.351382895 -119.008 330.8059 -119.008 330.8059 Age 6.165378157 2.219590975 2.77770915 0.006872801 1.745608 10.58515 1.745608 10.58515 Miles 0.362879436 0.144749991 2.50693926 0.014285035 0.074645 0.651113 0.074645 0.651113Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.