Can you kindly complete number 40. I have attached the bus data that will never

Question

Can you kindly complete number 40. I have attached the bus data that will never needed. thank you in advance!

Variables x, = Bus number Maintenance cost ($) Miles Bus manufacturer (Bluebird, Keiser, Thompson) X5 = Age xs-Bus type (diesel or gasoline) Xy- x,-Passengers Bus Number, Maintenance Cost, Age, Miles, Bus Type, Bus Manufacturer, Passengers, 135 120 Bluebrd 853 883 822 865 751 Diesel Diesel Diesel Gasoline Gasoline 503 Bluebird 759 8 870 Diese 5 780 Gasoline Gasoline 3 818 Gasoline Keiser 474 857 481 387 Kelser Bluebird 422 8 869 Gasoline 861 122 156 848 Diesel 845 Gasoline 885 Gasoline 838 Diasel 760 Diesel Bluebird Bluebird Bluebird Thompson Bluebird 474 561 357 741 Diesel 859 Gasoline 826 Gasoline Bluebird Bluebird Keiser Bluebird Bluebird 497 459 3 806 Gasoline 9 858 Diesel 2 785 Gasoline 875 Bluebird Bluebird 828 980 857 Diesel Gasoline Diesel 8 989 Bluebird 9 803 Diesel 819 821 Diesel Diesel 75 Bluebird 3 798 Gasoline 815 757 Diesel Diesel 751 493 10 1008 Diesel 9 631 Diesel 6 849 Diesel Diesel Diesal Bluebird Keiser Bluebird Thompson Bluebird 461 496 839 812

Explanation / Answer

       Model Summary
Model   R   R Square   Adjusted R Square   Std. Error of the Estimate
1   .055 .003   -.010   53.946

P VALUE COMES AROUND 0.626 which is greater than tabulated value hence cost of maintenance depends on age of bus.

I have done it on spss and contingency table is too large to paste here.

c) Null hypothesis:age of the bus, maintenance of cost and miles travelled not follow normal distribution.

AlternateHypothesis:age of the bus, maintenance of cost and miles travelled follow normal distribution.

significance level at 5%

after doing testing on spss

we found

age of the bus, maintenance of cost and miles travelled follow normal distribution.

Please Note: Im unable to paste tables from spss.

SUMMARY OUTPUT Regression Statistics Multiple R 0.05531 R Square 0.003059 Adjusted R Square -0.00972 Standard Error 308.1626 Observations 80 ANOVA df SS MS F Significance F Regression 1 22729.77 22729.77 0.239351 0.626048 Residual 78 7407206 94964.18 Total 79 7429936 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 656.8449 292.8347 2.243057 0.027731 73.85594 1239.834 73.85594 1239.834 X Variable 1 -0.31595 0.645811 -0.48924 0.626048 -1.60167 0.969758 -1.60167 0.969758

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