Tom is considering buying a used car but he is concerned about the repair costs. To investigate how repair cost is related to the age of a car, he has collected the following data:

Repairs (y) $. Age(x) month

327.67. 110

376.68. 113

392.52. 114

443.14. 134

342.62. 93

476.16. 141

324.74. 112

338.98. 114

433.45. 110

526.37. 142

362.42. 96

448.76. 139

335.27. 89

350.94. 93

291.81. 91

467.80. 109

474.48. 138

354.15. 83

420.11. 100

416.04. 137

Note: Round all of your numerical answers below to three decimal places.

(a)Fill out the blanks in the regression below that Tom has estimated based on the least squares approach:

= _______________ + _______________ xAge

(b)Interpret the economic implication of the estimated coefficient on "Age" in Part (a).

(c)The standard error of the estimate of the simple regression model is __________.

(d)The regression result indicates that age of the car ____________ (has or does not have) explanatory power for repair cost at the 5% significance level because thep-value of the coefficient is ___________ (less or greater) than 5%.

(e)The regression result suggests that the model can explain __________% of the changes in repair cost.