The maintenance manager at a trucking company wants to build a regression model to forecast the time (in years) until the first engine overhaul based on four predictor variables: (1) annual miles driven (in 1,000s of miles), (2) average load weight (in tons), (3) average driving speed (in mph), and (4) oil change interval (in 1,000s of miles). Based on driver logs and onboard computers, data have been obtained for a sample of 25 trucks. A portion of the data is shown in the accompanying table.

Time	Miles	Weight	Speed	Oil
8.1	43.1	17	46	14
0.9	98.8	25	44	31
8.5	43.6	16	62	11
1.5	110.7	25	59	21
1.6	102.6	25	56	17
1.9	97.2	26	66	17
2.5	93.2	19	58	15
7.5	53.6	15	69	10
7.9	51.6	20	54	12
4.0	84.9	25	55	24
0.6	120.8	30	50	18
4.9	77	21	46	24
5.3	68.8	19	50	26
4.9	54.9	21	59	26
5.5	66.4	18	55	27
8.4	39.4	21	52	17
5.5	52.8	18	61	29
5.9	54.7	16	50	14
4.6	74.6	24	63	24
6.4	58.3	23	56	14
6.4	52.7	23	51	20
7.0	69	16	51	20
4.0	94.7	27	58	25
7.5	45.2	13	56	19
5.9	61.7	20	58	23

a.) Estimate the regression model. (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.)

b.) What is the predicted time before the first engine overhaul for a particular truck driven 65,000 miles per year with an average load of 19 tons, an average driving speed of 57 mph, and 18,000 miles between oil changes. (Do not round intermediate calculations. Round final answer to 2 decimal places.)