A trainer collected the data in the following table for a random sample of 30 contestants in the Hilly Hundred (mile) bike race in Bloomington Indiana. He wants to use this information to predict times (in minutes) to complete the Hilly Hundred race. The trainer believes that the time to complete the race is affected by the age of the racer. This data is given below.

Age	Time		Age	Time
30	335		20	505
26	335		25	515
32	345		20	525
28	350		21	550
25	350		16	575
25	375		38	595
22	380		18	605
25	400		20	615
23	400		36	645
25	410		16	680
35	430		39	730
20	435		40	785
18	460		41	810
34	485		14	875
31	500		12	880

Create a scatter plot for these data. Comment on the observed relationship between Y and X.

Estimate an appropriate regression equation to predict the time to complete the race. Interpret the estimated regression coefficients.

Analyze the residual versus fit plot. Does this plot suggest that the regression equation is adequate? If not fit an alternative model until the results are satisfactory.

Use your final regression equation to predict the time to complete the race for a 31 year old runner.