Question

Q2: (15 pts) Runs scored in baseball. In Chance (Fall 2000), statistician Scott Berry built a multiple regression model for predicting total number of runs scored by a Major League Baseball team during a season. Using data on all teams over a 9-year period (a sample of n 234), the results in the next table were obtained. Also, R2 was 0.720. Use (to.os (224) ~1.645, to.025 (224) 1.96, t0.os (8)1.86, or to.025 (8) 2.306) Use ( Fo.05 (2,224) 3.00, Fo.025 (2,224)3.69, Fo.05 (224,2) 19.5, or Fo.025 (224,2) 39.5) Intercept Walks Singles Doubles Triples Home Stolen Caught Strikeouts Outs x1 Runs s 9 Bi 3.7 0.24 0.39 0.42 1.6 1.62 0.16 -0.12 -0.15-0.12 STANDAR B EARLCE 10 0123 00.04 032 0.14 0.12 0.01

(a) Test the overall model adequacy at alpha = 0.05. Interpret the results.

Answer 1

β	SE	t = β/SE	t Critical (0.05, 9) =	2.262157	Significant?
3.7	10	0.37			No
0.24	0.12	2			No
0.39	0.05	7.8			Yes
0.42	0.1	4.2			Yes
1.6	0.4	4			Yes
1.62	0.04	40.5			Yes
0.16	0.01	16			Yes
-0.12	0.14	-0.85714			No
-0.15	0.12	-1.25			No
-0.12	0.01	-12			Yes

The overall model is significant at α = 0.05.