Suppose a statistician built a multiple regression model for predicting the tota
ID: 3208470 • Letter: S
Question
Suppose a statistician built a multiple regression model for predicting the total number of runs scored by a baseball team during a season. Use the estimates to predict the number of runs scored by a team with 331 walks, 908 singles, 176 doubles, 28 triples, and 114 home runs.
Ind. Var estimate
Standard Error
Intercept 3.01
18.62
Walks (x1) 0.23
0.4
Singles (x 2) 0.43
0.03
Doubles (x 3) 0.63
0.03
Triples (x 4) 1.11
0.21
Home Runs (x5) 1.44
0.06
The model predicts .... runs for the season. (Round to the nearest whole number as needed.)
Ind. Var estimate
Standard Error
Intercept 3.01
18.62
Walks (x1) 0.23
0.4
Singles (x 2) 0.43
0.03
Doubles (x 3) 0.63
0.03
Triples (x 4) 1.11
0.21
Home Runs (x5) 1.44
0.06
Explanation / Answer
Answer to the question :
The linear regresison equation is
Weighted coefficients with values of variables:
Subbing the values we get =
Y=3.01+0.23*331+0.43*908+0.63*176+1.11*28+1.44*114
Y=775.7 runs for the season
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