Question: 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

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 following table were obtained.

a. Write the least squares prediction equation for y = total number of runs scored by a team in a season.
b. Interpret, practically, the Î² estimates in the model.
c. Conduct a test of H0: Î²7 = 0 against Ha: Î²7 d. Form a 95% confidence interval for Î²5. Interpret the results.

Standard Independent Variable B Estimate Error Intercept Walks (x) Singles (2) Doubles (x3) Triples (%) Home runs (s) Stolen bases () Caught stealing (x) Strikeouts (g) Outs () 3.70 34 49 -72 1.14 1.51 15.00 .02 03 .05 .19 .05 .05 .14 .01 .01 .14 -10 -.10

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a The least squares prediction equation is 370 34x 1 49x 2 72x 3 114x 4 151x 5 26x 6 14x 7 10x 8 10x ... View full answer

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