Use the partial SAS output provided below to the question. After the variable ERA has been excluded from the model, Model 3 was tested. The partial SAS print below provides information about model 3. The estimated regression line is Wins = 72.96 + 0.64 Saves + 15.30Runs -63.53 WHIP Obs Wins ERA Saves Runs Batting HRs WHIP 26 88 3.90 48 4.21 0.259 156 1.263 True or False: The estimated value of Wins is equal to 87.85 and the residual is equal to 0.004. Which means that this data point is almost on the regression line. (use 2 decimal places) True False

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Use the partial SAS output provided below to the question.
After the variable ERA has been excluded from the model, Model 3 was tested. The partial SAS
print below provides information about model 3.
The estimated regression line is Wins = 72.96 + 0.64 Saves + 15.30Runs -63.53 WHIP
Obs Wins ERA Saves Runs Batting HRs WHIP
26 88 3.90
48 4.21 0.259 156 1.263
True or False:
The estimated value of Wins is equal to 87.85 and the residual is equal to 0.004. Which means that
this data point is almost on the regression line. (use 2 decimal places)
True
False
Transcribed Image Text:Use the partial SAS output provided below to the question. After the variable ERA has been excluded from the model, Model 3 was tested. The partial SAS print below provides information about model 3. The estimated regression line is Wins = 72.96 + 0.64 Saves + 15.30Runs -63.53 WHIP Obs Wins ERA Saves Runs Batting HRs WHIP 26 88 3.90 48 4.21 0.259 156 1.263 True or False: The estimated value of Wins is equal to 87.85 and the residual is equal to 0.004. Which means that this data point is almost on the regression line. (use 2 decimal places) True False
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Step 1

Given statement

Estimated value of wins is equal to 87.85 and residual is equal to 0.004

Residual is the difference of actual value and the predicted value

Residual = actual – predicted =0.004

Difference is very very small

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