Homework Answers
This is minitab generated output , which is correct.
Regression Analysis: viewers versus
salary
The regression equation is
viewers = 6.00 - 0.0241 salary
Predictor Coef SE Coef T P
Constant 6.001 1.295 4.63 0.004
salary -0.02412 0.03619 -0.67 0.530
S = 3.05523 R-Sq = 6.9% R-Sq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 1 4.148 4.148 0.44 0.530
Residual Error 6 56.007 9.334
Total 7 60.155
Unusual Observations
Obs salary viewers Fit SE Fit Residual St Resid
1 98.0 3.50 3.64 3.03 -0.14 -0.36 X
X denotes an observation whose X value gives it large leverage.
Predicted Values for New Observations
New Obs Fit SE Fit 95% CI 95% PI
1 5.86 1.19 (2.95, 8.77) (-2.17, 13.88)
Values of Predictors for New Observations
New Obs salary
1 6.00
Hence best predicted value is 5.9 million viewers.
This is minitab generated output , which is correct.
Regression Analysis: viewers versus salary
The regression equation is
viewers = 6.00 - 0.0241 salary
Predictor Coef SE Coef T P
Constant 6.001 1.295 4.63 0.004
salary -0.02412 0.03619 -0.67 0.530
S = 3.05523 R-Sq = 6.9% R-Sq(adj) = 0.0%
Analysis of Variance
Source DF SS MS F P
Regression 1 4.148 4.148 0.44 0.530
Residual Error 6 56.007 9.334
Total 7 60.155
Unusual Observations
Obs salary viewers Fit SE Fit Residual St Resid
1 98.0 3.50 3.64 3.03 -0.14 -0.36 X
X denotes an observation whose X value gives it large leverage.
Predicted Values for New Observations
New Obs Fit SE Fit 95% CI 95% PI
1 5.86 1.19 (2.95, 8.77) (-2.17, 13.88)
Values of Predictors for New Observations
New Obs salary
1 6.00
Hence best predicted value is 5.9 million viewers.
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