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question 1 - For the GPA around 3.50 to 3.70 Y= 5707(3.50...

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1a .summary output regression statistics multiple R 0.99 R Square 0.98 Adjusted R Square 0.97 Standard Error 536.32 Observation 7 ANOVA df SS MS F Sanificance F Regression 1 59941800.57 59941800.57 208.39 0 Residual 5 1438199.43 287639.89 Total 6 61380000 Coefficients Standard Error t Stat P-Value Lower 95% Upper 95% Lower 95.0% Upper 95.0% 14815.62 1234.86 12 0 11641.3 17989.93 11641.3 17989.93 X 5706.57 395.31 14.44 0 4690.4 6722.74 4690.4 6722.74 Residual output Observation Predicted Unit Y Residuals tandard Residuals 1 33419.03 380.97 0.78 2 29652.69 147.31 0.3 3 33932.62 -432.62 -0.88 4 31136.4 -736.4 -1.5 5 36614.71 -214.71 -0.44 6 27427.13 172.87 0.35 7 34617.41 682.59 1.39

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1a. X Y 3.26 33800 2.6 29800 3.35 33500 2.86 30400 3.82 36400 2.21 27600 3.47 35300 1b. X Y 3.26 33800 2.6 29800 3.35 33500 2.86 30400 3.82 36400 2.21 27600 3.47 35300 1d. Regression Equation : Y=5707x+14816
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Unformatted text preview: For the GPA around 3.50 to 3.70 Y= 5707(3.50) +14816 =34791 Y=5707(3.70) +14816= 35932 Thus, the range for the GPA around 3.50 to 3.70 is \$34791<predicted salary < \$35932 1c. The Correlation coefficient of R is 0.988 and the coefficient of determination of R squa 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 10000 20000 30000 40000 relationship of the GPA and the Starting GPA Starting Salary 2 2.2 2.4 2.6 2.8 3 3.2 3.4 3.6 5000 10000 15000 20000 25000 30000 35000 40000 f(x) = AD/ x + AD/ R² = AD/ e relationship of the GPA and the Starting GPA are is 0.977 3.8 4 g Salar 3.8 4 g Salar...
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question 1 - For the GPA around 3.50 to 3.70 Y= 5707(3.50...

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