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A Study of the Top 75 MBA Programs Attempted to Predict

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A study of the top 75 MBA programs attempted to predict the average starting salary (in $1000's) of graduates of the program based on the amount of tuition (in $1000's) charged by the program. The results of a simple linear regression analysis are shown below: Least Squares Linear Regression of Salary Predictor
 Variables  Coefficient  Std Error  T  P  Constant 18.184910.33361.760.0826 Size 1.474940.1401710.520.0000\begin{array} { l r c c l } \text { Variables } & \text { Coefficient } & \text { Std Error } & \text { T } & \text { P } \\ \text { Constant } & 18.1849 & 10.3336 & 1.76 & 0.0826 \\ \text { Size } & 1.47494 & 0.14017 & 10.52 & 0.0000 \end{array}

R-Squared 0.6027\quad 0.6027 \quad Resid. Mean Square (MSE) 532.986532.986
Adjusted R-Squared 0.59720.5972 Standard Deviation 23.086523.0865 The model was then used to create 95% confidence and prediction intervals for y and for E(Y) when the tuition charged by the MBA program was $75,000. The results are shown here: 95% confidence interval for E(Y) : ($123,390, $134,220) 95% prediction interval for Y: ($82,476, $175,130) Which of the following interpretations is correct if you want to use the model to estimate E(Y) for all MBA programs?


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A skincare treatment lasting approximately 60 minutes, focused on improving the health and appearance of the skin on the face.

Monopolistic Competition

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Break-even Points

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