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A Study of the Top MBA Programs Attempted to Predict

question 10

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A study of the top 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 and the average GMAT score of the program's students. The results of a regression analysis based on a sample of 75 MBA programs is shown below:  Least Squares Linear Regression of Salary  Predictor  Variables  Coefficient  Std Error  T  P  Constant 687.851165.4064.160.0001 Tuition 11.31972.197245.150.0000 GMAT 0.967270.255353.790.0003\begin{array}{l}\text { Least Squares Linear Regression of Salary }\\\begin{array} { l c c c c c } \text { Predictor } & & & & & \\\text { Variables } & \text { Coefficient } & \text { Std Error } & \text { T } & \text { P } \\\text { Constant } & - 687.851 & 165.406 & 4.16 & 0.0001 \\\text { Tuition } & - 11.3197 & 2.19724 & - 5.15 & 0.0000 \\\text { GMAT } & - 0.96727 & 0.25535 & - 3.79 & 0.0003\end{array}\end{array}

 TxG 0.018500.003315.580.0000 \begin{array}{lllll}\text { TxG } & 0.01850 & 0.00331 & 5.58 & 0.0000\end{array}

 R-Squared 0.7816 Resid. Mean Square (MSE)  301.251 Adjusted R-Squared 0.7723 Standard Deviation 17.3566\begin{array}{lccc}\text { R-Squared } & 0.7816 & \text { Resid. Mean Square (MSE) } & 301.251\\\text { Adjusted R-Squared } & 0.7723& \text { Standard Deviation } & 17.3566\end{array}

 Source  DF  SS  MS  F  P  Regression 376523.825510.984.680.0000 Residual 7121388.8301.3 Total 7497921.7\begin{array}{lllcccc}\text { Source } & \text { DF } & \text { SS } & \text { MS } & \text { F } & \text { P } \\\text { Regression } & 3 &76523.8& 25510.9 & 84.68& 0.0000 \\\text { Residual } & 71 &21388.8& 301.3 & \\\text { Total } & 74 & 97921.7 & &\end{array}


Cases Included 75 Missing Cases 0

The global-f test statistic is shown on the printout to be the value F=84.68F = 84.68 . Interpret this value.


Definitions:

Pareto Efficient

A situation where no individual or preference criterion can be better off without making at least one individual or preference criterion worse off.

Initial Endowment

The initial allocation of resources, money, or goods that an individual, institution, or country possesses.

Pareto Optimal

An allocation of resources from which it is impossible to reallocate to make any one individual better off without making at least one individual worse off.

Utility Function

A mathematical representation used in economics to model the satisfaction or happiness a consumer derives from consuming goods and services.

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