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A Study of the Top MBA Programs Attempted to Predict

question 101

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A study of the top MBA programs attempted to predict the average starting salary (in $1000ʹs) of graduates of the program based on the amount of tuition (in $1000ʹs) charged by the program and
The average GMAT score of the programʹs students. The results of a regression analysis based on a
Sample of 75 MBA programs is shown below: Least Squares Linear Regression of Salary
$A study of the top MBA programs attempted to predict the average starting salary (in $1000ʹs) of graduates of the program based on the amount of tuition (in $1000ʹs) charged by the program and The average GMAT score of the programʹs students. The results of a regression analysis based on a Sample of 75 MBA programs is shown below: Least Squares Linear Regression of Salary \begin{array}{lccr} \text { R-Squared } & 0.6857 & \text { Resid. Mean Square (MSE) } & 427.511 \\ \text { Adjusted R-Squared } & 0.6769 & \text { Standard Deviation } & 20.6763 \end{array} Interpret the coefficient of determination value shown in the printout. A) At \alpha = 0.05 , there is insufficient evidence to indicate that something in the regression model is useful for predicting the average starting salary of the graduates of an MBA program. B) We expect most of the average starting salaries to fall within \$ 20,676 of their least squares predicted values. C) We expect most of the average starting salaries to fall within \$ 41,353 of their least squares predicted values. D) We can explain 68.57 \% of the variation in the average starting salaries around their mean using the model that includes the average GMAT score and the tuition for the MBA program.$

$\begin{array}{lccr}\text { R-Squared } & 0.6857 & \text { Resid. Mean Square (MSE) } & 427.511 \\\text { Adjusted R-Squared } & 0.6769 & \text { Standard Deviation } & 20.6763\end{array}$

$A study of the top MBA programs attempted to predict the average starting salary (in $1000ʹs) of graduates of the program based on the amount of tuition (in $1000ʹs) charged by the program and The average GMAT score of the programʹs students. The results of a regression analysis based on a Sample of 75 MBA programs is shown below: Least Squares Linear Regression of Salary \begin{array}{lccr} \text { R-Squared } & 0.6857 & \text { Resid. Mean Square (MSE) } & 427.511 \\ \text { Adjusted R-Squared } & 0.6769 & \text { Standard Deviation } & 20.6763 \end{array} Interpret the coefficient of determination value shown in the printout. A) At \alpha = 0.05 , there is insufficient evidence to indicate that something in the regression model is useful for predicting the average starting salary of the graduates of an MBA program. B) We expect most of the average starting salaries to fall within \$ 20,676 of their least squares predicted values. C) We expect most of the average starting salaries to fall within \$ 41,353 of their least squares predicted values. D) We can explain 68.57 \% of the variation in the average starting salaries around their mean using the model that includes the average GMAT score and the tuition for the MBA program.$

Interpret the coefficient of determination value shown in the printout.

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Definitions:

True-False Exams

A type of assessment where participants decide if statements are correct or incorrect.

Recognition

Acknowledgment or appreciation of someone's effort, achievement, or status.

Recall

The act of remembering or recollecting past experiences or information.

Priming

A method for measuring implicit memory in which a person reads or listens to information and is later tested to see whether the information affects performance on another type of task.