A study of the top 75 MBA programs attempted to predict the average starting salary (in $1000's) of 6 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 18.1849 10.3336 1.76 0.0826 Tuition 1.47494 0.14017 10.52 0.0000 R-Squared Adj R-Squared 0.5972 0.6027 Resid. Mean Square (MSE) 532.986 Standard Deviation 23.0865 In addition, we are told that the coefficient of correlation was calculated to be r = 0.7763. Interpret this result. A) There is a fairly strong positive linear relationship between the amount of tuition charged and the average starting salary variables. B) There is almost no linear relationship between the amount of tuition charged and the average starting salary variables. C) There is a very weak positive linear relationship between the amount of tuition charged and the average starting salary variables. D) There is a fairly strong negative linear relationship between the amount of tuition charged and the average starting salary variables.

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A study of the top 75 MBA programs attempted to predict the average starting salary (in $1000's) of 6
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
18.1849
10.3336
1.76
0.0826
Tuition
1.47494
0.14017
10.52
0.0000
R-Squared
Adj R-Squared 0.5972
0.6027 Resid. Mean Square (MSE) 532.986
Standard Deviation
23.0865
In addition, we are told that the coefficient of correlation was calculated to be r = 0.7763.
Interpret this result.
A) There is a fairly strong positive linear relationship between the amount of tuition charged
and the average starting salary variables.
B) There is almost no linear relationship between the amount of tuition charged and the
average starting salary variables.
C) There is a very weak positive linear relationship between the amount of tuition charged
and the average starting salary variables.
D) There is a fairly strong negative linear relationship between the amount of tuition
charged and the average starting salary variables.
Transcribed Image Text:A study of the top 75 MBA programs attempted to predict the average starting salary (in $1000's) of 6 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 18.1849 10.3336 1.76 0.0826 Tuition 1.47494 0.14017 10.52 0.0000 R-Squared Adj R-Squared 0.5972 0.6027 Resid. Mean Square (MSE) 532.986 Standard Deviation 23.0865 In addition, we are told that the coefficient of correlation was calculated to be r = 0.7763. Interpret this result. A) There is a fairly strong positive linear relationship between the amount of tuition charged and the average starting salary variables. B) There is almost no linear relationship between the amount of tuition charged and the average starting salary variables. C) There is a very weak positive linear relationship between the amount of tuition charged and the average starting salary variables. D) There is a fairly strong negative linear relationship between the amount of tuition charged and the average starting salary variables.
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