Question

# The following data provide the starting salary for students who recently graduated from a local university...

The following data provide the starting salary for students who recently graduated from a local university and accepted jobs soon after graduation. The starting salary, grade-point average (GPA), and major (business or other) are provided.

 SALARY \$29,500 \$46,000 \$39,800 \$36,500 GPA 3.1 3.5 3.8 2.9 Major Other Business Business Other SALARY \$42,000 \$31,500 \$36,200 GPA 3.4 2.1 2.5 Major Business Other Business

1. Using a computer, develop a regression model that could be used to predict starting salary based on GPA and major.
2. Use this model to predict the starting salary for a business major with a GPA of 3.0.
3. What does the model say about the starting salary for a business major compared to a non-business major?
4. Do you believe this model is useful in predicting the starting salary? Justify your answer using information provided in the computer output.

 Coefficients SE T-stat P-value Intercept 24328 9025 2.696 0.0543 GPA(X1) 3027 3234 0.936 0.4023 Major(X2) 6684 3594 1.86 0.1364

Linear model can be written as

Y' = 24328 + 3027*X1 + 6684*X2

b,

For a student with GPA= 3

with business major X1 = 3 and X2 = 1

Y' = 24328 + 3027*X1 + 6684 * X2

by substituiting X1 and X2.

Y' = 24328 + 3027 * 3 + 6684*1

=40093

c.

Salary of the business major is high when compared to no business major as the predicted value shows \$40093.

d.

 df SS MS F value P(>f) Regression 2 137598209 68799105 4.386 0.098 Residuals 4 62738933 15684733 Total 6 200337142

P-value of regression is 0.098(>0.05)

We can conclude that there does not exist any significant relationship between the variables.

R^2 = SSR/SST = 0.6868(68.68%)

Regression model is somehow only partially useful to predict starting salary.