You are a faculty advisor working with a student who is undecided about being an
ID: 3310987 • Letter: Y
Question
You are a faculty advisor working with a student who is undecided about being an accounting major below are the results of analysis of some sample data for the following variables
y = starting salary (thousands of dollars)
x1 = sex (1=male)(0=female)
x2 = gpa
x3 = age at graduation
x4 = major (accounting=1)(other =0)
a. Write the estimated regression equation?
b. Interpret the coefficient of AGE variable?
c.Interpret the coefficient of the major variable?
D.Interpret the explanatory power of the model numerically specific?
e. Is there evidence that accounting Majors will have higher starting salaries than other majors? Use alpha = .05
f. What is the difference in the predicted starting salary for a male accounting major with a GPA = 2.5 who graduates at 23 and a female accounting major with gpa = 2.5 who graduates at 23?
g construct and interpret a 90% confidence interval for the slope coefficient associated with GPA?
h. Does this entire set of explanatory variables explain a statistically significant proportion of the variation in starting salaries use Alpha = .01
i. Calculate the adjusted coefficient of determination?
j.Below is a correlation Matrix does there appear to be any evidence of a multi collinearity problem yes or no?
Explanation / Answer
a) The estimated regression equation is
Y = 13.406268 - 0.371051676 sex + gpa = 3.325668 + 0.085804187 age + 2.462907 major
b) Age = 0.0858 which is >0 i.e. there exist postive correlation between age starting salary
As age increase 1 year then starting salary increase $0.0858
c) Major = 2.462907 which is > 0 i.e. there exist postive correlation between major starting salary
As major (accounting =1) then starting salary increase $2.4629
d) Power or correlation determinatio = 97.02933559 / 97.8 = 0.99212
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