A social scientist would like to analyze the relationship between educational attainment (in years of higher education) and annual salary (in $1,000s). He collects data on 20 individuals. A portion of the data is as follows:
Salary | Education | ||||
40 | 3 | ||||
53 | 4 | ||||
⋮ | ⋮ | ||||
38 | 0 | ||||
Salary | Education | |
40 | 3 | |
53 | 4 | |
80 | 6 | |
42 | 2 | |
70 | 5 | |
50 | 4 | |
110 | 8 | |
38 | 0 | |
42 | 3 | |
55 | 4 | |
85 | 6 | |
40 | 2 | |
70 | 5 | |
60 | 4 | |
140 | 8 | |
40 | 0 | |
75 | 5 | |
65 | 4 | |
125 | 8 | |
38 | 0 | |
a. Find the sample regression equation for the model: Salary = β0 + β1Education + ε. (Round answers to 2 decimal places.)
Salaryˆ=Salary^= + Education
b. Interpret the coefficient for Education.
As Education increases by 1 unit, an individual’s annual salary is predicted to increase by $8,590.
As Education increases by 1 unit, an individual’s annual salary is predicted to increase by $10,850.
As Education increases by 1 unit, an individual’s annual salary is predicted to decrease by $8,590.
As Education increases by 1 unit, an individual’s annual salary is predicted to decrease by $10,850.
c. What is the predicted salary for an individual who completed 7 years of higher education? (Round coefficient estimates to at least 4 decimal places and final answer to the nearest whole number.)
SalaryˆSalary^ = $
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