We appreciate your visit to An economist was interested in modeling the relation among annual income level of education and work experience The following data was obtained from a random. This page offers clear insights and highlights the essential aspects of the topic. Our goal is to provide a helpful and engaging learning experience. Explore the content and find the answers you need!
Answer :
Answer:
Check the explanation
Step-by-step explanation:
A) We use Minitab to solve the question.
The correlation matrix is,
Correlation: Level of Education, Work Experience, Annual Income ($ ,000s)
Work Experience Level of Education
Level of Education -0.042 0.463
Annual Income ($ 0.463 0.756
From correlation matrix there is no any reason to concern multicoinearity.
B)
The Regression Analysis: Annual Income ($ Thousands) vs Work Experience and Level of Education
Analysis of Variance
Source D F Adj SS Adj MS F-Value P-Value
Regression 2 5577 2788.4 19.96 0.000
Work Experience 1 1675 1674.7 11.99 0.007
Level of Education 1 4114 4114.1 29.44 0.000
Error 9 1257 139.7
Total 11 6834
Model Summary
S R-sq R-sq(adj) R-sq(pred)
11.8204 81.60% 77.51% 69.81%
Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant -15.2 10.2 -1.49 0.171
Work Experience 1.545 0.446 3.46 0.007 1.00
Level of Education 5.57 1.03 5.43 0.000 1.00
E)
The value of R-sq is 81.60% & R-sq (adj) is 77.51% indicates that adequacy of the fitted model is good.
G & H )
Coefficients
Term Coef SE Coef T-Value P-Value
Constant -15.2 10.2 -1.49 0.171 > 0.05 (significant)
Work Experience 1.545 0.446 3.46 0.007 > 0.05 (significant) ______Reject H0 B1 = 0
Level of Education 5.57 1.03 5.43 0.000 < 0.05 (Not Significant) ______do not Reject H0 B2 = 0
H)
Regression Equation
Annual Income ($ Thousands) = -15.2 + 1.545 Work Experience + 5.57 Level of Education
= -15.2 + 1.545 * 12 + 5.57 * 4
= 25.62
I & J)
Regression Equation
Annual Income ($ Thousands) = -15.2 + 1.545 Work Experience + 5.57 Level of Education
Variable Setting
Work Experience 12
Level of Education 4
Predicted Income is 25.5649 thousands:
Kindly check the attached image below.
Fit SE Fit 95% CI 95% PI
25.5649 4.42545 (15.5538, 35.5759) (-2.98733, 54.1170)
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