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SCENARIO 14-8 A Financial Analyst Wanted to Examine the Relationship Between Salary

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SCENARIO 14-8
A financial analyst wanted to examine the relationship between salary (in $1,000) and 2 variables: age (X1 = Age) and experience in the field (X2 = Exper). He took a sample of 20 employees and obtained the following Microsoft Excel output:
SCENARIO 14-8 A financial analyst wanted to examine the relationship between salary (in $1,000) and 2 variables: age (X<sub>1</sub> = Age) and experience in the field (X<sub>2</sub> = Exper). He took a sample of 20 employees and obtained the following Microsoft Excel output:     Also, the sum of squares due to the regression for the model that includes only Age is 5022.0654 while the sum of squares due to the regression for the model that includes only Exper is 125.9848. -Referring to Scenario 14-8,the F test for the significance of the entire regression performed at a level of significance of 0.01 leads to a rejection of the null hypothesis.
SCENARIO 14-8 A financial analyst wanted to examine the relationship between salary (in $1,000) and 2 variables: age (X<sub>1</sub> = Age) and experience in the field (X<sub>2</sub> = Exper). He took a sample of 20 employees and obtained the following Microsoft Excel output:     Also, the sum of squares due to the regression for the model that includes only Age is 5022.0654 while the sum of squares due to the regression for the model that includes only Exper is 125.9848. -Referring to Scenario 14-8,the F test for the significance of the entire regression performed at a level of significance of 0.01 leads to a rejection of the null hypothesis.
Also, the sum of squares due to the regression for the model that includes only Age is 5022.0654 while the sum of squares due to the regression for the model that includes only Exper is 125.9848.
-Referring to Scenario 14-8,the F test for the significance of the entire regression performed at a level of significance of 0.01 leads to a rejection of the null hypothesis.


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