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SCENARIO 14-8
a Financial Analyst Wanted to Examine the Relationship β\beta

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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 14-7,the department head decided to construct a 95% confidence interval for  \beta <sub>1 </sub>.The confidence interval is from to .
 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 14-7,the department head decided to construct a 95% confidence interval for  \beta <sub>1 </sub>.The confidence interval is from to .
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 14-7,the department head decided to construct a 95% confidence interval for β\beta 1 .The confidence interval is from to .

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