The service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year.  The analyst ran a simple linear regression shown below. Table 7: Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .854a .730 .695 6.6235 a. Predictors: (Constant), Hourly Wage   Table 8: ANOVA ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 1918.458 1 1918.458 129.783 .000a Residual 709.567 48 14.782     Total 2628.025 49       a. Predictors: (Constant), Hourly Wage b. Dependent Variable: Number of Complaints   Table 9: Coefficients Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 20.2 4.357   4.636 .000 Hourly Wage -1.20 .088 -.946 -13.636 .000 a. Dependent Variable: Number of Complaints   What proportion of variation in the number of complaints can be explained by hourly wages? From the results shown above, write the regression equation. If wages were increased by $1.00, what is the expected effect on the number of complaints received per employee?  The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive? Is the regression coefficient statistically significant? How can you tell?

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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The service regresses the number of complaints lodged against an employee last year on the hourly wage of the employee for the year.  The analyst ran a simple linear regression shown below.

Table 7: Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.854a

.730

.695

6.6235

a. Predictors: (Constant), Hourly Wage

 

Table 8: ANOVA

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

1918.458

1

1918.458

129.783

.000a

Residual

709.567

48

14.782

 

 

Total

2628.025

49

 

 

 

a. Predictors: (Constant), Hourly Wage

b. Dependent Variable: Number of Complaints

 

Table 9: Coefficients

Coefficientsa

Model

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

B

Std. Error

Beta

1

(Constant)

20.2

4.357

 

4.636

.000

Hourly Wage

-1.20

.088

-.946

-13.636

.000

a. Dependent Variable: Number of Complaints

 

What proportion of variation in the number of complaints can be explained by hourly wages?

From the results shown above, write the regression equation.

If wages were increased by $1.00, what is the expected effect on the number of complaints received per employee? 

The current minimum wage is $5.15. If an employee earns the minimum wage, how many complaints can that employee expect to receive?

Is the regression coefficient statistically significant? How can you tell?

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