Question

1. 25-28) A sample of 30 companies was randomly selected for a study investigating what factors affect the size of company bonuses. Data were collected on the number of employees at the company and whether or not the employees were unionized(1=yes,0=no). Below are the multiple regression results. What does the scatterplot below suggest about developing a multiple regression model to predict Company Bonuses using Employees and Union as independent variables?

DependentVariableisAverageAnnualBonus

Predictor	Coef	SE Coef	T	P
Constant	347.9	872.2	0.40	0.693
Employees	0.6547	0.1105	5.92	0.000
Union	1259.5	605.8	2.08	0.047

S=1631.56R-Sq=62.4%R-Sq(adj)=59.6%

1. Using the interaction term Employees*Union in the model is appropriate.
2. Using Employeesas a dummy variable in this model is appropriate.
3. Employees should not be included in the model as a variable.
4. Onlyusing Unionas a dummy variable in this model is appropriate.
5. None of these.

2. Regression analysis was performed to develop a model for predicting a firm’s Price-Earnings Ratio (PE) based on Growth Rate, Profit Margin, and whether or not the firm is Green (1 = Yes, 0 = No). Based on the F-statistic of 26.48 which has a p-value of 0.000, we can conclude at α = .05 that

A).None of the independent variables in the model are significant.

B).All independent variables in the model are significant and the regression equation is significant.

C).All independent variables in the model are significant.

D).The regression equation is not significant.

E).The regression equation is significant.

3. The two plots below are created to check the assumptions for multiple linear regression model. According to the two plots, which of the following statement(s) is(are) correct?

I.Equal Variance and Linearity assumptions are NOT satisfied

II. Equal Variance and Linearity Assumptions are satisfied.

III. Independence Assumption is satisfied.

IV. Normality Assumption is NOT satisfied.

V. Independence Assumption is NOT satisfied.

1. I and IV.
2. I and III.
3. II and IV.
4. II and III.
5. I and V.

4. The Texas Transportation Institute studies traffic delays. Data the institute published in 2001 include information on the Total Delay per Person (hours per year spent delayed by traffic), the Average Arterial Road Speed (mph), the Average Highway Road Speed (mph), and the Size of the city (small, medium, large, very large). The regression model is:

Dependent variable is: Delay/person

R-squared = 79.1% R-squared (adjusted) = 77.4%

s = 6.474 with 68 - 6 = 62 degrees of freedom

Variable              Coeff                  SE(Coeff)            t-ratio      P-value

Intercept              139.104               16.69                      8.33     0.0001

HiWay MPH        1.07347                 0.2474                   4.34     0.0001

Arterial MPH       2.04836                 0.6672                   3.07     0.0032

Small                    3.58970                 2.953                    1.22     0.2287

Large                    5.00967                 2.104                    2.38     0.0203

Very Large          3.41058                 3.230                    1.06     0.2951

Which of the following independent variable(s) is(are) significant in this regression equation at α = .05?

1. HiWay MPH and Aterial MPH
2.    HiWay MPH, Arterial MPH, and Very Large
3. HiWay MPH, Arterial MPH, and Large
4. Small and Very Large
5.    Arterial MPH and Large

Answer 1

25. Option B. Using Employees as a dummy variable in this model is appropriate.(since p-value=0.000<0.05).

26. Option E).The regression equation is significant. (since p-value<0.05).

27. Plots are missing hence it is not possible to answer this question.

28. Option C: HiWay MPH, Arterial MPH, and Large (since their p-value<0.05).