University of Cincinnati

BANA 2082

Quiz 7A

1)The company identified in Chapter 7, Analytics in Action, is

2. The Analytics in Action example in Chapter 7 concerned

3. Chapter 7 focuses on

4. A regression analysis involving one independent variable and one dependent variable is referred to as a

5. The graph of the simple linear regression equation is a(n)

Quiz 7B

1. The difference between the observed value of the dependent variable and the value predicted using the estimated regression equation is known as the

2. What would be the value of the sum of squares due to regression (SSR) if the total sum of squares (SST) is 25.32 and the sum of squares due to error (SSE) is 6.89?

3. The                             is a measure of the goodness of fit of the estimated regression equation. It can be interpreted as the proportion of the variability in the dependent variable y that is explained by the estimated regression equation.

4. What would be the coefficient of determination if the total sum of squares (SST) is 23.29 and the sum of squares due to regression (SSR) is 10.03?

5. Regression analysis involving one dependent variable and more than one independent variable is known as

6. The scatter chart below displays the residuals verses the dependent variable, x. Which of the following conclusions can be drawn from the scatter chart given below?

7.                                         is used to test the hypothesis that the values of the regression parameters B 0, B 1, B 2, ... B q are all zero.

Quiz 7C

1. In a linear regression model, the variable (or variables) used for predicting or explaining values of the response variable are known as the                                            . It(they) is(are) denoted by x.

2. Using the attached LineSpeed data, develop an estimated regression equation to predict the number of defective parts found given the line speed. How much of the variation in defective parts is explained by your model? Enter your answer as a decimal rounded to three decimal places.

3. Considering the results in Question 2, what is the estimated coefficient for Line Speed? Round your answer to three decimal places.

4. Considering the results from Question 2, the coefficient for Line Speed is significant at a 5% level.

5. Considering the results from Question 2, the coefficient for Line Speed is significant at a 1% level.

6. Using the attached data, develop an estimated regression equation to predict the Total Points Earned based on the Hours Spent Studying. How much of the variation in Total Points Earned is explained by your model? Enter your answer as a decimal rounded to three decimal places.

7. Considering the results from Question 6, what is the test statistic associated with the coefficient for Hours Spent Studying? Round your answer to three decimal places.

8. Considering the results from Question 6, the coefficient for Hours Spent Studying is significant at a 1% level.

9. Considering the results from Question 6, use the model to predict the number of points a student would earn if the student studied 95 hours. Round your answer to one decimal place.

10. The attached data are the results of a survey on upscale accommodations. The data show the percentages of respondents who rated the locations as excellent or very good on Comfort, Amenities, In-House Dining and Overall. Develop an estimated regression equation to predict the Overall rating using Comfort, Amenities and In-House Dining. How much of the variation in the Overall rating is explained by your model? Enter your answer as a decimal rounded to three decimal places.

11. Considering the results from Question 10, we can conclude that the model is significant.

12. Considering the results from Question 10, which if any of the independent variables are not significant?

13. Recreate the analysis of Question 10 dropping the independent variable Comfort. Compare the results. Did R Square increase, decrease or remain the same?

14. Compare the results from Questions 10 and 13. Did Adjusted R Square increase, decrease or remain the same in Question 13?
15. Compare the results from Questions 10 and 13. Did the Standard Error increase, decrease or remain the same in Question 13?

Quiz 7D

1. A variable used to model the effect of categorical independent variables in a regression model which generally takes only the value zero or one is called

2. Which of the following regression models is used to model a nonlinear relationship between the independent and dependent variables by including the independent variable and the square of the independent variable in the model?

3. A study investigated the relationship between audit delay (the length of time from a company’s fiscal year-end to the date of the auditor’s report) and variables that describe the client and the auditor. Some of the independent variables that were included in this study follow:

Industry                           A dummy variable coded 1 if the firm was an industrial company or 0 if the firm was a bank, savings and loan, or insurance company.

Public                                A dummy variable coded 1 if the company was traded on an organized exchange or over the counter; otherwise coded 0.

Quality                              A measure of overall quality of internal controls, as judged by the auditor, on a 5-point scale ranging from “virtually none” (1) to “excellent” (5).

Finished                           A measure ranging from 1 to 4, as judged by the auditor, where 1 indicates “all work performed subsequent to year-end” and 4 indicates “most work performed prior to year-end.”

A sample of 40 companies provided the following data:

Audit

Develop the estimated regression equation using all of the independent variables included in the data. Enter the value of the intercept rounded to three decimal places.

4. Consider the result in Question 3. At a 5% level of significance, which variable is not significant?

5. Rerun the the analysis done in Question 3 without the independent variable identified in Question

4. Which independent variable is significant at the 1% level of significance?  

Quiz 7E

1. The degree of correlation among independent variables in a regression model is called

2.                                  refers to the scenario in which the relationship between the dependent variable and one independent variable is different at different values of a second independent variable.