1. Slide 8- 1 Copyright © 2010 Pearson Education, Inc. Active Learning Lecture Slides For use with Classroom Response Systems Business Statistics First Edition by Sharpe, De Veaux, Velleman Chapter 8: Linear Regression

2. Slide 8- 2 Copyright © 2010 Pearson Education, Inc. The difference between the observed and predicted value of y from a linear model is called the A. Remainder B. Correlation C. Residual D. Variance

3. Slide 8- 3 Copyright © 2010 Pearson Education, Inc. The difference between the observed and predicted value of y from a linear model is called the A. Remainder B. Correlation C. Residual D. Variance

4. Slide 8- 4 Copyright © 2010 Pearson Education, Inc. A negative residual means the predicted value is too big – an overestimate. A. True B. False

5. Slide 8- 5 Copyright © 2010 Pearson Education, Inc. A negative residual means the predicted value is too big – an overestimate. A. True B. False

6. Slide 8- 6 Copyright © 2010 Pearson Education, Inc. The line of best fit through data is the line that A. minimizes the sum of residuals. B. minimizes each residual. C. minimizes the sum of the squared residuals. D. maximizes the sum of the squared residuals.

7. Slide 8- 7 Copyright © 2010 Pearson Education, Inc. The line of best fit through data is the line that A. minimizes the sum of residuals. B. minimizes each residual. C. minimizes the sum of the squared residuals. D. maximizes the sum of the squared residuals.

8. Slide 8- 8 Copyright © 2010 Pearson Education, Inc. In comparison to correlation, what additional condition must be met in order to model a relationship with a regression line? A. Quantitative variables condition B. Nearly normal condition C. Straight enough condition D. Equal spread condition

9. Slide 8- 9 Copyright © 2010 Pearson Education, Inc. In comparison to correlation, what additional condition must be met in order to model a relationship with a regression line? A. Quantitative variables condition B. Nearly normal condition C. Straight enough condition D. Equal spread condition

10. Slide 8- 10 Copyright © 2010 Pearson Education, Inc. Which of the following is true about the standard deviation of the residuals? A. Measures how much the points spread around the regression line. B. Is used to check the equal spread condition. C. The larger the value the better the linear model fits the data. D. All of the above.

11. Slide 8- 11 Copyright © 2010 Pearson Education, Inc. Which of the following is true about the standard deviation of the residuals? A. Measures how much the points spread around the regression line. B. Is used to check the equal spread condition. C. The larger the value the better the linear model fits the data. D. All of the above.

12. Slide 8- 12 Copyright © 2010 Pearson Education, Inc. If the correlation r = 0, then we know that A. the slope of the regression line is positive. B. there is a perfect linear relationship. C. the slope of the regression line is zero. D. the intercept of the regression line is zero.

13. Slide 8- 13 Copyright © 2010 Pearson Education, Inc. If the correlation r = 0, then we know that A. the slope of the regression line is positive. B. there is a perfect linear relationship. C. the slope of the regression line is zero. D. the intercept of the regression line is zero.

14. Slide 8- 14 Copyright © 2010 Pearson Education, Inc. When we have a good linear model, we can infer that x causes y. A. True B. False

15. Slide 8- 15 Copyright © 2010 Pearson Education, Inc. When we have a good linear model, we can infer that x causes y. A. True B. False

16. Slide 8- 16 Copyright © 2010 Pearson Education, Inc. A regression analysis of employee salaries and years of service to the company found R 2 = 0.311. Which of the following is true? I. The correlation between employee salary and years of service to the company is 0.311. II. 31.1 % of employee salaries can be correctly predicted with this model. III. 31.1% of the variance in employee salaries can be accounted for by the model. A. I only B. II only C. III only D. II and III

17. Slide 8- 17 Copyright © 2010 Pearson Education, Inc. A regression analysis of employee salaries and years of service to the company found R 2 = 0.311. Which of the following is true? I. The correlation between employee salary and years of service to the company is 0.311. II. 31.1 % of employee salaries can be correctly predicted with this model. III. 31.1% of the variance in employee salaries can be accounted for by the model. A. I only B. II only C. III only D. II and III

18. Slide 8- 18 Copyright © 2010 Pearson Education, Inc. A consumer group collected data on standard color TV sets (no HD or large screen sets). They created a linear model to estimate the cost of the TV (in $) based on the screen size (in inches). Which is the most likely slope of the line of best fit? A. 0.25 B. 2.5 C. 25.0 D. 250.0

19. Slide 8- 19 Copyright © 2010 Pearson Education, Inc. A consumer group collected data on standard color TV sets (no HD or large screen sets). They created a linear model to estimate the cost of the TV (in $) based on the screen size (in inches). Which is the most likely slope of the line of best fit? A. 0.25 B. 2.5 C. 25.0 D. 250.0