EBK STATISTICS FOR BUSINESS AND ECONOMI
13th Edition
ISBN: 8220103633567
Author: Sincich
Publisher: PEARSON
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Chapter 11.6, Problem 11.95ACI
Predicting quit rates In manufacturing The reasons given by workers for quitting their jobs generally tall into one of two categories: (1) worker quits to seek or take a different job. or (2) worker quits to withdraw from the labor force Economic theory suggests that wages and quit rates are related The next table lists quit rates (quits per 100 employees) and the average hourly wage in a sample of 15 manufacturing industries. Consider the simple linear regression of quit rate yon average wage x.
- a. Do the data present sufficient evidence to conclude that average hourly wage rate contributes useful information for the prediction of quit rates’ What does your model suggest about the relationship between quit rates and wages?
- b. Find a 95% prediction interval for the quit rate in an industry with an average hourly wage of $9.00. Interpret the result.
- c. Find a 95% confidence interval for the mean quit rate for industries with an average hourly wage of $9.00. Interpret this result.
| Industry | Quit Rate, y | Average Wage, x |
| 1 | 1.4 | S 8 20 |
| 2 | .7 | 10 35 |
| 3 | 2.6 | 6 18 |
| 4 | 3.4 | 5.37 |
| 5 | 1.7 | 994 |
| 6 | 1.7 | 9.11 |
| 7 | 1.0 | 1059 |
| 8 | .5 | 13.29 |
| 9 | 2.0 | 7.99 |
| 10 | 3.8 | 5.54 |
| 11 | 2.3 | 7.50 |
| 12 | 1.9 | 643 |
| 13 | 1.4 | 8.83 |
| 14 | 1.8 | 10.93 |
| 15 | 2.0 | 8.80 |
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13. Collinearity in a multiple regression analysis
Suppose you want to examine the effects of a training program on future earnings using the following model:
earn98= 4.64 +2.376train +0.371earn96 +0.366educ- 1.86 age +2.534 married
(1.14) (0.43)
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(0.062)
(0.013)
(0.4)
where
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train -1 if the individual participated in the training program, and =0 otherwise
earn 96- 1996 earnings, in thousands of dollars
educ years of education
age = age, in years
married-1 if the individual is married, and -0 otherwise
Suppose that there is a high degree of correlation (but not perfect) between earnings in 1996, education, age, and marital status.
True or False: We should be concerned about this high degree of correlation because it affects our ability to reliably estimate the impact of the training
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True
False
Chapter 11 Solutions
EBK STATISTICS FOR BUSINESS AND ECONOMI
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