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Predicting quit rates in manufacturing. The reasons given
Chapter 11, Problem 89E(choose chapter or problem)
Predicting quit rates in manufacturing. The reasons given by workers for quitting their jobs generally fall 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 table below 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 y on average wage x.
Industry |
Quit Rate, y |
Average Wage, x |
1 |
1.4 |
$8.20 |
2 |
0.7 |
10.35 |
3 |
2.6 |
6.18 |
4 |
3.4 |
5.37 |
5 |
1.7 |
9.94 |
6 |
1.7 |
9.11 |
7 |
1 |
10.59 |
8 |
0.5 |
13.29 |
9 |
2 |
7.99 |
10 |
3.8 |
5.54 |
11 |
2.3 |
7.5 |
12 |
1.9 |
6.43 |
13 |
1.4 |
8.83 |
14 |
1.8 |
10.93 |
15 |
2 |
8.8 |
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.
Questions & Answers
QUESTION:
Predicting quit rates in manufacturing. The reasons given by workers for quitting their jobs generally fall 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 table below 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 y on average wage x.
Industry |
Quit Rate, y |
Average Wage, x |
1 |
1.4 |
$8.20 |
2 |
0.7 |
10.35 |
3 |
2.6 |
6.18 |
4 |
3.4 |
5.37 |
5 |
1.7 |
9.94 |
6 |
1.7 |
9.11 |
7 |
1 |
10.59 |
8 |
0.5 |
13.29 |
9 |
2 |
7.99 |
10 |
3.8 |
5.54 |
11 |
2.3 |
7.5 |
12 |
1.9 |
6.43 |
13 |
1.4 |
8.83 |
14 |
1.8 |
10.93 |
15 |
2 |
8.8 |
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.
ANSWER:Step 1 of 7
Let x denotes the average hourly wage and y be the quit rates (number of quits per 100
employees).
a) Using MINITAB, we conduct regression analysis on the given data in the
following steps.
Stepl: Import the data into the worksheet.
Step2: Choose Stat 
Step3: Specify QuitRate in the Response text box,
Step4: Specify AveWage in the Predictors text box.
Step5: Specify 9.00 in Prediction intervals for new observations tab.
Step6: Click OK.