Applied Statistics and Probability for Engineers
6th Edition
ISBN: 9781118539712
Author: Douglas C. Montgomery
Publisher: WILEY
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Chapter 15.9, Problem 87E
To determine
Find the decision based on minimax, most probable and expected cost criteria.
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12. A sociologist hypothesizes that the crime rate is higher in areas
with higher poverty rate and lower median income. She col-
lects data on the crime rate (crimes per 100,000 residents),
the poverty rate (in %), and the median income (in $1,000s)
from 41 New England cities. A portion of the regression results
is shown in the following table.
Standard
Coefficients
error
t stat
p-value
Intercept
-301.62
549.71
-0.55 0.5864
Poverty
53.16
14.22
3.74 0.0006
Income
4.95
8.26
0.60 0.5526
a.
b.
Are the signs as expected on the slope coefficients?
Predict the crime rate in an area with a poverty rate of
20% and a median income of $50,000.
3. Using data from 50 work
2. The owner of several used-car dealerships believes that the
selling price of a used car can best be predicted using the car's
age. He uses data on the recent selling price (in $) and age of
20 used sedans to estimate Price = Po + B₁Age + ε. A portion
of the regression results is shown in the accompanying table.
Standard
Coefficients
Intercept
21187.94
Error
733.42
t Stat p-value
28.89 1.56E-16
Age
-1208.25
128.95 -9.37
2.41E-08
a. What is the estimate for B₁? Interpret this value.
b. What is the sample regression equation?
C. Predict the selling price of a 5-year-old sedan.
ian income of $50,000.
erty rate of
13. Using data from 50 workers, a researcher estimates Wage =
Bo+B,Education + B₂Experience + B3Age+e, where Wage
is the hourly wage rate and Education, Experience, and Age
are the years of higher education, the years of experience, and
the age of the worker, respectively. A portion of the regression
results is shown in the following table. ni ogolloo bash
1
Standard
Coefficients error
t stat p-value
Intercept
7.87
4.09
1.93
0.0603
Education
1.44
0.34
4.24 0.0001
Experience
0.45
0.14
3.16
0.0028
Age
-0.01
0.08 -0.14 0.8920
a. Interpret the estimated coefficients for Education and
Experience.
b. Predict the hourly wage rate for a 30-year-old worker
with four years of higher education and three years of
experience.
Chapter 15 Solutions
Applied Statistics and Probability for Engineers
Ch. 15.3 - 15-1. Control charts for and R are to be set up...Ch. 15.3 - 15-2. Twenty-five samples of size 5 are drawn from...Ch. 15.3 - 15-3. Control charts are to be constructed for...Ch. 15.3 - 15-4. Samples of size n = 6 are collected from a...Ch. 15.3 - 15-5. The level of cholesterol (in mg/dL) is an...Ch. 15.3 - 15-6. An control chart with three-sigma control...Ch. 15.3 - 15-7. An extrusion die is used to produce aluminum...Ch. 15.3 - 15-8. The copper content of a plating bath is...Ch. 15.3 - 15-9. The pull strength of a wire-bonded lead for...Ch. 15.3 - 15-10. The following data were considered in...
Ch. 15.3 - 15-11. The thickness of a metal part is an...Ch. 15.3 - 15-12. Apply the Western Electric Rules to the...Ch. 15.3 - 15-13. Apply the Western Electric Rules to the...Ch. 15.3 - 15-14. Web traffic can be measured to help...Ch. 15.3 - 15-15. Consider the data in Exercise 15-9....Ch. 15.3 - 15-16. Consider the data in Exercise 15-10....Ch. 15.3 - 15-17. An X control chart with 3-sigma control...Ch. 15.3 - 15-18. An article in Quality & Safety in Health...Ch. 15.4 - 15-19. Twenty successive hardness measurements are...Ch. 15.4 - 15-20. In a semiconductor manufacturing process,...Ch. 15.4 - 15-21. O An automatic sensor measures the diameter...Ch. 15.4 - 15-22. The viscosity of a chemical intermediate is...Ch. 15.4 - 15-23. The following table of data was analyzed in...Ch. 15.4 - 15-24. Pulsed laser deposition technique is a thin...Ch. 15.4 - 15-25. The production manager of a soap...Ch. 15.4 - 15-26. An article in Quality & Safety in Health...Ch. 15.4 - 15-27. An article in Journal of the Operational...Ch. 15.5 - 15-28. Suppose that a quality characteristic is...Ch. 15.5 - 15-29. Suppose that a quality characteristic is...Ch. 15.5 - 15-30. Suppose that a quality characteristic is...Ch. 15.5 - 15-31. A normally distributed process uses 66.7%...Ch. 15.5 - 15-32. A normally distributed process uses 85% of...Ch. 15.5 - 15-33. Reconsider Exercise 15-1. Suppose that the...Ch. 15.5 - 15-34. Reconsider Exercise 15-2 in which the...Ch. 15.5 - 15-35. Reconsider Exercise 15-3. Suppose that the...Ch. 15.5 - 15-36. Reconsider Exercise 15-4(a). Assuming that...Ch. 15.5 - 15-37. Reconsider the diameter measurements in...Ch. 15.5 - 15-38. Reconsider the copper-content measurements...Ch. 15.5 - 15-39. Reconsider the pull-strength measurements...Ch. 15.5 - 15-40. Reconsider the syringe lengths in Exercise...Ch. 15.5 - 15-41. Reconsider the hardness measurements in...Ch. 15.5 - 15-42. Reconsider the viscosity measurements in...Ch. 15.5 - 15-43. Suppose that a quality characteristic is...Ch. 15.5 - 15-44. Suppose that a quality characteristic is...Ch. 15.5 - 15-45. An control chart with 3-sigma control...Ch. 15.5 - 15-46. A control chart for individual observations...Ch. 15.5 - 15-47. A process mean is centered between the...Ch. 15.5 - 15-48. The PCR for a measurement is 1.5 and the...Ch. 15.6 - 15-49. An early example of SPC was described in...Ch. 15.6 - 15-50. Suppose that the following fraction...Ch. 15.6 - 15-51. The following are the numbers of defective...Ch. 15.6 - 15-52. The following represent the number of...Ch. 15.6 - 15-53. The following represent the number of...Ch. 15.6 - 15-54. Consider the data on the number of...Ch. 15.6 - 15-55. In a semiconductor manufacturing company,...Ch. 15.6 - Prob. 56ECh. 15.6 - Prob. 57ECh. 15.6 - Prob. 58ECh. 15.7 - Prob. 59ECh. 15.7 - Prob. 60ECh. 15.7 - 15-61. Consider the control chart in Fig. 15-3....Ch. 15.7 - Prob. 62ECh. 15.7 - Prob. 63ECh. 15.7 - Prob. 64ECh. 15.7 - Prob. 65ECh. 15.7 - Prob. 66ECh. 15.7 - Prob. 67ECh. 15.7 - Prob. 68ECh. 15.7 - Prob. 69ECh. 15.7 - 15-70. Consider an control chart with UCL =...Ch. 15.7 - Prob. 71ECh. 15.7 - Prob. 72ECh. 15.8 - Prob. 73ECh. 15.8 - Prob. 74ECh. 15.8 - Prob. 75ECh. 15.8 - Prob. 76ECh. 15.8 - Prob. 77ECh. 15.8 - Prob. 78ECh. 15.8 - Prob. 79ECh. 15.8 - Prob. 80ECh. 15.8 - Prob. 81ECh. 15.8 - 15-82. A process has a target of μ0 = 100 and a...Ch. 15.8 - 15-83. Heart rate (in counts/minute) is measured...Ch. 15.8 - Prob. 84ECh. 15.8 - Prob. 85ECh. 15.8 - Prob. 86ECh. 15.9 - Prob. 87ECh. 15.9 - Prob. 88ECh. 15.9 - Prob. 89ECh. 15.9 - Prob. 90ECh. 15 - Prob. 91SECh. 15 - 15-92. Rework Exercise 15-91 with and S...Ch. 15 - Prob. 93SECh. 15 - Prob. 94SECh. 15 - 15-95. An article in Quality Engineering [“Is the...Ch. 15 - Prob. 96SECh. 15 - Prob. 97SECh. 15 - Prob. 98SECh. 15 - Prob. 99SECh. 15 - Prob. 100SECh. 15 - Prob. 101SECh. 15 - Prob. 102SECh. 15 - Prob. 103SECh. 15 - Prob. 104SECh. 15 - Prob. 105SECh. 15 - Prob. 106SECh. 15 - Prob. 107SECh. 15 - Prob. 108SECh. 15 - 15-109. The depth of a keyway is an important part...Ch. 15 - Prob. 110SECh. 15 - Prob. 111SECh. 15 - Prob. 112SECh. 15 - Prob. 113SECh. 15 - Prob. 114SECh. 15 - Prob. 115SECh. 15 - Prob. 117SECh. 15 - Prob. 118SECh. 15 - 15-119. Consider an control chart with UCL =...Ch. 15 - Prob. 120SECh. 15 - Prob. 121SECh. 15 - Prob. 122SECh. 15 - Prob. 123SECh. 15 - Prob. 124SECh. 15 - Prob. 125SECh. 15 - Prob. 126SECh. 15 - Prob. 127SECh. 15 - Prob. 128SECh. 15 - Prob. 129SECh. 15 - Prob. 130SECh. 15 - Prob. 131SECh. 15 - 15-132. Consider an control chart with k-sigma...Ch. 15 - Prob. 133SECh. 15 - Prob. 134SECh. 15 - Prob. 135SECh. 15 - Prob. 136SECh. 15 - 15-137. Consider a process whose specifications on...Ch. 15 - Prob. 138SECh. 15 - Prob. 139SECh. 15 - Prob. 140SECh. 15 - Prob. 141SE
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