Applied Statistics and Probability for Engineers
6th Edition
ISBN: 9781118539712
Author: Douglas C. Montgomery
Publisher: WILEY
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Chapter 15, Problem 125SE
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Consider the AR(3) model X₁ = 0.6Xt-1 − 0.4Xt-2 +0.1Xt-3. What is the value of the
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0.6
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None of these values
0.1
-0.4
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Suppose you are gambling on a roulette wheel. Each time the wheel is spun, the result is one of the outcomes 0, 1, and so on through 36. Of these outcomes, 18 are red, 18 are black, and 1 is green. On each spin you bet $5 that a red outcome will occur and $1 that the green outcome will occur. If red occurs, you win a net $4. (You win $10 from red and nothing from green.) If green occurs, you win a net $24. (You win $30 from green and nothing from red.) If black occurs, you lose everything you bet for a loss of $6.
a. Use simulation to generate 1,000 plays from this strategy. Each play should indicate the net amount won or lost. Then, based on these outcomes, calculate a 95% confidence interval for the total net amount won or lost from 1,000 plays of the game. (Round your answers to two decimal places and if your answer is negative value, enter "minus" sign.) I worked out the Upper Limit, but I can't seem to arrive at the correct answer for the Lower Limit. What is the Lower Limit?…
Let us suppose we have some article reported on a study of potential sources of injury to equine veterinarians conducted at a
university veterinary hospital. Forces on the hand were measured for several common activities that veterinarians engage in when
examining or treating horses. We will consider the forces on the hands for two tasks, lifting and using ultrasound. Assume that both
sample sizes are 6, the sample mean force for lifting was 6.2 pounds with standard deviation 1.5 pounds, and the sample mean force
for using ultrasound was 6.4 pounds with standard deviation 0.3 pounds. Assume that the standard deviations are known.
Suppose that you wanted to detect a true difference in mean force of 0.25 pounds on the hands for these two activities. Under the null
hypothesis, 40 0. What level of type II error would you recommend here?
=
Round your answer to four decimal places (e.g. 98.7654). Use α = 0.05.
β
= 0.0594
What sample size would be required?
Assume the sample sizes are to be…
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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