
Applied Statistics and Probability for Engineers
6th Edition
ISBN: 9781118539712
Author: Douglas C. Montgomery
Publisher: WILEY
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Chapter 12.1, Problem 21E
a.
To determine
Construct a multiple linear regression model to the data by using percentage of completions, percentage of TDs or touchdowns and percentage of interceptions as the regressors.
b.
To determine
Find the estimate of
c.
To determine
Obtain the values of the standard errors of the regression coefficients.
d.
To determine
Find the predicted value of rating for value 60% for percentage of completions, value 4% for percentage of TDs and value 3% for percentage of interceptions.
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Using the accompanying Accounting Professionals data to answer the following questions.
a. Find and interpret a 90% confidence interval for the mean years of service.
b. Find and interpret a 90% confidence interval for the proportion of employees who have a graduate degree.
view the Accounting Professionals data.
Employee Years of Service Graduate Degree?1 26 Y2 8 N3 10 N4 6 N5 23 N6 5 N7 8 Y8 5 N9 26 N10 14 Y11 10 N12 8 Y13 7 Y14 27 N15 16 Y16 17 N17 21 N18 9 Y19 9 N20 9 N
Question content area bottom
Part 1
a. A 90% confidence interval for the mean years of service is
(Use ascending order. Round to two decimal places as needed.)
Chapter 12 Solutions
Applied Statistics and Probability for Engineers
Ch. 12.1 - 12.1. Exercise 11.1 described a regression model...Ch. 12.1 - 12.2. A class of 63 students has two hourly exams...Ch. 12.1 - 12.3. Can the percentage of the workforce who are...Ch. 12.1 - Prob. 4ECh. 12.1 - Prob. 5ECh. 12.1 - Prob. 6ECh. 12.1 - Prob. 7ECh. 12.1 - 12-8. You have fit a multiple linear regression...Ch. 12.1 - 12-9. The data from a patient satisfaction survey...Ch. 12.1 - 12-10. The electric power consumed each month by a...
Ch. 12.1 - 12-11. Table E12-3 provides the highway gasoline...Ch. 12.1 - 12-12. The pull strength of a wire bond is an...Ch. 12.1 - Prob. 13ECh. 12.1 - Prob. 14ECh. 12.1 - 12-15. An article in Electronic Packaging and...Ch. 12.1 - 12-16. An article in Cancer Epidemiology,...Ch. 12.1 - Prob. 17ECh. 12.1 - Prob. 18ECh. 12.1 - Prob. 19ECh. 12.1 - Prob. 20ECh. 12.1 - Prob. 21ECh. 12.1 - Prob. 22ECh. 12.1 - 12-23. A study was performed on wear of a bearing...Ch. 12.1 - Prob. 24ECh. 12.2 - 12-25. Recall the regression of percent of body...Ch. 12.2 - Prob. 27ECh. 12.2 - Prob. 28ECh. 12.2 - 12-29. Consider the following computer...Ch. 12.2 - 12-30. You have fit a regression model with two...Ch. 12.2 - 12-31. Consider the regression model fit to the...Ch. 12.2 - 12-32. Consider the absorption index data in...Ch. 12.2 - Prob. 33ECh. 12.2 - Prob. 34ECh. 12.2 - 12-35. Consider the gasoline mileage data in...Ch. 12.2 - Prob. 36ECh. 12.2 - Prob. 37ECh. 12.2 - Prob. 38ECh. 12.2 - 12-39. Consider the regression model fit to the...Ch. 12.2 - Prob. 40ECh. 12.2 - Prob. 41ECh. 12.2 - Prob. 42ECh. 12.2 - 12-43. Consider the NFL data in Exercise...Ch. 12.2 - Prob. 44ECh. 12.2 - 12-45. Consider the bearing wear data in Exercise...Ch. 12.2 - 12-46. Data on National Hockey League team...Ch. 12.2 - Prob. 47ECh. 12.2 - Prob. 48ECh. 12.4 - Prob. 52ECh. 12.4 - 12-53. Consider the regression model fit to the...Ch. 12.4 - 12-55. Consider the semiconductor data in Exercise...Ch. 12.4 - 12-56. Consider the electric power consumption...Ch. 12.4 - Prob. 57ECh. 12.4 - Prob. 58ECh. 12.4 - 12-59. Consider the regression model fit to the...Ch. 12.4 - Prob. 60ECh. 12.4 - 12-61. Consider the regression model fit to the...Ch. 12.4 - Prob. 62ECh. 12.4 - Prob. 63ECh. 12.4 - Prob. 64ECh. 12.4 - Prob. 65ECh. 12.4 - Prob. 66ECh. 12.4 - Prob. 67ECh. 12.4 - 12-68. Consider the NHL data in Exercise...Ch. 12.5 - 12-69. Consider the gasoline mileage data in...Ch. 12.5 - Prob. 70ECh. 12.5 - Prob. 71ECh. 12.5 - Prob. 72ECh. 12.5 - 12-73. Consider the regression model fit to the...Ch. 12.5 - Prob. 74ECh. 12.5 - Prob. 75ECh. 12.5 - Prob. 76ECh. 12.5 - Prob. 77ECh. 12.5 - Prob. 78ECh. 12.5 - Prob. 79ECh. 12.5 - 12-80. Fit a model to the response PITCH in the...Ch. 12.5 - Prob. 81ECh. 12.6 - 12-84. An article entitled “A Method for Improving...Ch. 12.6 - Prob. 85ECh. 12.6 - Prob. 86ECh. 12.6 - Prob. 87ECh. 12.6 - 12-88. Consider the arsenic concentration data in...Ch. 12.6 - Prob. 89ECh. 12.6 - Prob. 90ECh. 12.6 - 12-91. Consider the X-ray inspection data in...Ch. 12.6 - 12-92. Consider the electric power data in...Ch. 12.6 - Prob. 93ECh. 12.6 - Prob. 94ECh. 12.6 - 12-95. Consider the gray range modulation data in...Ch. 12.6 - 12-96. Consider the nisin extraction data in...Ch. 12.6 - Prob. 97ECh. 12.6 - Prob. 98ECh. 12.6 - Prob. 99ECh. 12.6 - 12-100. Consider the arsenic data in Exercise...Ch. 12.6 - 12-101. Consider the gas mileage data in Exercise...Ch. 12.6 - Prob. 102ECh. 12.6 - Prob. 103ECh. 12.6 - Prob. 104ECh. 12.6 - Prob. 105ECh. 12 - Prob. 106SECh. 12 - 12-107. Consider the following inverse of the...Ch. 12 - 12-108. The data shown in Table E12-14 represent...Ch. 12 - Prob. 109SECh. 12 - Prob. 111SECh. 12 - Prob. 112SECh. 12 - 12-113. Consider the jet engine thrust data in...Ch. 12 - 12-114. Consider the electronic inverter data in...Ch. 12 - 12-115. A multiple regression model was used to...Ch. 12 - Prob. 116SECh. 12 - 12-117. An article in the Journal of the American...Ch. 12 - 12-118. Exercise 12-9 introduced the hospital...Ch. 12 - Prob. 119SECh. 12 - Prob. 120SECh. 12 - 12-121. A regression model is used to relate a...Ch. 12 - Prob. 122SECh. 12 - Prob. 123SECh. 12 - Prob. 124SECh. 12 - Prob. 125SE
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