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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Given the following sample data values:
7, 12, 15, 9, 15, 13, 12, 10, 18,12
Find the following:
a) Σ
x=
b) x² =
c) x =
n
d) Median
=
e) Midrange
x
=
(Enter a whole number)
(Enter a whole number)
(use one decimal place accuracy)
(use one decimal place accuracy)
(use one decimal place accuracy)
f) the range=
g) the variance, s²
(Enter a whole number)
f) Standard Deviation, s =
(use one decimal place accuracy)
Use the formula s²
·Σx² -(x)²
n(n-1)
nΣ x²-(x)²
2
Use the formula s =
n(n-1)
(use one decimal place accuracy)
Table of hours of television watched per week:
11
15 24
34
36
22
20
30
12
32
24
36
42
36
42
26
37
39
48
35
26
29
27
81276
40
54
47
KARKE
31
35
42
75
35
46
36
42
65
28
54 65
28
23
28
23669
34
43 35 36
16
19
19
28212
Using the data above, construct a frequency table according the following
classes:
Number of Hours Frequency Relative Frequency
10-19
20-29
|30-39
40-49
50-59
60-69
70-79
80-89
From the frequency table above, find
a) the lower class limits
b) the upper class limits
c) the class width
d) the class boundaries
Statistics 300
Frequency Tables and Pictures of Data, page 2
Using your frequency table, construct a frequency and a relative frequency
histogram labeling both axes.
Table of hours of television watched per week:
11
15 24
34
36
22
20
30
12
32
24
36
42
36
42
26
37
39
48
35
26
29
27
81276
40
54
47
KARKE
31
35
42
75
35
46
36
42
65
28
54 65
28
23
28
23669
34
43 35 36
16
19
19
28212
Using the data above, construct a frequency table according the following
classes:
Number of Hours Frequency Relative Frequency
10-19
20-29
|30-39
40-49
50-59
60-69
70-79
80-89
From the frequency table above, find
a) the lower class limits
b) the upper class limits
c) the class width
d) the class boundaries
Statistics 300
Frequency Tables and Pictures of Data, page 2
Using your frequency table, construct a frequency and a relative frequency
histogram labeling both axes.
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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