55 5.5 A glass bottle manufacturing company has recorded data on the average number of defects per 10,000 bottles due to stones (small pieces of rock embedded in the bottle wall) and the number of weeks since the last furnace overhaul. The data are shown below. Defects per 10,000 Weeks 13.0 4 16.1 5 14.5 6 17.8 7 22.0 8 27.4 9 16.8 10 65.6 ☐☐ Defects per 10,000 Weeks 34.2 11 12 49.2 13 66.2 81.2 87.4 14 15 16 114.5 17 a. Fit a straight-line regression model to the data and perform the standard tests for model adequacy. b. Suggest an appropriate transformation to eliminate the problems encoun- tered in part a. Fit the transformed model and check for adequacy.
55 5.5 A glass bottle manufacturing company has recorded data on the average number of defects per 10,000 bottles due to stones (small pieces of rock embedded in the bottle wall) and the number of weeks since the last furnace overhaul. The data are shown below. Defects per 10,000 Weeks 13.0 4 16.1 5 14.5 6 17.8 7 22.0 8 27.4 9 16.8 10 65.6 ☐☐ Defects per 10,000 Weeks 34.2 11 12 49.2 13 66.2 81.2 87.4 14 15 16 114.5 17 a. Fit a straight-line regression model to the data and perform the standard tests for model adequacy. b. Suggest an appropriate transformation to eliminate the problems encoun- tered in part a. Fit the transformed model and check for adequacy.
College Algebra (MindTap Course List)
12th Edition
ISBN:9781305652231
Author:R. David Gustafson, Jeff Hughes
Publisher:R. David Gustafson, Jeff Hughes
Chapter4: Polynomial And Rational Functions
Section4.6: Rational Functions
Problem 11SC: Find the mean hourly cost when the cell phone described above is used for 240 minutes.
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Transcribed Image Text:55
5.5
A glass bottle manufacturing company has recorded data on the average
number of defects per 10,000 bottles due to stones (small pieces of rock
embedded in the bottle wall) and the number of weeks since the last furnace
overhaul. The data are shown below.
Defects per 10,000
Weeks
13.0
4
16.1
5
14.5
6
17.8
7
22.0
8
27.4
9
16.8
10
65.6
☐☐
Defects per 10,000
Weeks
34.2
11
12
49.2
13
66.2
81.2
87.4
14
15
16
114.5
17
a. Fit a straight-line regression model to the data and perform the standard
tests for model adequacy.
b. Suggest an appropriate transformation to eliminate the problems encoun-
tered in part a. Fit the transformed model and check for adequacy.
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