TABLE · E11-14 Fastener Failure Data Load, x (psi) Sample Size, n 2500 Number Failing, r 10 50 2700 70 17 2900 100 30 21 3100 60 3300 40 18 3500 85 43 3700 90 54 3900 50 33 4100 80 60 4300 65 51 a. Fit a logistic regression model to the data. Use a simple linear regression model as the structure for the linear predictor. b. Is the logistic regression model in part (a) adequate?
TABLE · E11-14 Fastener Failure Data Load, x (psi) Sample Size, n 2500 Number Failing, r 10 50 2700 70 17 2900 100 30 21 3100 60 3300 40 18 3500 85 43 3700 90 54 3900 50 33 4100 80 60 4300 65 51 a. Fit a logistic regression model to the data. Use a simple linear regression model as the structure for the linear predictor. b. Is the logistic regression model in part (a) adequate?
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
100%
The compressive strength of an alloy fastener used in aircraft construction
is being studied. Ten loads were selected over the range 2500–4300 psi, and a number of fasteners
were tested at those loads. The numbers of fasteners failing at each load were recorded. The
complete test data are shown in Table E11-14.

Transcribed Image Text:TABLE · E11-14 Fastener Failure Data
Load, x (psi) Sample Size, n
2500
Number Failing, r
10
50
2700
70
17
2900
3100
00
30
60
21
3300
40
18
3500
85
43
3700
90
54
3900
50
33
4100
80
60
4300
65
51
a. Fit a logistic regression model to the data. Use a simple linear regression model as the
structure for the linear predictor.
b. Is the logistic regression model in part (a) adequate?
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