In #15, the regression equation should be: In μ= ß₁ + ẞ₁ Int+ ẞ2x where x = 0 for Company A and x = 1 for Company B. 15. Employee accident numbers in two large manufacturing companies (A & B) were compiled over a two-year period with the intention of com- paring rates between the two companies and looking for trends over time. The unit of time used was two months, with the results over two years appearing in Table 7.12. The Poisson distribution is a natural one to consider for counting accident data of this type. Although no information is provided here on exposure of the companies to accidents (such as number of employees), it would normally be of interest. For example, if Company B had twice as many employees as Company A (and otherwise working conditions were similar), then we might natu- rally expect the accident rate in Company B to be approximately twice that of Company A. Exposure information of this type can be taken into consideration in GLM modeling through the use of offset parameters. TABLE 7.12 Industrial accidents over time in companies A and B. Time Period (Unit = 2 Months) Company A Company B 12 19 14 8 1 2 3 4 5 6 10 18 11 6 7 8 9 10 11 12 19 13 19 17 21 16 21 15 23 27 19 29 37 27 35 26 PROBLEMS 263 A plot of the data reveals a slight upward trend in accidents over time for both companies. Consider and analyze a multiplicative model where the accident rate is proportional to time for each company, or in other words, that logµ = 0 + ẞ₁ logt + xc where xc is an indicator for company.
In #15, the regression equation should be: In μ= ß₁ + ẞ₁ Int+ ẞ2x where x = 0 for Company A and x = 1 for Company B. 15. Employee accident numbers in two large manufacturing companies (A & B) were compiled over a two-year period with the intention of com- paring rates between the two companies and looking for trends over time. The unit of time used was two months, with the results over two years appearing in Table 7.12. The Poisson distribution is a natural one to consider for counting accident data of this type. Although no information is provided here on exposure of the companies to accidents (such as number of employees), it would normally be of interest. For example, if Company B had twice as many employees as Company A (and otherwise working conditions were similar), then we might natu- rally expect the accident rate in Company B to be approximately twice that of Company A. Exposure information of this type can be taken into consideration in GLM modeling through the use of offset parameters. TABLE 7.12 Industrial accidents over time in companies A and B. Time Period (Unit = 2 Months) Company A Company B 12 19 14 8 1 2 3 4 5 6 10 18 11 6 7 8 9 10 11 12 19 13 19 17 21 16 21 15 23 27 19 29 37 27 35 26 PROBLEMS 263 A plot of the data reveals a slight upward trend in accidents over time for both companies. Consider and analyze a multiplicative model where the accident rate is proportional to time for each company, or in other words, that logµ = 0 + ẞ₁ logt + xc where xc is an indicator for company.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.4: Distributions Of Data
Problem 19PFA
Related questions
Question
Please assist with the following questions with the answers
Transcribed Image Text:In #15, the regression equation should be:
In μ= ß₁ + ẞ₁ Int+ ẞ2x where x = 0 for Company A and x = 1 for Company B.
Transcribed Image Text:15. Employee accident numbers in two large manufacturing companies (A
& B) were compiled over a two-year period with the intention of com-
paring rates between the two companies and looking for trends over
time. The unit of time used was two months, with the results over two
years appearing in Table 7.12. The Poisson distribution is a natural
one to consider for counting accident data of this type. Although no
information is provided here on exposure of the companies to accidents
(such as number of employees), it would normally be of interest. For
example, if Company B had twice as many employees as Company A
(and otherwise working conditions were similar), then we might natu-
rally expect the accident rate in Company B to be approximately twice
that of Company A. Exposure information of this type can be taken into
consideration in GLM modeling through the use of offset parameters.
TABLE 7.12
Industrial accidents over time in companies A and B.
Time Period (Unit
=
2 Months)
Company A
Company B 12 19 14
8
1 2 3 4 5
6 10 18 11
6 7 8 9
10
11 12
19
13 19 17
21
16 21
15
23
27
19
29
37 27
35 26
PROBLEMS
263
A plot of the data reveals a slight upward trend in accidents over time
for both companies. Consider and analyze a multiplicative model where
the accident rate is proportional to time for each company, or in other
words, that logµ = 0 + ẞ₁ logt + xc where xc is an indicator for
company.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by step
Solved in 2 steps with 6 images
Recommended textbooks for you
Glencoe Algebra 1, Student Edition, 9780079039897…
Algebra
ISBN:
9780079039897
Author:
Carter
Publisher:
McGraw Hill
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Algebra
ISBN:
9781680331141
Author:
HOUGHTON MIFFLIN HARCOURT
Publisher:
Houghton Mifflin Harcourt
Glencoe Algebra 1, Student Edition, 9780079039897…
Algebra
ISBN:
9780079039897
Author:
Carter
Publisher:
McGraw Hill
Big Ideas Math A Bridge To Success Algebra 1: Stu…
Algebra
ISBN:
9781680331141
Author:
HOUGHTON MIFFLIN HARCOURT
Publisher:
Houghton Mifflin Harcourt