Exercise 4.32:
Shown here are the number of auto accidents per year for every 1000
people in each of 40 occupations (Knight Ridder Tribune, June 19,
2004):
| Occupation | Accidents
per 1000 | Occupations | Accidents per
1000 | | Student | 152 | Banking,
finance | 89 | | Physician | 109 |
Customer service | 88 | | Lawyer |
106 | Manager | 88 | | Architect |
105 | Medical support | 87 | | Real
estate broker | 105 | Computer-related | 87 |
| Enlisted military | 99 | Dentist |
86 | | Social worker | 98 |
Pharmacist | 85 | | Manual laborer |
96 | Proprietor | 84 | | Analyst |
95 | Teacher, professor | 84 |
| Engineer |
94 |
Accountant |
84 |
| Consultant |
94 |
Law enforcement |
79 |
| Sales |
93 |
Physical therapist |
78 |
| Military officer |
91 |
Veterinarian |
78 |
| Nurse |
90 |
Clerical, secretary |
77 |
| School administrator |
90 |
Clergy |
76 |
| Skilled laborer |
90 |
Homemaker |
76 |
| Librarian |
90 |
Politician |
76 |
| Creative arts |
90 |
Pilot |
75 |
| Executive |
89 |
Firefighter |
67 |
| Insurance agent |
89 |
Farmer |
43 |
a. Would you recommend using the standard
deviation or the iqr as a measure of variability for this data set?
b. Are there outliers in this data set? If so,
which observations are mild outliers? Which are extreme outliers?
c. Draw a modified boxplot for this data set.
d. If you were asked by an insurance company to
decide which, if any, occupations should be offered a professional
discount on auto insurance, which occupations would you recommend?
Explain.
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