Q1-A 20-year study of British male physicians (R. Doll and R. Peto, British Med. J.,

2: 1525-1536, 1976) noted that the proportion who died from lung cancer was

0.00140 per year for cigarette smokers and 0.00010 per year for nonsmokers.

The proportion who died from heart disease was 0.00669 for smokers and

0.00413 for nonsmokers.

a. Describe the association of smoking with lung cancer and with heart disease,

using the difference of proportions, the relative risk, and the odds ratio.

Interpret.

b. Which response (lung cancer or heart disease) is more strongly related to

cigarette smoking, in terms of the reduction in deaths that could occur with

an absence of smoking?

Q2-Table 2.12 comes from one of the first studies of the link between lung cancer

and smoking, by Richard Doll and A. Bradford Hill. In 20 hospitals in London,

UK, patients admitted with lung cancer in the previous year were queried

about their smoking behavior. For each patient admitted, researchers studied

the smoking behavior of a noncancer control patient at the same hospital of the

Table 2.12. Data for Problem 2.16

Lung Cancer

Have Smoked Cases Controls

Yes 688 650

No 21 59

Total 709 709

Based on data reported in Table IV, R. Doll and A. B. Hill, Br. Med. J.,

739-748, September 30, 1950.

same sex and within the same 5-year grouping on age. A smoker was defined

as a person who had smoked at least one cigarette a day for at least a year.

a. Identify the response variable and the explanatory variable.

b. Can you use these data to compare smokers with nonsmokers in terms of

the proportion who suffered lung cancer? Why or why not?

c. Summarize the association, and explain how to interpret it.

Q3-Table 2.14 was taken from the 2002 General Social Survey.

a. Test the null hypothesis of independence between party identification and

race. Interpret.

Table 2.14. Data for Problem 2.19

Party Identification

Race Democrat Independent Republican

White 871 444 873

Black 302 80 43

b. Use standardized residuals to describe the evidence.

c. Partition the chi-squared into two components, and use the components to

describe the evidence.