The Language of Argument

2 3 7

C o n c o m i t a n t V a r i a t i o n

the hypothesis that B does not cause A. Together these manipulations can

reduce the live options to items 3 and 4.

Many scientific experiments work this way. When scientists first discov-

ered the correlation between smoking and lung cancer, some cigarette man-

ufacturers responded that lung cancer might cause the desire to smoke or

there might be a third cause of both smoking and lung cancer that explains

the correlation. Possibly, it was suggested, smoking relieves discomfort due

to early lung cancer or due to a third factor that itself causes lung cancer. To

test these hypotheses, scientists manipulated the amount of smoking by lab

animals. When all other factors were held as constant as possible, but smok-

ing was increased, lung cancer increased; and when smoking went down,

lung cancer went down. These results would not have occurred if some

third factor had caused both smoking and lung cancer but remained stable

as smoking was manipulated. The findings would also have been different if

incipient lung cancer caused smoking, but had remained constant as scien-

tists manipulated smoking levels. Such experiments can, thus, help us rule

out at least some of the options 1–4.

Direct manipulation like this is not always possible or ethically permis-

sible. The data would probably be more reliable if the test subjects were hu-

man beings rather than lab animals, but that is not an ethical option. Perhaps

more complicated statistical methods could produce more reliable results,

but they often require large amounts and special kinds of data. Such data is,

unfortunately, often unavailable.

In each of the following examples a strong correlation, either negative or

positive, holds between two sets of phenomena, A and B. Try to decide whether

A is the cause of B, B is the cause of A, both are caused by some third factor, C,

or the correlation is simply accidental. Explain your choice.

1. For a particular United States president, there is a negative correlation
   between the number of hairs on his head (A) and the population of China (B).


2. My son’s height (A) increases along with the height of the tree outside my
   front door (B).


3. It has been claimed that there is a strong positive correlation between
   those students who take sex education courses (A) and those who
   contract venereal disease (B).


4. At one time there was a strong negative correlation between the number
   of mules in a state (A) and the salaries paid to professors at the state
   university (B). In other words, the more mules, the lower professional
   salaries.^6


5. There is a high positive correlation between the number of fire engines in
   a particular borough in New York City (A) and the number of fires that
   occur there (B).^7

Exercise VI

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