1 8 6C H A P T E R 8 ■ A r g u m e n t s T o a n d F r o m G e n e r a l i z a t i o n sa Canadian quarter in an American vending machine, and it has never worked.
This will increase our confidence in his generalization, but size of sample alone
is not a sufficient ground for a strong inductive argument. Suppose that Harold
has tried the same coin in hundreds of American vending machines, or tried
a hundred different Canadian coins in the same vending machine. In the first
case, there might be something wrong with this particular coin; in the second
case, there might be something wrong with this particular vending machine. In
neither case would he have good grounds for making the general claim that no
Canadian quarters work in any American vending machine. This leads us to the
third question we should ask of any statistical generalization.Is the Sample Biased?
When the sample, however large, is not representative of the population, then it
is said to be unfair or biased. Here we can speak of the fallacy of biased sampling.
One of the most famous errors of biased sampling was committed by a
magazine named the Literary Digest. Before the presidential election of 1936,
this magazine sent out 10 million questionnaires asking which candidate
the recipient would vote for: Franklin Roosevelt or Alf Landon. It received
2.5 million returns, and on the basis of the results, confidently predicted that
Landon would win by a landslide: 56 percent for Landon to only 44 percent
for Roosevelt. When the election results came in, Roosevelt had won by an
even larger landslide in the opposite direction: 62 percent for Roosevelt to a
mere 38 percent for Landon.
What went wrong? The sample was certainly large enough; in fact, by
contemporary standards it was much larger than needed. It was the way the
sample was selected, not its size, that caused the problem: The sample was
randomly drawn from names in telephone books and from club member-
ship lists. In 1936 there were only 11 million payphones in the United States,
and many of the poor—especially the rural poor—did not have payphones.
During the Great Depression there were more than nine million unem-
ployed in America; they were almost all poor and thus underrepresented on
club membership lists. Finally, a large percentage of these underrepresented
groups voted for Roosevelt, the Democratic candidate. As a result of these
biases in its sampling, along with some others, the Literary Digest underesti-
mated Roosevelt’s percentage of the vote by a whopping 18 percent.
Looking back, it may be hard to believe that intelligent observers could
have done such a ridiculously bad job of sampling opinion, but the story
repeats itself, though rarely on the grand scale of the Literary Digest fiasco. In
1948, for example, the Gallup poll, which had correctly predicted Roosevelt’s
victory in 1936, predicted, as did other major polls, a clear victory for Thomas
Dewey over Harry Truman. Confidence was so high in this prediction that
the Chicago Tribune published a banner headline declaring that Dewey had
won the election before the votes were actually counted.97364_ch08_ptg01_177-194.indd 186 15/11/13 10:44 AM
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