314 CRITIQUE OF The Bell Curve
are not biased—in the statistician's definition. Lack of S-bias means
that the same score, when achieved by members of different groups,
predicts the same consequence—that is, a black person and a white
person with an identical IQ score of 100 will have the same probabil-
ities for doing anything that IQ is supposed to predict. (I should
hope that mental tests aren't S-biased, for the testing profession isn't
worth very much if practitioners can't eliminate such an obvious
source of unfairness by careful choice and framing of questions.)
But V-bias, the source of public concern, embodies an entirely
different issue that, unfortunately, uses the same word. The public
wants to know whether blacks average 85 and whites 100 because
society treats blacks unfairly—that is, whether lower black scores
record biases in this social sense. And this crucial question (to which
we do not know the answer) cannot be addressed by a demonstration
that S-bias doesn't exist (the only issue treated, however correctly,
by The Bell Curve).
- Content: As stated above, virtually all the data in The Bell Curve
derive from one analysis—a plotting, by a technique called multiple
regression, of the social behaviors that agitate us, such as crime,
unemployment, and births out of wedlock (treated as dependent
variables), against both IQ and parental socioeconomic status
(treated as independent variables). The authors first hold IQ con-
stant and consider the relationship of social behaviors to parental
socioeconomic status. They then hold socioeconomic status constant
and consider the relationship of the same social behaviors to IQ. In
general, they find a higher correlation with IQ than with socioeco-
nomic status; for example, people with low IQ are more likely to
drop out of high school than people whose parents have low socio-
economic status.
But such analyses must engage two issues—form and strength of
the relationship)—and Herrnstein and Murray only discuss the issue
that seems to support their viewpoint, while virtually ignoring (and
in one key passage almost willfully and purposely hiding) the other
factor that counts so profoundly against them. Their numerous
graphs only present the form of the relationships—that is, they draw
the regression curves of their variables against IQ and parental so-
cioeconomic status. But, in violation of all statistical norms that I've
ever learned, they plot only the regression curve and do not show the
scatter of variation around the curve, so their graphs show nothing