the creation ofintelligence quotient (IQ)tests around the turn of the 20th century.
One development was the theory of evolution, which focuses on individual
differences. For traits like abstract reasoning or language to evolve in a species,
members of predecessor species must differ from one another on that trait.
Only then can natural selection produce an increase in the number of individ-
uals possessing the more adaptive trait. A second development was the grow-
ing acceptance of materialism—the view that what we label mental activity
reflects only brain processes. In this view, any intellectual differences between
people must also be reflected in differences in their brains. A third development
was the rise of psychological experimentation and measurement. Sophisticated
techniques for investigating and quantifying human behavior were being de-
veloped in the experimental laboratories of Europe and North America. Finally,
the industrialized nations had become committed to universal education. But
not everyone seemed to profit very much by formal education. Consequently,
educators became interested in identifying students who might need special
educational intervention.
TheRiseoftheIntelligenceTestingMovement
Francis Galton Francis Galton, Darwin’s cousin and one of the founders of the
intelligence testing movement, was a bright, independently wealthy man who
had a passion for measuring things. He was the first to suggest that fingerprints
be used for personal identification. He measured the degree of boredom at sci-
entific lectures, and tried to find out which country had the most beautiful
women.
Galton, along with his friend Karl Pearson (1867–1936), devised the concept
and formula forcorrelation(see Boring, 1950; Gould, 1981; Hergenhahn, 1986).
As it turns out, the concept of correlation is extremely important to the research
on intelligence. Correlation is a measure of the degree to which two measure-
ments are linearly related. Correlations range betweenþ1and1. A positive
correlation indicates that when scores on one measure increase, scores on the
other measure tend to increase as well. A negative correlation indicates that
when scores on one measure increase, scores on the other measure tend to de-
crease. A lack of correlation between two measures means that when scores on
one measure increase, scores on the other measure tend neither to increase nor
decrease. Height and weight are positively correlated—people who are tall
also tend to be people who weigh more. Smoking and longevity are negatively
correlated—people who smoke more tend to live fewer years. The last digit
of one’s social security number and one’s annual income in dollars are not
correlated—people with higher last digits are not likely to earn more money or
less money.
It is important to note that just because two measures are correlated does not
mean that there is a causal relationship between them. However, if there is a
causal relationship, it is certain that the two measures will be correlated. There
is a positive correlation between the speed with which a sprinter runs and the
number of wins in a track meet. Here the faster speed is the cause of the win-
ning. But there is also a positive correlation between the number of ice cream
cones consumed in New York City on any given day and the number of deaths
780 R. Kim Guenther