Educability-and-Group-Differences-1973-by-Arthur-Robert-Jensen

Multiple and Partial Correlation Methods 205
(1) The multiple correlation, R EI, between a number of environmental
measures (E) and intelligence (I)
(2) The multiple correlation, R er between the environmental
measures and the racial dichotomy treated as a quantized
variable
(3) The point-biserial correlation, rRI, between the racial dichotomy
and intelligence.
From these three correlations we can then obtain partial
correlations, that is, correlations between each pair of variables
with the effects of the third statistically held constant. Unfortunately,
there are no data in the literature which permit the optimal
use of this method, which consists of having multiple correlations
of a large number of environmental variables with IQ and race.
But we can illustrate the method using a single composite measure
of the environment. A study by Tenopyr (1967) is interesting
because it involves control of SES both by selection of subjects
and by statistically partialling out SES from the correlations
between race and abilities. The subjects were 167 Negro and white
machine-shop trainees recruited from the low socioeconomic areas
of the community (Los Angeles). They had an average of 11*9
years of education and their mother’s average education was 11*1
years. The whites were slightly but not significantly lower than
the Negroes on a composite SES index based on the education
of the subject, his mother’s education, and the status level of his
father’s job. In addition to the SES index, three ability tests were
given to all subjects: Verbal Comprehension (V), Numerical
Ability (N ), and Spatial Visualization (S ). The correlations among
all the variables are as follows:
N S Race SES
Verbal (V) 0-30 0-11 0-27 0-21
Numerical (N) 0-21 0-18 014
Spatial (S ) 0-21 0-04
Race* -0-09
* Negro = 0, W hite = 1
From these above correlations, we can obtain the following partial
correlations:3