The most common argument made by researchers for thinking that differences among IQ scores between races might be genetic is flawed (see previous post), but, in case you find yourself slipping back to thinking it’s plausible that the differences between races in average scores is genetic, take note of the following lesson from a statistics textbook by Lindman:
Consider a case of high school students’ test scores in algebra viewed in relation to their teacher and school. The students within a school are randomly assigned to a teacher in their usual school. Lindman notes that a significant difference among school averages “is likely to be interpreted as due to differences in physical facilities, administration, and other factors that are independent of the teaching abilities of the teachers themselves… [However, d]ifferences between teachers in different schools are part of the [average school difference], and the observed differences between schools could be due entirely to the fact that some schools have better teachers [or] some schools have smarter children attending them” (Lindman 1992, 194).
(Lindman could have added that the observed differences between schools could be due entirely to combinations of factors, such as students responding worse to teachers whose attention is distracted because their school’s administrators insist more on detailed documentation of student performance, and so on.)
In any case, analysis of data cannot help researchers hypothesize about factors causing the difference in the average scores from one school to the next when the teachers are replicated (in their students’ test scores) only within schools.
To translate this into the concerns of this talk, researchers cannot hypothesize about factors causing the difference in the average scores from one race to the next when all individuals in one race are never raised as individuals of another race—we can’t take a pair of identical twins and randomly assign them to be treated, say, as Asian-American and African American.
Lindman, H.R.: 1992, Analysis of Variance in Experimental Design, Springer-Verlag, New York.