In this guidebook, we have a powerful contribution to social science methodology in a context where methodology is contested, and is therefore "political”: different methodologies can produce quite different results or findings using the same evidence. The evidence in Ragin and Fiss’s book is survey data. Ragin’s has developed for 25 years a way to bridge the case study method and the "large n” statistical study. He calls it the "set analytic method”--making use of fuzzy sets to bridge the divide between quantitative and qualitative methods. Paradoxically, the fuzzy set is a powerful tool because it replaces an unwieldy, "fuzzy" instrument--the variable, which establishes only the positions of cases relative to each other, with a precise one--degree of membership in a well-defined set. Now, with Intersectional Inequality, Ragin and his coauthor, Peter Fiss, show how the method works in application to a very mainstream sociological research topic. That topic, the use of IQ and school achievement tests as predictors of life chances, is advanced here by viewing cases intersectionally, i.e., in terms of the different ways they combine causally relevant conditions. The specific controversy they take up is the famous Bell Curve book of Charles Murray and Richard Herrnstein which argued that IQ is influenced by both inherited and environmental factors. Controversy has gone on for 20 years over which variable has the strongest impact on life changes: education, or test scores, or family background. The centrality, now more than ever, of education to American social and economic policy, compels close re-examination of traditional methods (and the blind spots of the so-called net-effects approach). By use of this sophisticated qualitative comparative analysis, Ragin and Fiss underscore the importance of racial differences in addressing social inequality in America today.