When we see data on a spreadsheet, concepts and methods associated with standard quantitative techniques inevitably come to mind. Usually and by default, we try to make sense of the data by deriving the summary statistics to understand what has gone up or down, we explore associations between factors by identifying correlations, and administer technical tests to see if the results confirm, reinterpret, or nullify our research questions and hypotheses.

But is it possible to look at a dataset “qualitatively”? And what would that imply? Is it possible to look at columns and rows and identify relations and configurations between them that are more than associational? At first glance, the possibility of this approach seems incongruous because we usually associate qualitative methods with text and quantitative methods with numbers.

This chapter introduces the reader to a qualitative approach by providing an overview of the set theoretic methodology and the QCA method. An introduction to the methodology and the method is important not just because it is mostly an unfamiliar method to many social scientists, particularly those who work in the Indian context, but also because, as a methodology, its philosophical and conceptual roots are somewhat distinct from standard social science approaches. And, equally important, because QCA relies on numbers and software codes for analysis, it misconstrues expectations since the use of numbers can inadvertently lead to interpretations based on quantitative reasoning.