The dominant methodological approach in psychological research has involved the use of quantitative methods within a positivist framework. In this article we argue that both qualitative and quantitative methods have their strengths and limitations, depending on the research question under investigation. We examine some of the advantages of qualitative methods, paying particular attention to the value of such methods for feminist researchers. We challenge the positivist assumption that all research should be apolitical and value-free, arguing that the political context in which all research studies take place plays an important role in decisions about the appropriate research methods to use. Despite the value attached to qualitative methods by feminist researchers, there may be projects for which quantitative methods, or a combination of qualitative and quantitative techniques, are more suitable. We draw on examples from our research on the transition from school to the job market for young people, and a study of 16-to 19-year-old first time mothers to illustrate these points, examining the practical implications of our arguments for applied social psychology research.
Key words:Qualitativeequantitative relationship, feminist research, applied social research, appropriate methods, racism, political context.The dominant positivist approach to doing research from a psychological perspective treats researchers as apolitical, emotionally distanced, and unbiased beings who apply the techniques of the natural sciences to the study of human behaviour through the use of the scientific method. Researchers are assumed to select topics for investigation on the basis of theoretical and empirical interest, then develop a set of hypotheses from current research in the area, before identifying specific variables and populations of 'subjects' for isolation and study. Information about these variables (such as employment history, psychological well-being, or attitudes to child care) are generally recorded in numerical or 'quantitative' terms on standardized measures