5 reasons that I will increase the priority of quantitative research in my work.

  1. Qualitative and quantitative research can be integrated epistemologically.

Qualitative and quantitative methods are often taught as synonymous with certain philosophical commitments, quantitative researchers are labelled “positivists”, qualitative ones “constructivist” (Bryman 2008 p. 14). One of the strongest challenges to positivist research is that: ‘academic researchers do not approach a project from a neutral, objective position, but are situated within constructed and historically- rooted, discourses of knowledge and power’ (Kitchin 2000 p. 32). However, if qualitative methods are assumed to construct knowledge from the interactions we’ve had, why would we not assume the same of quantitative methods? The use of stats, in itself, does not imply that we are making objective claims to knowledge – statistics are just as much ‘products of our social arrangements’, and able to be used as reflexively as qualitative data (Best 2001, p. 3).

  1. Using both methodologies can help us to explore causes more thoroughly.

Mahoney and Goertz ‘believe that qualitative and quantitative scholars share the overarching goal of producing valid descriptive and causal inferences’ (2006, p. 228). Where they differ, however, is in their approach to case selection and causal explanation (Mahoney and Goertz 2006). Qualitative research, through investigating a small number of cases in increased detail, results in ‘causal- process observations’ which ‘provide… information about the mechanism and context’ of an outcome (Collier et al. 2010, p. 185). This is useful in ‘explain[ing] specific outcomes in particular cases’ (Mahoney and Goertz 2006, p.242). Quantitative research, on the other hand, generates ‘data- set observations’, which ‘show… patterns of association between variables as well as allow for the estimation of the size of effects’ (Mahoney and Goertz 2006, pp. 241 – 242).  These ‘are especially helpful when one wishes to generalize about average causal effects for a large population. (Mahoney and Goertz 2006, p. 242). However, research can benefit from understanding a social phenomenon in both ways and both perspectives are used to support the findings of the other to produce more convincing and rounded results.

  1. This approach can give new insight into topics.

The types of knowledge generated by statistical and qualitative data, therefore, complement each other. Used together, small scale qualitative research can ‘stimulat[e] larger- N analysis and ‘[l]ikewise… it seems natural to ask [of statistical results] if these results make sense in… individual cases’ (Mahoney and Goertz 2006, p. 231). In this way, adopting quantitative data can give not just a better understanding of causality and help to confirm each other, but also can be used to help generate new questions, theories and topics for qualitative research, and vice versa.

  1. Using quantitative methods gives me new skills.

Learning how to use quantitative methods gives me a wider toolkit for research and unlocks a new set of literature which I would have previously avoided. Without using quantitative research, I would always be limited to only considering evidence which I felt comfortable to interpret. This in effect reduces the literature which you can draw on by half and biases your perspective before you even begin your research.

  1. Finally, learning to use quantitative methods can be fun!

Learning to use SPSS has given me not just a new tool, but has been a novel experience. I now get excited about finding interesting data sets in my spare time!



Bryman, A. (2008). The End of the Paradigm Wars? In: Alasuutari, P. (ed). SAGE Handbook of Social Research Methods. pp. 13 – 26. SAGE Publications.

Best, J. (2001). Telling the Truth About Damned Lies and Statistics. [Online]. The Chronicle of Higher Education. May 4th. Available from: http://www.math.usu.edu/~schneit/STAT3000/PDF/Lies&Stats.pdf [Accessed 12/02/17].

Mahoney, J and Goertz, G. (2006). A Tale of Two Cultures: Contrasting Quantitative and Qualitative Research. Political Analysis. 14. Pp. 227 – 249.

Collier, D. et al. (2010). Sources of Leverage in Causal Inference: Toward an Alternative View of Methodology. In: Brady, H. and Collier, D. (eds). Rethinking Social Inquiry: Diverse Tools, Shared Standards. (2nd ed.). pp. 161 – 201. Lanham: Rowman & Littlefield.

Kitchin, R. (2000). The Researched Opinions on Research: Disabled People and Disability Research. Disability & Society. 15 (1). pp. 25-47.


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