Case Studies Versus Statistics
The table below summarizes the complementarity between case studies and statistical methods.
The main strength of the case study is depth — detail, richness, completeness, and within-case variance — whereas for statistical methods it is breadth.
If you want to understand a phenomenon in any degree of thoroughness — say, child neglect in the family or cost overrun in urban regeneration — what causes it, how to prevent it, etc., you need to do case studies.
If you want to understand how widespread the phenomenon is, how it correlates with other phenomena and varies across different populations, and at what level of statistical significance, then you have to do statistical studies.
If you want to understand both, which is advisable if you would like to speak with weight about the phenomenon at hand, then you need to do both case studies and statistical analyses. The complementarity of the two methods is that simple.
The main strength of the case study is depth — detail, richness, completeness, and within-case variance — whereas for statistical methods it is breadth.
When you think about it, it’s amazing that the separation and antagonism between qualitative and quantitative methods often seen in the literature, and in university departments, have lasted as long as they have. This is what happens when tribalism and power, instead of reason, rules the halls of academia. As such it is testimony to the fact that academics, too, are all-too-human, and not testimony to much else.
The separation between qualitative and quantitative methods is not a logical consequence of what graduates and scholars need to know in order to do their studies and do them well; quite the opposite. Good social science is opposed to an either/or and stands for a both/and on the question of qualitative versus quantitative methods.
When you think about it, it’s amazing that the separation and antagonism between qualitative and quantitative methods often seen in the literature, and in university departments, have lasted as long as they have.
That said, it should be added that the balance between case studies and statistical methods today is biased in favor of the latter in social science, so much so that it puts case studies at a disadvantage within most disciplines. For the time being, it is therefore necessary to continue to work on clarifying methodologically the case study and its relations to other social science methods in order to dispel some of the misunderstandings that exist about case study research. Even more importantly, it is necessary for scholars and students to keep doing high-quality, high-impact case studies.
Read further here; free pdf with full article: “Case Study.”
