There are many books that provide students with detailed accounts of the methods that they can use in geographical research, but very few that give much guidance on analysis. Hence, whilst students – both undergraduate and postgraduate – can often undertake a competent piece of empirical data collection, all too often they come unstuck when it comes to how to analyse the data. This note is therefore intended to provide a quick checklist of tips to help with analysis in geographical research, and it is derived particularly from my experiences in helping PhD students to grapple with these issues.
- Do not be beguiled into thinking that there is one definitive way to analyse data – there are many different types of analysis. Thus, positivist approaches focus on ‘explanation’ and ‘prediction’, whereas hermeneutic approaches focus on ‘understanding’; some critical approaches tend to focus on encouraging ‘emancipation’. Whichever approach one adopts, though, there are certain key principles that can generally help to guide analysis.
- Analysis is the way in which researchers choose to make sense of the data. All good research will have some kind of analytical framework, which makes clear to the reader how the author has tried to interpret diversity in the empirical data.
- Analysis must refer back to the conceptual/theoretical framework of the research. Research is about moving knowledge forward. Hence, the analytical chapters of a thesis, must show how the empirical data gathered has enabled the author to make sense of questions raised by the literatures examined in the conceptual or theoretical introductory chapters to a thesis. Analytical chapters must have just as comprehensive a bibliography as the methodological and theoretical chapters.
- Analysis should focus on the ‘why?’ questions. All too often, students tend to concentrate on descriptive questions, such as ‘what?’, ‘where?’, ‘who?’ and ‘when?’ when gathering data, without then going on to ask ‘why?’. Unless ‘why?’ is asked, it becomes very difficult to explain or understand what is actually going on. This applies just as much to asking why particular geomorphological structures are shaped as they are, as to asking why people behave in the ways that they do. ‘How?’ questions fall between these two extremes – they can be used to ‘explain’ ‘how’ something works, but I do still prefer to read about ‘Why?’ as well.
- It can be helpful to think about ‘dependent’ and ‘independent’ variables when trying to shape an analytical framework. Particularly when working within a positivist approach, it is useful to think about one group of variables (the independent ones) explaining the variation and differences in the pattern of the ‘dependent’ ones.
- It is very important to have a good idea about the analytical framework before going out ‘into the field’ to collect data. Unless one has some idea in advance about how the data are actually to be analysed, there is a danger that much redundant data could be gathered or that it will not be possible actually to explain or understand it. Remember the ‘Why?’ questions! This raises important issues to do with the balance between ‘inductive’ and ‘deductive’ approaches. Very little research is either purely deductive or inductive, and there is always an exciting interplay between theoretical and empirical work. Even when the research is heavily inductive, a focus on consistently asking ‘why?’ questions in the field can help to ensure rigorous analysis.
- Analysis is about imposing structure. Very often when one is immersed in exploring the data gathered in empirical fieldwork it is difficult to see any structure in it. Sometimes it is therefore useful to step back and try to look at it in a different way. Asking (and answering!) a simple question, such as ‘What are the three main factors that help to explain this?’, can help to impose structure.
I do hope this is all helpful advice. Please add comments below about the things that you find helpful in undertaking analysis.