Although not considered a particular creative area of writing, research is of course important, and in terms of essays this often involves doing a lot of reading and then citing where your ideas came from. However, when it comes to the generation of new theories and ideas, it may not be enough to simply combine and compare the conclusions of others, but to analyse data and create new models from scratch. So, dry as it may be, this entry will take some time to discuss some different types of data.
Qualitative VS Quantitative
Simply put, qualitative research is interested in the ‘what’, the details of something, the qualities of something with no respect to the frequency in which phenomena occur. It aims to discover trends in thought and opinion, and creates a deeper but focused analysis of a specific thing or area. Within the creative fields appropriate to myself, qualitative analysis of data crops up far more often, as there is a greater preoccupation with the effects and feelings of what is being created and discussed.
Quantitative is the rawest of ‘data’, numbers cataloguing trends and measurable quantities, quantitative data most easily translates into statistics and graphs, and can cover an extremely wide area of surface detail. Quantitative data is preferred in some ways because things that are able to be measured objectively cannot be ‘lies’, the main concern is in the ‘accuracy’ of the data, referring to errors that may occur in gathering it in the first place, the margins of which are estimated and included as part of the results.
It is also worthwhile to make the distinction that each, qualitative and quantitative, methods both imply a complete absence of the other. For example, a qualitative analysis does not consider how frequently the representation of things occur, a quantitative analysis does not consider the differences in the form of the things it is counting, and since these definitions are so prescriptive and limiting, it therefore follows that an effective piece of research features a combination of these different types of data.
Obvious, but worth keeping in mind, for my own awareness of how I approach research.