All modules in this section distinguished two categories of data: qualitative and quantitative data. Both have advantages and disadvantages when answering social science research questions, and social scientists tend to recommend using them in a complementary manner. Importantly, depending on what type of data we are working with, there are different ways to analyze the data. Data analysis techniques also depend on how sophisticated the researcher is about certain methods. There is more details about qualitative and quantitative methods in the “Designing research’ section of the Toolbox. Some sources separate categorical data from qualitative and quantitative data; categorical data is information that is divided into groups (such as race, gender, etc.).
The following video can help refresh differences between qualitative and quantitative research:
These differences are also summarized in the box below:
Quantitative Data |
Qualitative data |
Information that can be quantified, counted or measured Expressed in numerical value Most common form of quantitative data analysis: statistical analysis |
Information that is descriptive in nature Expressed in terms of text (description) Examples of qualitative data analysis: narrative analysis, content analysis, discourse analysis |
This module gives a basic foundation of data analysis, inviting students to explore these methods further, depending on their own interests.
If we wish to analyse quantitative data, our analysis will be most likely driven by statistical techniques. If we wish to analyse qualitative data, it is important to keep in mind that our analysis will “heavily dependent on the researcher’s analytic and integrative skills and personal knowledge of the social context where the data is collected” (Bhattacherjee 2012, 113). In other words, the analysis phase of qualitative research assumes a great deal of contextual knowledge from the researcher, which may be knowledge of the local culture, language or other social aspects. Also, qualitative analysis is primarily concerned with explaining and understanding a given phenomenon, while quantitative research may also aim for predicting or generalizing.