Friday, 28 July 2017

Research Design: qualitative versus quantitative

Our research design is the spirit in which we will make our decisions about the type of data we will collect. It needs to fit with our research philosophy, and fit with our research method, or methods. Some people call this a research strategy, but I know it as the research design.

The research design falls largely into two main clusters: qualitative, or quantitative, or a combination of both, as follows (McLeod, 2008; Veal, 2005):
  1. Qualitative strategies, which look for behaviour (eg, inductive, word, image, sound or video coding, interview, focus group, ethnography, action research)
  2. Quantitative strategies, which look for numerical statistical patterns (eg, deductive, survey, experimental approaches, mathematical modelling, SPSS)
  3. Mixed methods strategies, using some of each (e.g., cross-sectional, cross-sequential or longitudinal studies)
Qualitative data sources include journals, unstructured observations, paintings, film stock, written records, images, historical accounts, reflections, diaries or recordings. It is more normal to take a descriptive approach - to explore feelings, impressions, what is not said, along with what is said, tone, pace and thematic responses - with qualitative data. Because of there being so many more variables than with quantitative data, qualitative data is harder to analyse (McLeod, 2008; Veal, 2005). Thematic analysis using codes - looking for themes within our data set and marking where a theme repeatedly occurs - is a fairly normal way of analysing qualitative data.

Where we have a small data set, qualitative research can be useful. It allows us to explore in depth how people think or feel - using case studies, interviews, focus groups and surveys yielding textual data - and be able to draw some conclusions. However, generalisability is a problem with qualitative studies, as is researcher bias. It can also take quite a long time to gather our data when undertaking qualitative study, as we are dealing with human subjects, and need to take our time to collect good quality data.

Normally, an inductive inquiry strategy is used with a qualitative research design (or qualitative data). It would also be normal to use a subjective research philosophy.

Quantitative data is usually a numeric measure that yields something which can be counted, ranked, categorised, graphed, or statistically analysed using a range of techniques and processes. Sources come from experiments, lab tests, surveys (yielding numerical data) or structured observations. Normally, an deductive inquiry strategy is used with a quantitative research design (or with quantitative data), and an objective research philosophy.

Hopefully that makes the difference between qualitative and quantitative research designs clear!




  1. Replies
    1. Thanks Mitchel, much appreciated: and I am so sorry I didn't reply to your post earlier!

  2. Hi I would like to know if I can use this diagram in a book chapter I am writing? Can you tell me how to get permission to copyright.

    1. Thanks Jessica: this is a construction that I put together myself based on John Creswell's explanation of research method (with elements of Anthony Veal). With regard to copyright, you would need to credit me. I will email you.

  3. I can be reached by email at

  4. This comment has been removed by the author.

  5. Hi, what do you think is the best research design for qualitative research if the instruments that was used are questionnaire and checklist with open ended question?

    1. Good question: surveys are usually considered a quantitative, or a mixed methods, tool. If you took a pragmatic approach, you could use an inductive survey if you used a lot of text answers, or impressions through imgages, rankings, emotional reactions etc, then analysed using qualitative tools.


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