Collecting, Analyzing, and Interpreting Quantitative Data

  • Add to list Added to list Added
  • Cite
  • Share
  • Embed
  • Download PDFopens in new window


The Designing Your Research Project Skill presented a variety of different designs: some that generate data in word form (qualitative data), others that generate data in numeric form (quantitative data). This Skill focuses on the latter, exploring how best to collect, analyse, interpret, and present quantitative data. The aim of this Skill is to give you a core understanding of fundamental principles of collecting, analysing, and interpreting quantitative data, so that you can ask key questions, know when you need to seek additional advice, and then make good decisions. Overall, you should gain an increased confidence in understanding a wide range of issues surrounding quantitative data.

There are some myths about quantitative data that would be best to clear up right away. The first myth is that the term ‘quantitative’ denotes a research design; in actuality, there is no such thing as ‘quantitative research’. As discussed in the Designing Your Research Project Skill, there are a wide range of designs that you can use to collect quantitative data. Often, the use of quantitative data is associated with a positivist or post-positivist paradigm, although this is not always the case.

Another myth to bust is the primacy of numerical data. However, just because something is numeric does not make it any more or any less important in a research sense than data collected in word form. Different types of data answer different types of research questions, and to understand most phenomena more fully, it is helpful to have as broad an understanding of the different types of research designs used to explore them and to learn to interpret the full range of types of data collected from these.

Importantly, interpretation of quantitative data is always linked to the design. How the data were collected and how they were analysed is critical to one’s ability to generalise the results to then make any predictions based on the data. Unless you understand the research design, data collection, and analysis, the numbers alone are meaningless. Therefore, this Skill focuses on how decisions about design, data collection, and analysis influence understanding and interpretation of quantitative data so that you are able to make the best choices in your own research as well as to better interpret studies of others involving the use of quantitative data.

Did You Know?

There’s a glossary of terms and concepts available for this entire Module in the Beginning Your Research Skill.

Suggested Readings
Fielding, J., & Gilbert, N. (2006). Understanding social statistics. Sage.
Levitt, S. D., & Dubner, S. J. (2007). Freakonomics: A rogue economist explores the hidden side of everything. Penguin Publishing.
Stone, D. (2020). Counting: How we use numbers to decide what matters. Liveright Publishers.
Urdan, T. C. (2016). Statistics in Plain English (
4th ed.
). Routledge.
Warne, R. T. (2020). Statistics for the social sciences: A general linear model approach (
2nd ed.
). Cambridge University Press.