Choosing a research method is one of the first big decisions in any study. Should you collect numbers and run statistical tests, or interview people and analyse what they say? Or both? The answer depends on your research question, not on which method seems more impressive.
Quantitative research: measuring and counting
Quantitative research deals with numerical data. It asks questions like how much, how many and how often, and looks for patterns, relationships and differences that can be measured.
Typical methods:
- Structured questionnaires with fixed answer options
- Secondary data such as census tables, district statistical abstracts and crop area records
- Experiments and standardised tests (for example, fitness tests in physical education)
- Statistical techniques such as percentages, correlation, regression, t-tests and indices
Good for questions like:
- How has the area under sugarcane changed in Solapur district over twenty years?
- Is there a relationship between rainfall and jowar yields?
- Do students who use a particular learning method score higher than those who do not?
Strengths: results can be compared and generalised (if the sample is well chosen); findings are precise and testable.
Limitations: numbers may not explain why something happens or how people experience it.
Qualitative research: understanding meaning
Qualitative research explores experiences, opinions, meanings and processes. It asks why and how, and usually works with words, observations or texts rather than numbers.
Typical methods:
- In-depth interviews
- Focus group discussions
- Participant observation and field notes
- Case studies of a village, institution or community
- Analysis of texts, such as novels, poetry, policy documents or newspaper coverage
Good for questions like:
- Why do young people in a village leave farming?
- How do women athletes experience media coverage of their sport?
- How is the theme of agrarian life represented in a particular collection of Marathi poetry?
Strengths: rich, detailed understanding; captures people’s own voices and context.
Limitations: smaller samples, so findings are not usually generalised statistically; analysis requires careful, transparent interpretation.
Mixed methods: the best of both
Many good studies combine the two. For example, a researcher studying self-help groups might survey 200 members to measure changes in income (quantitative) and then interview 15 members to understand how participation changed their decision-making at home (qualitative).
Mixed methods can give a fuller picture, but they require more time and skill. Plan clearly how the two parts will connect.
How to decide
Ask yourself these questions:
- What is my research question? If it involves measuring, comparing or testing, lean quantitative. If it involves understanding experiences or meanings, lean qualitative.
- What data can I realistically access? Reliable secondary data may be available for some topics; others require fieldwork.
- What do I have time and resources for? Large surveys and detailed interviews both take effort, in different ways.
- What is common in my discipline? Look at recent papers in your target journal.
- What skills do I have, or can I learn? Statistical analysis and qualitative coding both need training.
Explain your choice
Whichever method you choose, explain it clearly in your methodology section: why this method suits your question, how you selected your sample, how you collected the data and how you analysed it. Reviewers are far more interested in whether your method fits your question than in which method you used.
— Editorial Team, Imaginative Ink Publications