Quantitative or qualitative research

Students often choose a methodology "by feel" — someone said a survey is easier, someone else likes talking to people, a third is afraid of statistics. But methodology isn't a matter of preference. The choice between a quantitative, qualitative, or mixed approach flows from the research question. In other words: the question dictates the method, not the other way around.

In this guide we explain when to use which approach, what techniques exist within each, and how to recognize which fits your situation.

1. Quantitative research — when you measure

Quantitative research uses numerical data and statistical processing. The goal is generalization — how something behaves in a population, what the relationships between variables are, how strongly one affects another.

Typical quantitative questions:

• "Is there a correlation between X and Y?"
• "How often does Z occur in a given population?"
• "Is intervention A more successful than B?"
• "What is the average attitude of students toward..."

Main quantitative methods

• Survey / questionnaire — the most widespread, allows a large sample and statistical processing
• Experiment — manipulation of variables under controlled conditions
• Secondary data analysis — analysis of existing data sets (national statistics, Eurostat, publicly available databases)
• Quantitative content analysis — counting occurrences in texts or media

Advantages

• Ability to generalize to a larger population (with an appropriate sample)
• Objective, repeatable results
• Clear statistical significance criteria
• Easier communication of findings (percentages, coefficients, charts)

Disadvantages

• Doesn't explain why — only "what" and "how much"
• Lacks nuance, context, depth of understanding
• Requires a larger sample for reliable conclusions
• Statistical processing can deter students unaccustomed to it

2. Qualitative research — when you understand

Qualitative research uses textual, visual, and verbal data. The goal is in-depth understanding — how people experience, interpret, and give meaning to phenomena.

Typical qualitative questions:

• "How do young parents experience parental leave?"
• "What processes underlie professional burnout among teachers?"
• "What are entrepreneurs' narratives about success?"
• "What makes a good therapeutic relationship from the clients' perspective?"

Main qualitative methods

• Semi-structured interview — the most common technique, in-depth conversations with 10-20 participants
• Focus groups — group discussion on a given topic (usually 6-10 participants)
• Ethnography / observation — participant or detached observation in a natural setting
• Case study — in-depth analysis of one or a few cases
• Qualitative content / discourse analysis — analysis of texts, media, documents
• Narrative analysis — analysis of stories and personal accounts

Advantages

• Depth of understanding — insight into processes and meanings
• Openness to unexpected discoveries
• Closeness to the phenomenon being studied
• Suitable for under-researched areas

Disadvantages

• Less generalizing power — findings apply to a specific context
• Subjectivity in interpretation (requires methodological rigor)
• Time-consuming — transcription, coding, analysis
• Harder to communicate statistical clarity

"Quantitative questions tell you what. Qualitative questions tell you why. The best research often wants both."

3. Mixed methodology — when you need both

More and more research combines quantitative and qualitative approaches. Typical patterns:

Sequential explanatory

First you run a survey (quant), then use the findings to design interviews (qual) that explain why the results came out as they did.

Sequential exploratory

First interviews (qual) to discover themes and measurement dimensions, then a survey (quant) to test on a larger sample.

Parallel (convergent)

You collect quant and qual data simultaneously, then triangulate them in the discussion — comparing what both say.

4. How to choose?

Ask yourself:

• What are you looking for? Numbers, frequencies, correlations → quantitative. Experiences, meanings, processes → qualitative.
• How large a sample can you reach? Do you have access to a large number of respondents (200+)? → quantitative is possible. Can you talk in depth with 15 people? → qualitative is possible.
• How much time do you have? Qualitative often takes longer due to transcription and analysis.
• What is your comfort zone? Although you shouldn't choose a method based on personal preference alone, realism matters. If you hate statistics, don't base your paper on complex regressions.
• What does the literature say? Check how similar research in the field is conducted. You don't have to follow it, but rely on the common practice of your field.

5. Whatever you choose — be rigorous

Regardless of method, the examination committee values methodological seriousness. That means:

• Justification of why you chose the method (linked to the research question and existing literature)
• A clear description of the procedure — detailed enough that someone else could repeat your research
• Consideration of limitations — no method is perfect, show awareness of the limitations
• Ethical issues — how you ensured consent, anonymity, and data security
• Reliability and validity — for quant: statistical analysis of instrument reliability; for qual: triangulation, audit trail, reflexivity

In conclusion

There is no "better" method — there is a method that fits the question. If you want to know how many people do something, count. If you want to know why they do it, talk. If you want both, consider combining — but be ready for double the effort.

The best advice: before choosing a method, formulate your research question as precisely as possible. Then see which method best gives you the answer. The question always leads the method, never the other way around.