Understanding research design
Research design is your plan for how you'll collect, analyze, and interpret data to answer your research questions. It must align with your field, your questions, and your access to resources.
Quantitative research design
Quantitative research uses numerical data and statistical analysis. Common in sciences, engineering, business, economics, psychology.
Characteristics
- Large sample sizes
- Numerical data that can be statistically tested
- Objective measurement
- Hypothesis testing
- Reproducibility (same methods should yield similar results)
Qualitative research design
Qualitative research explores meaning, context, and human experience through text, interviews, observations, and thick description. Common in sociology, anthropology, education, cultural studies.
Characteristics
- Small, purposeful samples
- Text or observational data
- Interpretive analysis
- Depth over breadth
- Context-dependent findings
Mixed methods combine quantitative and qualitative approaches — use quantitative data to answer "how much" and qualitative to answer "why." Common in public health, education policy, organizational research.
Choosing your design
| Research Question | Best Approach |
|---|---|
| Does X predict Y? (correlation) | Quantitative |
| What does X mean to participants? | Qualitative |
| How much and why? | Mixed methods |
Need help designing your study?
Our dissertation advisors review your methodology and ensure it aligns with your research questions.
Common design pitfalls
- Misalignment: Quantitative questions paired with qualitative design (or vice versa)
- Scope creep: Mixed methods that tries to do too much without clear purpose
- Sampling problems: Sample size too small (qualitative) or biased (quantitative)
- Unclear procedures: Methods section too vague to be replicated