The Three Main Approaches
Choosing the right approach depends on your research problem. If your problem is about measuring an effect, you need numbers. If it is about understanding a lived experience, you need words.
Side-by-Side Comparison Table
| Feature | Quantitative Research | Qualitative Research | Mixed Methods Research |
|---|---|---|---|
| Purpose | To test hypotheses, measure variables, and identify relationships | To explore meanings, experiences, and perceptions in depth | To provide comprehensive understanding by combining both |
| Data Type | Numerical (statistics, percentages, scores) | Textual (interview transcripts, field notes, documents) | Both numerical and textual |
| Approach | Deductive (testing a theory) | Inductive (building a theory or exploring) | Pragmatic (what works best for the question) |
| Common In | Psychology, Economics, STEM, Health Sciences | Sociology, Education, History, Nursing | Education, Public Health, Business, Social Work |
| Sample Size | Larger (often 100+) | Smaller (often 15–30) | Depends on phase |
| US Example | Analyzing the correlation between SAT scores and first-year college GPA at a California state university | Exploring how first-generation college students in Texas navigate imposter syndrome | Evaluating a new STEM curriculum in a Chicago high school by measuring test score changes (quant) and interviewing teachers about implementation (qual) |
Quantitative Research Explained
What It Is
Quantitative research deals with numbers and statistics. It measures variables and tests relationships. It is objective, structured, and seeks generalizable findings.
When to Use It
You should use quantitative methods when:
- You need to measure something precisely
- You want to test a hypothesis
- You need to compare groups
- You want to identify statistical relationships
- Your research question starts with "How many," "How much," or "To what extent"
Common Quantitative Designs
- Descriptive: Describes characteristics of a population (e.g., "What is the average GPA of nursing students in Ohio?")
- Correlational: Examines relationships between variables (e.g., "Is there a relationship between study hours and exam scores?")
- Causal-Comparative/Quasi-Experimental: Compares groups without randomization (e.g., "Do students in charter schools score higher than those in public schools?")
- Experimental: Establishes cause and effect through randomization (e.g., "Does a new teaching method improve test scores compared to traditional methods?")
Qualitative Research Explained
What It Is
Qualitative research deals with words, meanings, and experiences. It explores complex phenomena in depth. It is subjective, flexible, and seeks rich understanding rather than generalization.
When to Use It
You should use qualitative methods when:
- You need to understand experiences or perceptions
- The topic is under-researched or complex
- You want to hear participant voices
- You are building theory
- Your research question starts with "How do individuals experience" or "What does it mean"
Common Qualitative Designs
- Phenomenology: Understands the essence of a lived experience (e.g., "What is the experience of being a first-generation college student?")
- Ethnography: Studies cultural groups in natural settings (e.g., "What is the culture of a rural Appalachian high school?")
- Case Study: In-depth examination of a single case or bounded system (e.g., "How did one urban school successfully implement project-based learning?")
- Grounded Theory: Develops theory from data (e.g., "What theory explains how nurses cope with burnout?")
- Narrative Inquiry: Explores individual stories and life experiences (e.g., "What are the career narratives of women in STEM?")
Mixed Methods Research Explained
What It Is
Mixed methods combines quantitative and qualitative approaches. It provides a more complete understanding than either alone. It is pragmatic and recognizes that complex research questions need multiple perspectives.
When to Use It
You should use mixed methods when:
- One data source is insufficient
- You need to explain quantitative results with qualitative stories
- You want to develop better instruments
- You need both breadth and depth
- Your research question has multiple layers
Common Mixed Methods Designs
- Convergent Parallel: Collect both types of data simultaneously, analyze separately, then compare (e.g., Survey 500 teachers and interview 20 about the same topic to see if stories match statistics)
- Explanatory Sequential: Collect quantitative data first, then qualitative to explain results (e.g., Find a surprising survey result, then interview participants to understand why)
- Exploratory Sequential: Collect qualitative data first to explore, then quantitative to measure (e.g., Interview first to identify key themes, then develop a survey to measure them in a larger population)
How to Choose the Right Methodology for Your US Study
Ask yourself these questions to guide your decision:
1. What is the state of knowledge on my topic?
- If the topic is well-researched with established theories (e.g., consumer behavior), a quantitative approach is likely suitable.
- If the topic is under-researched or complex (e.g., the experience of veteran reintegration into civilian workplaces), a qualitative approach is better for generating deep insights.
- If you need both breadth and depth, mixed methods is the strongest choice.
2. What are my research questions?
- Questions starting with "How many?", "To what extent?", or "What is the relationship?" point toward quantitative methods.
- Questions starting with "How do individuals experience...?" or "What does it mean to...?" point toward qualitative methods.
- Questions that have both components point toward mixed methods.
3. What are the expectations in my discipline?
- In US academia, quantitative methods are dominant in hard sciences and economics.
- Qualitative methods are well-established in humanities, anthropology, and nursing.
- Mixed methods are increasingly popular in education and public health for their ability to provide a "complete picture."
4. What are practical constraints?
- Time: Qualitative research takes more time per participant.
- Money: Large surveys cost money for incentives or platform access.
- Access: Can you access enough participants for a quantitative study? Can you access the right participants for in-depth qualitative work?
Common Mistakes to Avoid
- Confusing "Methodology" with "Methods": Methodology is the rationale; methods are the tools.
- Choosing a Method First: Do not pick a survey just because you like surveys. The research question should dictate the method.
- Ignoring the Literature: Your methodology should be justified by citing similar, successful studies in your field.
- Being Defensive: Do not apologize for your choice. Justify it confidently.
- Forgetting Ethics: All methods must be implemented ethically, with IRB approval and participant protection.
Frequently Asked Questions
How do I know if my dissertation should be qualitative or quantitative?
Look at your research goal. If you need to measure something, compare groups, or test a hypothesis (e.g., "Does X cause Y?"), go quantitative. If you need to understand a process, explore a complex issue, or hear personal stories (e.g., "What is it like to experience X?"), go qualitative. If you want to do both, choose mixed methods. Also check your discipline's norms.
I'm doing a mixed-methods study. Do I need two literature reviews?
No, you need one comprehensive literature review that covers both the quantitative and qualitative aspects of your topic. However, your methodology chapter will have two distinct sub-sections: one detailing the quantitative strand (sample, instruments, analysis) and one detailing the qualitative strand (sample, interviews, analysis), followed by a section explaining how you will integrate the two datasets. The integration section is critical — it explains how the two strands "talk" to each other to provide a complete answer to your research question.
Continue to the next guide: Part 2: Sampling Techniques and Data Collection →