Thesis Research Methods Explained

Choosing your research method is one of the most important - and often most headache-inducing - decisions you'll make when writing your thesis. Which should you choose: a survey or interviews? How many people do you need to ask? How do you analyze the data?

If these questions are causing confusion right now, don't worry - in this article, I'll guide you through the world of research methods and help you select the one that's right for you.

Quantitative vs. Qualitative: What's the Difference?

These two approaches differ fundamentally in the type of data they work with and the questions they seek to answer.

A Simple Example of the Difference

Let's say you're studying employee satisfaction:

See the difference? Quantitative research shows numbers and correlations, while qualitative research provides deeper insights into the whys and hows.

Quantitative Research in Detail

The goal of quantitative research is to answer your research questions with quantifiable data. You analyze using statistical methods, and your results can be generalized to a larger population.

When Should You Choose Quantitative?

• You want to identify correlations and relationships between variables
• You want to test hypotheses
• You need generalizable results
• You're seeking answers to "how much," "how often," or "what's the relationship" types of questions
• The topic is already relatively well-researched (there's something to measure)

Steps for Survey Research

The most common quantitative method is survey research. Here's how to do it:

1. Survey Design

The structure of your survey is critical. Some basic rules:

• Introduction: Brief introduction, purpose of the research, assurance of anonymity
• Demographic questions: Age, gender, education level, etc. (but only what's relevant!)
• Screening questions: If needed, to filter out inappropriate respondents
• Main topics: Questions related to your research questions
• Closing questions: Perhaps an open-ended question for additional comments

2. Question Types

3. Sampling and Sample Size

Two key concepts:

Population: The group your results apply to (e.g., "university students in Hungary," "SMEs in Budapest")

Sample: The part of the population you actually survey

Sampling Methods:

• Random sampling: Everyone has an equal chance of being selected - this is ideal but rarely feasible
• Stratified sampling: You divide the population into groups and select proportionally from each
• Convenience sampling: You survey whoever you can reach - most common for theses, but limited generalizability
• Snowball sampling: One respondent recommends others - useful for specialized populations

4. Data Collection

You can distribute your survey through:

• Online: Google Forms, Microsoft Forms, Typeform, SurveyMonkey
• Social media: Facebook groups, LinkedIn
• Email: If you have an email list
• In person: At schools, workplaces, events

5. Data Analysis

The most common statistical methods in theses:

• Descriptive statistics: Mean, standard deviation, frequency, percentages
• Correlation analysis: Strength of relationship between two variables
• T-test: Comparing means of two groups
• ANOVA: Comparing multiple groups
• Chi-square test: Relationships between categorical variables
• Regression: Causal relationships between variables

Tools: SPSS, Excel (sufficient for basics), R, JASP (free SPSS alternative)

Qualitative Research in Detail

The goal of qualitative research is deeper understanding. You don't collect numbers but rather experiences, opinions, and stories - and you analyze these.

When Should You Choose Qualitative?

• You want to understand a phenomenon more deeply
• You're seeking answers to "why" and "how" questions
• The topic is still under-researched (exploratory research)
• You're examining personal experiences and opinions
• You're studying a smaller, specific group

Interviews

The most common qualitative method. Types include:

• Structured interview: Pre-written questions, you ask everyone the same thing
• Semi-structured interview: You have a question guide but flexibly follow the conversation - most common
• Unstructured interview: Only topics exist, the conversation flows freely

Structure of an Interview Guide

Practical Tips for Interviewing

• Record the interview (voice recorder or phone) - ask permission first!
• Take written notes as well
• Let participants speak - don't interrupt
• Use open-ended questions ("Tell me about..." instead of "Yes or no?")
• Write a summary after the interview while it's fresh in your mind

Focus Groups

Group interviews, typically with 6-10 participants. Particularly useful when:

• You want to learn from participant interactions
• You're interested in opinions and attitudes
• You're examining reactions to a product or service

Case Study

Detailed examination of one case (company, project, person). You can combine multiple data sources:

• Interviews with stakeholders
• Document analysis
• Observation
• Statistical data

Qualitative Data Analysis

Qualitative data analysis is done through coding:

1. Transcription: Writing out interviews verbatim
2. Coding: "Labeling" the text - identifying recurring themes
3. Categorization: Grouping codes into larger themes
4. Pattern seeking: Identifying connections, contradictions, trends
5. Interpretation: What do these patterns mean?

Tools: ATLAS.ti, NVivo, or simply Excel/Word tables

Mixed Methods

Mixed methods combine quantitative and qualitative approaches. This is increasingly popular because it combines the best properties of both.

Types

How Do You Decide Which to Choose?

Some questions to help:

Writing the Methodology Chapter

In your thesis, you must describe your research methodology in detail. This chapter typically includes:

1. Research approach: Quantitative, qualitative, or mixed?
2. Population and sample: Who did you study and how did you select them?
3. Data collection method: Survey, interviews, etc.?
4. Research instrument: What did you use (survey presentation, interview guide)?
5. Data collection process: When and how did it happen?
6. Analysis methods: What statistical or qualitative techniques did you use?
7. Ethical considerations: Anonymity, consent
8. Research limitations: What are the method's weaknesses?

Common Mistakes and How to Avoid Them

Mistake #1: Too few respondents/interviewees

If you only collect 20 surveys, you won't be able to do statistical analysis. If you only conduct 3 interviews, you won't reach saturation.

Mistake #2: Poor question design

Leading or ambiguous questions distort results. "Don't you agree that..." - this is not an objective question.

Mistake #3: Method and research question don't match

If you're seeking the "why," a survey won't provide it. If you want to generalize, 5 interviews aren't enough.

Mistake #4: Not using a validated instrument

If there's already an existing, validated questionnaire for your topic, use it (and cite it). Don't invent your own scales if it's not necessary.

Mistake #5: Hiding limitations

Every research study has limitations. If you honestly describe them (convenience sampling, small sample, etc.), that's not a weakness - it's scientific rigor.

Summary

A good research method isn't the one that's "coolest" - but the one that best fits your research question and your resources. Don't be afraid to choose simple methods if they serve the purpose!

Ensuring Research Quality

Regardless of which method you choose, ensuring the quality of your research is essential. Two key concepts guide this: validity and reliability.

Validity

Validity refers to whether your research actually measures what it claims to measure. There are several types: content validity (do your questions cover the topic adequately?), construct validity (does your measure align with the theoretical concept?), and external validity (can your findings be generalized beyond your sample?). Consider validity at every stage of your research design.

Reliability

Reliability refers to the consistency of your measurements. Would you get similar results if you repeated the study? For surveys, Cronbach's alpha measures internal consistency. For qualitative research, inter-coder reliability shows whether different coders would categorize data similarly. Document how you ensured reliability in your methodology chapter.

Practical Considerations

Beyond methodological soundness, practical factors influence method selection:

• Time constraints: How much time do you have? Interviews and qualitative analysis are more time-intensive than surveys.
• Access to participants: Can you reach your target population? Some groups are harder to access than others.
• Skills and resources: Do you have the skills for statistical analysis? Do you have access to the necessary software?
• Ethical requirements: Does your research require ethics board approval? Some methods may have stricter requirements.
• Advisor expertise: Your advisor can better support methods they know well.

If you have further questions, check out our other articles on survey design and data analysis!