Qualitative and Quantitative Research Methods

The research question is settled, the literature review is drafted, and then the supervisor asks the one thing that stalls a dissertation for weeks: how exactly are you going to investigate that?

Research methods are the systematic procedures you use to collect and analyse data in an empirical piece of work. Whether you choose qualitative or quantitative research methods is decided by your research question and not by taste: qualitative and quantitative research methods differ in what they are built to deliver, so a question about measuring and generalising points to quantitative work, and a question about understanding a poorly researched phenomenon points to qualitative work. By the end of this guide you can justify that choice in three sentences.

📌 Key points at a glance

• Every choice of method is two choices: collection and analysis.
• Qualitative methods understand a phenomenon, quantitative methods measure it.
• The research question decides the method, never the reverse.
• Deduction tests an existing theory, induction builds a new one.
• Mixed methods combines both routes inside one project.

What are research methods?

A research method is a rule governed and openly documented procedure for producing and analysing data. Rule governed means the rules are fixed before the data arrives and every departure from them is written down.

British methods teaching rarely opens with the qualitative and quantitative split. Research design comes first, and the choice between the two approaches sits inside it. The Skills for Learning pages of Leeds Beckett University on research design treat the design as the framework for the whole project and list approach, data collection, sampling, analysis and ethics as its parts.

Openness is the half of the definition your marker reads. Ten conversations with friends turn into an interview study only once you state how the people were selected and how the material was ordered.

Method, methodology and the methods chapter

Three similar words, three different meanings, and a standard query in supervision. A method is the single procedure, for example the semi structured interview. Methodology asks why a procedure produces valid knowledge at all. Your methods chapter describes and justifies the procedures you used.

What a usable methods description looks like

A simple test helps: hand the chapter to somebody on your course and ask whether they could run the study from it. Every point where that reader has to ask you something is a missing sentence.

A method is worth exactly as much as its description is reproducible.

The difference between qualitative and quantitative research methods

The difference between qualitative and quantitative research methods lies in the goal of the enquiry and not in the amount of data. Quantitative procedures measure fixed characteristics across many cases and test whether a suspected relationship holds statistically. Qualitative procedures reconstruct, across few cases, how people interpret something and why they act as they do.

Almost everything else follows from that goal: the form of the questions, the size and selection of the sample, and the type of analysis.

One misunderstanding survives almost every study guide: that quantitative automatically means representative. Representativeness is decided by the selection procedure, not by the number of respondents. A survey with 800 answers from your own course is quantitative, cleanly analysable and still not representative of students in the United Kingdom. How a defensible selection is built is set out in the guide to the sample and its size.

Collection and analysis: two decisions, not one

A choice of method always consists of two decisions: how you obtain your data and how you analyse it. Collection methods produce material, analysis methods order and interpret it, and both can be combined fairly freely.

A third level often lands in the same pot: the research design. Design fixes the period, the number of groups and the arrangement in which anything is collected at all.

Why the split matters in your methods chapter

Study guides often list the semi structured interview next to thematic analysis as though the two were alternatives. Alternatives they are not. The interview produces transcripts, and thematic analysis is one of several ways of analysing them. Treating both as one thing costs you a justification, and that gap is what gets queried. Which procedures are available is set out in the guide to analysis methods in empirical research.

Secondary analysis: using data that already exists

Not every empirical dissertation collects its own data. Secondary analysis works with material that others collected and counts as a full empirical route. The first stop in the United Kingdom is the UK Data Service and its access conditions, which sort every collection into three levels: open data without registration, safeguarded data after registration and an End User Licence, and controlled data through the SecureLab for accredited researchers.

The level decides your timetable. That service advises students below PhD level to keep to safeguarded End User Licence data for dissertations, states that Secure Access collections are not generally suitable for them, and notes that a Special Licence application can take a couple of months. How a collection of your own runs instead is set out in the guide to data collection.

Deductive and inductive approaches: finding the right answering strategy

Deductive and inductive describe the direction in which you move between theory and data. Deductive work starts from an existing theory, derives a hypothesis from it and tests that hypothesis against your data. Inductive work starts from the observations and builds towards a theory of your own.

A look at the literature is worth having before the qualitative or quantitative decision. Are there robust theories your study can attach itself to, or is the field too thin for that?

Deductive: testing an existing theory

Deductive work begins with a search for a theory that can answer your research question. From it you derive a hypothesis and test that hypothesis on a concrete case, so the aim is to confirm or refute an existing explanation. In undergraduate and taught masters projects the route is usually quantitative.

An example shows the derivation. Suppose your business management dissertation looks at hybrid working and job satisfaction. If the studies you read report that autonomy raises satisfaction and that hybrid working raises perceived autonomy, your hypothesis becomes: the more days worked away from the office, the higher the reported satisfaction.

Inductive: building a theory of your own

Inductive work either lacks a theoretical basis or deliberately avoids looking for answers in the literature first. Instead you observe as openly as possible, find a pattern and develop your own explanation, which makes the approach exploratory. On the same topic that means interviewing staff in one organisation and formulating an assumption somebody else can test.

The pairing of induction with qualitative work and deduction with quantitative work is a rule of thumb. Qualitative content analysis can build categories from the material or apply categories derived from theory, and exploratory quantitative studies run without a prior hypothesis. More on that sits in the guide to deductive and inductive research.

Qualitative research methods: features and examples

Qualitative research methods capture a phenomenon openly and interpretively across few, purposively selected cases. The view of the person taking part and the reasons they give stand at the centre, so the aim is understanding rather than measurement.

• Goal: reconstruct subjective perception and the reasons behind a behaviour rather than establish frequencies.
• Field of use: thinly researched topics and pilot work from which a questionnaire is later built.
• Procedure: open conversations with a few people or with specialists, followed by transcription and systematic coding.
• Example: semi structured interviews with eight sixth form students about why they use one particular platform.

How many cases are enough arrives before every qualitative project. No universally valid number exists, but reference points do: a systematic review by Hennink and Kaiser (2022) in Social Science and Medicine found saturation within 9 to 17 interviews for narrowly defined objectives and relatively homogenous groups, and within 4 to 8 focus group discussions. Saturation means the point at which further conversations produce no new themes. The derivation sits in the guide to qualitative research.

Purposive selection is what makes those numbers work. Eight interviews with people in comparable situations can reach saturation, while eight spread across four countries will not.

Quantitative research methods: features and examples

Quantitative research methods measure fixed characteristics in standardised form across as many cases as possible and analyse the data statistically. Standardised means every participant receives the same questions with the same answer options. Only on that condition can the cases be compared at all.

• Goal: test relationships between characteristics and carry the finding from the sample to the population.
• Field of use: topics with existing theory and missing robust figures for a larger group.
• Procedure: derive a hypothesis from theory, collect in standardised form, then test the hypothesis statistically.
• Example: standardised online survey of 600 sixth form students about the platform they use most often.

For student projects quantitative research is often the faster route, because an online survey delivers many answers quickly and parts of the analysis can be automated. The effort moves forward instead: a badly built questionnaire cannot be repaired afterwards, whereas an interview guide can still be adjusted during the conversation.

Measurement quality decides what the figures are worth. Every item has to capture what your hypothesis is about, and a pilot with ten people exposes ambiguous wording. Building the instrument is covered in the guide to creating a questionnaire.

Mixed methods: both approaches in one project

Mixed methods describes the combination of qualitative and quantitative steps inside one study. Qualitative and quantitative are not camps you have to join.

Leeds Beckett University sets the choice out as one between a mono-method approach, either quantitative or qualitative, and a mixed-methods approach drawing on both. Choosing between them is a design decision, so a combination has to be argued for rather than adopted out of indecision.

All three routes come from the same Leeds Beckett guidance, which also notes that qualitative work suits interactions and perceptions while quantitative work suits frequencies and patterns.

Feasibility decides the rest. Within one dissertation term a small qualitative pilot of four or five conversations is realistic, a full triangulation usually is not. Settling which part carries your research question keeps the write up focused.

Methods of empirical research at a glance

The overview below sorts the common empirical research methods by what they deliver and where they sit in the research process. A method is neither good nor bad in itself, it either fits your question or it does not.

Two rows fall out of line: content analysis and statistical analysis are analysis procedures. Many overview lists still place them in the same column as the interview.

The case study is missing on purpose. Case study is a research design, not a collection procedure: inside one you can interview, observe and analyse documents.

💡 Tip

Copy two rows out of the table: one collection method and one analysis method. That pair is the core of your methods chapter.

When is which method appropriate?

Which method is appropriate is decided by the form of your research question. Questions about frequency and relationship call for a standardised procedure, questions about experience for an open one.

Two decisions sit behind every line of the table below: the procedure itself, and the group of people it is applied to. A British methods chapter marks both separately.

Matching the question to the method

Each form of question has a procedure that fits and a limitation that comes with it. The limitation is no reason to drop the method, it is the sentence that belongs in your limitations section.

Choosing who takes part: probability and non probability sampling

Sampling is split into two families before any technique is named. Leeds Beckett University lists stratified random, multi stage cluster and systematic sampling as the probability types, and quota, purposive and snowball sampling as the non probability types.

The family you pick governs what your results may claim. Probability sampling gives every unit of the population a known chance of selection and carries statistical generalisation; non probability sampling selects deliberately and keeps the findings tied to the people you reached.

What are the advantages and disadvantages of quantitative research methods?

Quantitative research methods deliver comparable, testable figures and scale well, but they say nothing about why somebody answered as they did. Advantage and disadvantage hang on the same feature: standardisation.

What quantitative methods achieve

• Characteristics can be measured precisely and compared between groups.
• Statistical relationships become testable instead of merely asserted.
• Objectivity and reliability can be checked with established coefficients.
• Five hundred answers cost barely more time than fifty.

What you accept in return

• The questionnaire is fixed, spontaneous follow up disappears.
• Misunderstandings on single items go unnoticed.
• Reasons and interpretations stay invisible in the figures.
• A relationship in survey data is not yet a cause.
• Without a clean sample the finding stays with the respondents.

The penultimate line is often shortened into the claim that quantitative work cannot study causes. Wrong, as it happens: the experiment tests causes and is quantitative throughout. A cross sectional survey, by contrast, cannot separate cause from effect.

What are the advantages and disadvantages of qualitative research methods?

Qualitative research methods make reasons, interpretations and unexpected aspects visible, at the price of poorly comparable cases and a laborious analysis. Openness produces both sides.

What qualitative methods achieve

• Data collection adapts to new leads during the conversation.
• Unexpected aspects reach the record in the first place.
• Reasons and interpretations of the respondents become traceable.
• Single cases generate new hypotheses that others can test.

Where it gets uncomfortable

• Cases are comparable with one another only to a limited degree.
• Transcription and coding consume a great deal of time.
• Result quality depends heavily on the interviewing.
• Statistical projection onto a population is not possible.
• Without a documented procedure the analysis looks arbitrary.

The fourth point stems from purposive case selection and not from the method itself. Out of it grows the charge that qualitative work is not objective. Objectivity, reliability and validity come from quantitative test theory and fit open procedures only in part. Qualitative work applies standards of its own, set out in the guide to quality criteria of empirical research.

Building research methods into your dissertation

In a quantitative dissertation the choice of method belongs in the research design chapter, directly after the hypotheses. In a qualitative dissertation the sharpened research question stands there instead, because no hypothesis is tested.

Vocabulary differs across the sector and mixing it up costs marks. A dissertation in the United Kingdom is normally the final project of an undergraduate or taught masters degree, while thesis denotes doctoral work. An oral examination is not part of the taught route either: the University of Sheffield sets out the viva voce as part of postgraduate research examination, so your methods chapter has to stand on the page.

Where the method sits in the structure

The outline below shows the usual build of an empirical dissertation, using a quantitative survey as the example.

1. Introduction. Research question and why the topic matters.
2. Literature review. State of research and theoretical framework.
3. Research design. Hypotheses, method, sample, variables, instrument.
4. Data collection. Fieldwork, period, response rate.
5. Analysis. Procedures and results.
6. Discussion. Interpretation and limitations of your approach.
7. Conclusion. Answer to the research question and open questions.

How to justify the choice in three sentences

Justifying the method is the part many dissertations skip and almost every supervisor asks for. First, what your research question demands. Second, which procedure delivers exactly that. Third, which limitation you accept. An example: the question asks how often a behaviour occurs in a larger group; a standardised survey records that comparably; the reasons behind it stay outside what the design shows.

What has to be settled before the first question

Ethical approval comes before any data. UWE Bristol states that approval is required for research with human participants undertaken by university staff and students, undergraduate and postgraduate alike, and that it has to be in place before any primary data collection begins. A university or college research ethics committee handles the review, and the paperwork usually includes a participant information sheet, a consent form and a data plan. Requirements differ by institution, so the programme handbook and your supervisor are the binding source. The wider process sits in the guide to the fundamentals of empirical research. This guide does not replace legal advice.

⚠️ Important

Programme regulations and your supervisor outrank every guide. Some courses prescribe one procedure or rule another out. Settle that before the first collection, because standardised material cannot be turned back into open material afterwards.

Further reading

The four sources below were checked on 8 September 2026 and each points at the university or the service that produced it.

British sources come first on purpose. Access rules, ethics procedures and degree vocabulary differ between countries, and your chapter is marked against the rules of the institution you are enrolled at.

• Leeds Beckett University, Skills for Learning: Research Design. Design as the framework, the mono-method and mixed-methods choice, probability and non probability sampling. Read the guidance
• UK Data Service: Access levels and conditions. The three access levels and what registration, an End User Licence and the SecureLab involve. Read the conditions
• UK Data Service: Which categories of data are most suitable for me? What students below PhD level should apply for. Read the advice
• UWE Bristol: Why you need ethical approval. When approval is required and at which point of the project it has to be in place. Read the policy

Institutional guidance changes without a new edition number, so record the date you accessed each page.

Conclusion

The choice between qualitative and quantitative research methods is a deduction from your research question and not a matter of principle. Measuring and generalising leads to quantitative work, understanding and reconstructing leads to qualitative work. Keep the second decision in view: collection and analysis are separate steps, and both belong in your methods chapter with a reason attached.

A dissertation is marked on the fit between question, method and claim. A modest design carried out cleanly beats an ambitious one that nobody could repeat.

Where to go next

• The whole sequence from idea to finding: the empirical research process
• Research question still unsettled: research question, thesis and hypothesis
• Method fixed, questionnaire missing: creating a questionnaire
• The overview of the whole field: fundamentals of empirical research

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