Research Methods | Definition, Types, Examples
Research methods are specific procedures for collecting and analysing data. Developing your research methods is an integral part of your research design. When planning your methods, there are two key decisions you will make.
First, decide how you will collect data. Your methods depend on what type of data you need to answer your research question:
- Qualitative vs quantitative: Will your data take the form of words or numbers?
- Primary vs secondary: Will you collect original data yourself, or will you use data that have already been collected by someone else?
- Descriptive vs experimental: Will you take measurements of something as it is, or will you perform an experiment?
Second, decide how you will analyse the data.
- For quantitative data, you can use statistical analysis methods to test relationships between variables.
- For qualitative data, you can use methods such as thematic analysis to interpret patterns and meanings in the data.
Methods for collecting data
Data are the information that you collect for the purposes of answering your research question. The type of data you need depends on the aims of your research.
Qualitative vs quantitative data
Your choice of qualitative or quantitative data collection depends on the type of knowledge you want to develop.
For questions about ideas, experiences and meanings, or to study something that can’t be described numerically, collect qualitative data.
If you want to develop a more mechanistic understanding of a topic, or your research involves hypothesis testing, collect quantitative data.
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Quantitative |
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You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.
Primary vs secondary data
Primary data are any original information that you collect for the purposes of answering your research question (e.g. through surveys, observations and experiments). Secondary data are information that has already been collected by other researchers (e.g. in a government census or previous scientific studies).
If you are exploring a novel research question, you’ll probably need to collect primary data. But if you want to synthesise existing knowledge, analyse historical trends, or identify patterns on a large scale, secondary data might be a better choice.
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Descriptive vs experimental data
In descriptive research, you collect data about your study subject without intervening. The validity of your research will depend on your sampling method.
In experimental research, you systematically intervene in a process and measure the outcome. The validity of your research will depend on your experimental design.
To conduct an experiment, you need to be able to vary your independent variable, precisely measure your dependent variable, and control for confounding variables. If it’s practically and ethically possible, this method is the best choice for answering questions about cause and effect.
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Examples of data collection methods
Research method | Primary or secondary? | Qualitative or quantitative? | When to use |
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Experiment | Primary | Quantitative | To test cause-and-effect relationships. |
Survey | Primary | Quantitative | To understand general characteristics of a population. |
Interview/focus group | Primary | Qualitative | To gain more in-depth understanding of a topic. |
Observation | Primary | Either | To understand how something occurs in its natural setting. |
Literature review | Secondary | Either | To situate your research in an existing body of work, or to evaluate trends within a research topic. |
Case study | Either | Either | To gain an in-depth understanding of a specific group or context, or when you don’t have the resources for a large study. |
Methods for analysing data
Your data analysis methods will depend on the type of data you collect and how you prepare them for analysis.
Data can often be analysed both quantitatively and qualitatively. For example, survey responses could be analysed qualitatively by studying the meanings of responses or quantitatively by studying the frequencies of responses.
Qualitative analysis methods
Qualitative analysis is used to understand words, ideas, and experiences. You can use it to interpret data that were collected:
- From open-ended survey and interview questions, literature reviews, case studies, and other sources that use text rather than numbers.
- Using non-probability sampling methods.
Qualitative analysis tends to be quite flexible and relies on the researcher’s judgement, so you have to reflect carefully on your choices and assumptions.
Quantitative analysis methods
Quantitative analysis uses numbers and statistics to understand frequencies, averages and correlations (in descriptive studies) or cause-and-effect relationships (in experiments).
You can use quantitative analysis to interpret data that were collected either:
- During an experiment.
- Using probability sampling methods.
Because the data are collected and analysed in a statistically valid way, the results of quantitative analysis can be easily standardised and shared among researchers.
Examples of data analysis methods
Research method | Qualitative or quantitative? | When to use |
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Statistical analysis | Quantitative | To analyse data collected in a statistically valid manner (e.g. from experiments, surveys, and observations). |
Meta-analysis | Quantitative | To statistically analyse the results of a large collection of studies.
Can only be applied to studies that collected data in a statistically valid manner. |
Thematic analysis | Qualitative | To analyse data collected from interviews, focus groups or textual sources.
To understand general themes in the data and how they are communicated. |
Content analysis | Either | To analyse large volumes of textual or visual data collected from surveys, literature reviews, or other sources.
Can be quantitative (i.e. frequencies of words) or qualitative (i.e. meanings of words). |