Which type of data provides information that has been collected by the researcher specifically for the current research project?

Research methods are specific procedures for collecting and analyzing 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 has 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 analyze 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 is 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.

You can also take a mixed methods approach, where you use both qualitative and quantitative research methods.

Primary vs. secondary data

Primary data is any original information that you collect for the purposes of answering your research question (e.g. through surveys, observations and experiments). Secondary data is 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 synthesize existing knowledge, analyze historical trends, or identify patterns on a large scale, secondary data might be a better choice.

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.

Examples of data collection methods

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Methods for analyzing data

Your data analysis methods will depend on the type of data you collect and how you prepare it for analysis.

Data can often be analyzed both quantitatively and qualitatively. For example, survey responses could be analyzed 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 was 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 was collected either:

• During an experiment.
• Using probability sampling methods.

Because the data is collected and analyzed in a statistically valid way, the results of quantitative analysis can be easily standardized and shared among researchers.

Examples of data analysis methods

Frequently asked questions about research methods

What is sampling?

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.