But how will you collect it?
- In this explanation, we'll discuss the various sources of data and the methods of data collection used in sociology.
- We'll start by introducing the sources of primary data and methods of primary data collection.
- Next, we'll explore secondary data sources that are used in social science research.
- Lastly, we'll take a look at the difference between sources of quantitative data and sources of qualitative data.
What are sources of data collection?
The most fundamental question in research is, 'How do researchers obtain information that they further analyse and draw wider conclusions from?' The answer is, 'By asking the right questions in the right format and the right setting'. In other words... through sources of data and data collection!
The methods of collecting the data are your sources of data. You can also use the term research instruments when referring to sources of data.
One of the most important distinctions to make when it comes to data is that between primary data and secondary data. The choice to opt for either one or both of these will depend on your research considerations (i.e., nature of your research, philosophical, practical, and ethical considerations).
Sources of primary data
Primary data is that which had not been previously generated. It's collected at the time of research by the researcher themselves. We can refer to sources of primary data as primary research methods.
Primary data collection
Let's take a look at some examples of sources of primary data collection.
Experiments can be conducted in laboratories or in real-world (or 'field') settings. The point of experiments is to establish correlation and/or causation between multiple variables.
Social surveys are a popular method of data collection both within and outside sociology. They involve systematically collecting data from a large sample in order to gather information and establish relationships between multiple variables.
A questionnaire is a list of questions, and it is the main way of collecting data in social surveys. They can either be administered online or in-person, in the form of pen-and-paper tasks or structured interviews.
Interviews are also a valuable research tool in the social sciences, because they allow researchers to gain insight into social issues, as well as how research subjects themselves perceive those issues. Interviews can be structured, semi-structured or unstructured. They are also sometimes conducted in groups.
Observations allow the researcher to be immersed in the environment that they are studying. Whether they are conducting a participant observation or non-participant observation, the researcher can also decide whether they want their presence to be known or not (i.e. whether they conduct an overt or covert observation).
An example of primary data collection is the real-world experiment conducted by Stanley Milgram (1963) who investigated the conflict between personal conscience and obedience to authority.
Fig. 1 - Milgram's obedience experiment. Yale University Manuscripts and Archives
Sources of secondary data
As opposed to primary data, secondary data is that which already exists at the time of research. The researcher does not have to generate it themselves, but rather, can simply collate or analyse data which has already been collected.
Secondary data collection
There are many popular sources of secondary data used in sociology. Some examples include:
Sources of data that are typically described as primary, for example experiments, interviews, questionnaires etc, can be secondary sources too. If someone else conducted them, and you are only looking at the interview transcriptions, results of questionnaires or write-ups of experiments, that would make it secondary research. This is useful if you cannot reach your research subjects.
The choice of your data collection methods depends on your expected outputs, for example, whether they are qualitative or quantitative. In addition, you should choose according to the measures of research quality that we covered in Research Design. These are validity, reliability, generalisability, credibility, and transparency.
Quantitative and qualitative data
Social researchers distinguish between quantitative (i.e., numerical) data outputs and qualitative (i.e., descriptive) data outputs.
Fig. 2 - Sociologists distinguish between qualitative and quantitative data and seek these out depending on the aims of their research.
Sources of quantitative data
Quantitative is data that is presented in the form of numbers. It tends to be used in order to identify relationships between multiple social variables, such as gender and career choices, or social class and educational achievement.
There is a wealth of sources of quantitative data that are very easily accessible. One of the most popular sources of quantitative data among sociologists are official statistics.
Imagine you are investigating the levels of academic attainment in your English class. If you wanted to refine your data to be able to identify trends in academic achievement, you could ask people to complete a mock test and use their numerical scores as your data.
Qualitative sources of data
Qualitative data refers to all data that isn't presented in numbers. Contrary to popular belief, this doesn't just include text. Qualitative sources of data can also be:
- Pictures or images
- Paintings
- Music recordings
- Descriptive data from observational studies
- Written sources like diaries and autobiographies
For a more detailed investigation of academic achievement, you could also ask the teacher to describe their levels in descriptive categories, for example 'low attainment', 'moderate attainment', and 'high attainment'.
Sources of Data - Key takeaways
- Data can be quantitative (i.e., numerical) and qualitative (i.e., descriptive).
- Data collection methods are also known as sources of data or research instruments.
- Data can be collected via primary or secondary data collection methods.
- Primary data is collected first-hand by the researcher themselves, whereas secondary data collection means using the data outputs collected by someone else.
- Choosing appropriate data collection methods translates into a level of research quality that is measurable, using validity, reliability, generalisability, credibility, and transparency of research as criteria.
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