There are some pairings in the world that are just meant to be. Milk and cookies, Scooby-Doo and Shaggy, lock and key... But also, scientists and their data.
As a social science, sociology is an incredibly rich discipline. While a lot of that comes from the theoretical perspectives which lay the foundations for the subject, we can attribute a lot of the abundance of empirical sociological knowledge to the researchers who collect and analyse data.
- In this explanation, we will look at various types of data used in sociological research.
- We will start by exploring the various types of data, including primary, secondary and tertiary data.
- Next, we'll examine the difference between quantitative and qualitative data - another key distinction in the social sciences.
- Finally, we'll look at factors that influence choice of data, with reference to the values of validity and reliability.
Different kinds of data in sociology
Researchers collect, analyse and interpret primary and secondary data. Researchers themselves collect primary data, and secondary data is the use of someone else's outputs.
You can choose to use a questionnaire that will collect both quantitative and qualitative data, i.e., questions with numerical answers (respondent's income, for example) and qualitative answers (ask them to describe their socioeconomic status in their own words, for example). You could also ask the same questions during an interview - it is a matter of choosing which method will produce data most suitable for analysis and interpretation.
The figure below shows that both primary and secondary data can be quantitative and qualitative.
Fig. 1 - There are many different types of data
Primary data in sociology: definition
Primary research involves generating data that has not previously been collected or analysed.
If you wanted to find out whether 17-year-olds prefer either pizza or ice cream, you could go ask your friends who are 17 years old. That would constitute collecting primary data.
Examples of primary research methods in sociology (i.e., that yield primary data) include:
Evaluation of primary data
As is the case with all sociological data and their collection methods, there are a number of advantages and disadvantages when it comes to using primary data.
Advantages of primary data | Disadvantages of primary data |
Collected first-hand, so there is no need to rely on other sociologists' figures. It is the most up-to-date data. Can present unexpected findings and steer the research in a new direction. Data collected is unique to the specific research project.
| Some primary methods can be expensive, time-consuming, or even dangerous. Can be unethical if you do not have informed consent from the participants (e.g., cover observations). Researchers' own values may bias the process. The group you may be interested to study may not be accessible (e.g., too far away or may not want to participate).
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Table 1 - Advantages and Disadvantages of primary data.
Secondary data in sociology
Secondary research involves collating and analysing data that has already been generated.
Similarly, if you wanted to find out whether 17-year-olds prefer either pizza or ice cream, you could go online and look for statistics about the food preferences of adolescents.
Examples of secondary data sources include:
Evaluation of secondary data
There are also a number of strengths and limitations to be aware of when it comes to using secondary data in sociological research.
Advantages of secondary data | Disadvantages of secondary data |
Easy access to data (such as the Office for National Statistics website). No need to seek informed consent from the research subjects. Your values will not influence the data as it was collected by someone else.
| If the data is unreliable, unable to be generalised, or invalid, you may have to search for alternative sources. Documents (old paintings or archive documents, for instance) may not be authentic or credible. Official statistics may have a bias. The data you need may not be available in the format that you require.
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Table 2 - Advantages and Disadvantages of secondary data.
Tertiary data in sociology
Tertiary data is not as commonly discussed when it comes to sociological research, but it can be quite important to take note of in certain types of research. Tertiary data include reference materials that have collected and regurgitated other data or information.
Examples of tertiary data sources include:
Textbooks
Manuals
Handbooks
Bibliographies
Guidebooks
Dictionaries
Encyclopedias
While primary, secondary and tertiary data come from various sources and have various uses, the many types of data themselves also have some notable differences. For instance, data can either be quantitative or qualitative. Let's explore what this means.
Examples of data types: quantitative data and qualitative data
Sociological researchers use different forms of data depending on their topic and research objectives. For instance, they may want to consider whether the aim of their research is to measure something numerically or to describe and/or analyse it in detail. This is where sociologists have to decide whether they are seeking quantitative or qualitative data.
Quantitative data is used to measure social phenomena in numerical, statistical or analytical terms. For example, you could measure the height of your classmates in numerical terms (e.g. 162 cm or 175 cm)
Qualitative data is used to describe phenomena examined in categorical terms. Using the same example, you could ask your classmates to describe each other using categories “short”, “medium height” and “tall”.
Types of quantitative data
As we have seen in the example above, quantitative data takes a numerical (or 'number') form.
A sociologist might opt for methods which generate quantitative research if they want to examine social patterns or if they'd like to study the nature and/or strength of a relationship between two or more factors. There are various types of quantitative data, which you will learn more about later on in your academic career. In the meantime, we can take a look at some examples:
- The percentage of a population that is under the age of 18
- The relationship between ethnicity and occupation
- The number of people diagnosed with a particular illness in a given year
- The relationship between wealth and leisure activities
Types of qualitative data
On the other hand, qualitative data is data that is not in numerical form (but is also not necessarily just 'words').
A sociologist might prefer qualitative data if they are looking for an in-depth description and/or analysis of aspects of social life. Types of qualitative data include:
Descriptions of observations
Interview transcripts
Written sources (such as diaries, journals, novels, newspaper articles, etc)
Visual media (including photographs, paintings and videos)
Audio media (such as recorded music)
Some concepts need to be expressed in a way that makes them measurable - we have to operationalise them.
For instance, how might we measure the amount of 'exercise' that a person does? As a researcher, you will likely use indicators or proxy measures, which are typically expressed as quantitative data. For example, you could examine hours of exercise completed by using gym attendance rates, or you could conduct standardised fitness tests at various points and study the difference in results over time.
Triangulation
Some researchers prefer to combine quantitative and qualitative research methods in pursuit of a fuller picture of social phenomena. There are two different approaches that researchers can take here:
Triangulation allows researchers to check whether data collected is valid and reliable by collecting it from two or more different sources. By seeing the same thing from different perspectives, the researcher confirms or challenges their findings of one method through the use of another.
On the other hand, a researcher may adopt a variety of sources due to believing that no single research approach is superior to another. This is methodological pluralism, or a mixed methods approach.
You may choose to observe your participants and then select a purposive sample to conduct questionnaires. This would allow searching for patterns using quantitative data, and unstructured interviews - for context and depth.
Fig. 2 - Research methods include triangulation
Aspects of data quality
Now that we know what questions sociologists ask when it comes to the type and form of the data they are seeking, another important question to ask is the qualities that they want this data to have. Some of the most commonly sought qualities of scientific data are validity and reliability.
Validity
Data is considered to be valid if it accurately presents a particular description, measurement or finding.
For example, many sociologists suggest that Official Statistics on crime are not quite valid, because many crimes (such as white-collar crimes) go unreported. As such, the statistics do not paint an accurate picture of the prevalence of crime.
Reliability
Data is considered to be reliable when, if other researchers were to use the same methods, they would obtain the same results.
For example, a researcher might observe the behaviour of sports fans at a football match in the UK. If another researcher observed the same crowd at the same event, and their results matched those of the first researcher, this data would be considered reliable.
Types of Data - Key takeaways
Researchers can collect data themselves or use data collected by someone else. That is the distinction between primary and secondary data. Both data collection methods have advantages and disadvantages.
Data can also be quantitative (i.e., numerical, statistical) or qualitative (i.e., descriptive, categorical).
Some concepts in sociological research are abstract and need to be operationalised in order to be measured.
Some researchers prefer to use mixed methods. The belief that no single research approach is superior to another is called 'methodological pluralism'.
Triangulation is a mixed-methods technique used to validate the data by collecting it through various research instruments. Furthermore,
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