What are quantitative and qualitative data? When reading psychological research and studies, you will come across two types of data; quantitative and qualitative data. These types of data are then used and analysed to see what has been found after conducting research. However, both quantitative and qualitative data have different uses in research and provide different approaches to revealing information about the phenomena of interest.
- First, we will cover the qualitative and quantitative data definitions. We will then discuss the difference between qualitative and quantitative data to further your understanding.
- Throughout, we will mention examples of qualitative and quantitative data and highlight the qualitative and quantitative data analysis methods commonly used in psychology.
- To finish off, we will discuss the advantages and disadvantages of quantitative and qualitative data.
Quantitative and qualitative data is used to analyse the results of a study to provide evidence of whether a hypothesis should be accepted or rejected, freepik.com/storyset
Quantitative and qualitative data in research
Quantitative and qualitative data are two different forms of data. However, they have the same purpose; to establish whether the results support or disprove a theory and hypothesis.
A hypothesis is a predictive statement that the researcher makes at the start of the study. The contents of the hypothesis should predict what the researcher believes will happen in the research.
The fundaments of psychological research are to mimic the scientific research process, which involves making a hypothesis and carrying out scientific, empirical research to identify if the data support or disprove the hypothesis proposed. Both quantitative and qualitative data can provide evidence for a theory/ hypothesis. The data type obtained can depend on the research method used or what the researcher intends to find.
Qualitative and quantitative data definition
Quantitative and qualitative data are two different forms of data that have different uses in research.
Quantitative data is usually used in psychology research when the researcher wants to measure and understand something numerically.
Quantitative data is numerical data.
Qualitative data is used in research when the researcher aims to understand psychological phenomena in-depth.
Qualitative data is detailed, non-numerical data.
Qualitative data can still be quantified to represent quantitative data, so the two are not as mutually exclusive as one might think. Themes and content analysis can be observed in qualitative data and quantified to provide quantitative data.
Difference between qualitative and quantitative data
From the qualitative and quantitative data definitions, you can probably tell the difference between both data types. Quantitative data quantifies and provides numerical information regarding what was found in the study.
In comparison, qualitative data describes what was found in research using words. Therefore, the difference between qualitative and quantitative data is that they provide different depths of information concerning what was found in the study. How this is analysed also differs.
In addition to this, the difference between qualitative and quantitative data is that they are obtained from different research methods.
Unstructured interviews, open-ended questions, observations and case study research methods produce qualitative data.
In contrast, close-ended and fixed-response questions, experiments, and occasionally surveys produce quantitative data.
Examples of qualitative and quantitative data
Quantitative data measures variables on a numerical scale; it may be used to measure how many or how much a factor affects a phenomenon.
Descriptive statistics is a form of quantitative data used in psychology research to describe the study's results.
A measurement of the average height in men, for instance, is an example of quantitative data.
Qualitative data may be used when the researcher wants to identify the mechanisms that cause a phenomenon.
An extract from a hypothetical interview has been written to illustrate qualitative data:
Interviewer: How would you describe your relationship with your mum?
Interviewee: My mum and I have always been close. We always [erhh] go out together and essentially do everything together.
Interviewer: How do you feel about your mum working?
Interviewee: I guess when she leaves for her work trips, I kind of feel lonely, and I'm not sure what sure I should do?
This hypothetical research is investigating the quality of the mother-child relationship. The data obtained is all non-numerical; therefore, the data is qualitative. Content and thematic analysis will reveal more about this data.
Interviews are a research method used to collect qualitative data, freepik.com/pch.vector
Qualitative and quantitative data analysis methods
Standard qualitative data analysis methods are content analysis and thematic analysis. Content and thematic analysis involve identifying key themes and patterns in qualitative data as a data analysis method.
Content analysis involves identifying key themes within qualitative data, such as an interview transcript. The frequency of the themes within the transcript is then tallied. After this, statistical analyses can be conducted.
Although this analyses qualitative data, it produces quantitative data, what we mentioned above!
Graphs and charts such as scatter plots are often included in psychology reports to make it easier for readers to understand and interpret research findings, freepik.com/pch.vector
Thematic analysis is similar to content analysis in that it identifies key themes in qualitative data. The difference is that the results are written in the form of a detailed report. Within the report, the key themes are identified, and extracts of, for instance, a transcript are written to provide evidence of the existence of the theme.
We briefly learned that quantitative data is usually analysed and interpreted using statistical tests.
Statistical tests analyse data using various computations based on the type of data provided and what the researcher is trying to investigate.
For instance, when aiming to identify if there is an association between two variables, a correlation would be used. These statistical tests aim to identify if the hypothesis should be accepted or rejected.
There are many statistical tests, such as correlations, t-tests or ANOVAs, and each has its purpose. Researchers often display the results of the statistical analyses on graphs and charts such as histograms, bar charts or scatter plots. These are used to make it easier for readers to visualise and understand data.
Advantages and disadvantages of quantitative and qualitative data
Let's now discuss the advantages and disadvantages of quantitative and qualitative data!
Quantitative data
The advantage of quantitative data is that it makes it easier for the researcher to identify patterns and trends in data. In addition, the use of graphs and charts makes it easier for the reader to understand and interpret the study's findings.
Another advantage of quantitative data is that it is objective; the researchers' bias cannot influence the findings. Statistical tests rely solely on the data produced, so the researcher's bias cannot affect the results; this increases the validity of the findings.
When collecting quantitative data, data can be collected from a relatively large sample faster than when qualitative data is collected.
However, quantitative data is not perfect; there are disadvantages to this type of data too. Quantitative data does not provide detailed information regarding psychological phenomena, so it may be challenging to understand the causes or important factors contributing to the observed results.
When carrying out specific research methods, such as case studies, quantitative data has limited use. This is because case studies aim to get an in-depth understanding of what is being investigated.
Qualitative data
The advantage of qualitative data is that they allow researchers to develop an in-depth understanding of psychological phenomena. Qualitative data tends to be broader, so the researcher may be able to find unexpected results; this implies that this type of data would be useful when investigating new phenomena.
The disadvantage of qualitative data is that they are challenging to use when data has been collected from a large sample. Therefore, data is usually collected from a small sample making it difficult to generalise.
In addition to this, it can be expensive and time-consuming to collect and analyse qualitative data. Qualitative data methods and analysis are difficult to replicate, so it is also difficult to establish reliability.
Quantitative and Qualitative Data - Key takeaways
- Quantitative data is numerical data.
- Qualitative data is detailed, non-numerical data.
- The difference between qualitative and quantitative data is that they are obtained from different research methods, and both types of data provide different depths of information concerning what was found in a study.
- Quantitative data is usually analysed using statistical tests.
- Qualitative data is usually analysed using content and thematic analysis.
Explanations 
Exams 
Magazine 
