Quantitative and qualitative data are two sides of the same coin, and researchers typically use both of them to get a broader view of their findings. Simply put, quantitative data is numerical in nature, while qualitative data refers to things that can be observed but not measured.
To know more about their main differences, look no further than our examples below.
1. Quantitative Data
Quantitative data is data that is numerical in nature. It is typically represented by numbers and includes the following:
- Physical measurements of a person, place, or thing
- Meanings of what a survey subject chose to answer
Quantitative data is typically used to describe a subject’s behavior. It is also used to make comparisons between groups or time periods.
2. Qualitative Data
Qualitative data is data that is descriptive in nature. It is typically represented by words, pictures, or video and includes the following:
- An individual’s perspective on a certain topic
- What happened during an event
Qualitative data is typically used to describe a subject’s opinion, beliefs, and thoughts. It is also used to analyze an event or a person’s behavior.
3. Differences in Purposes
The contrast in their purposes can further define the differences between quantitative and qualitative data. Quantitative data is usually used to measure the behavior or performance of an individual, group, or event. Meanwhile, qualitative data is used to describe the subject’s thoughts and feelings.
4. Differences in Measurements
The differences between quantitative and qualitative data can be found in the way they are measured.
Quantitative data is often measured using numbers and figures, while qualitative data is more often described in words.
As a rule of thumb, quantitative data is more objective and easier to measure, while qualitative data is more subjective and harder to measure.
5. Differences in Data Analysis
The differences between quantitative and qualitative data can be seen in the way they are analyzed.
Quantitative data is typically analyzed using research methods such as:
- Analyses based on numbers
- Interpreting graphs and charts
- Statistical calculations
Qualitative data, meanwhile, is usually analyzed using research methods such as:
- Interviews
- Focus groups
- Content analysis
6. Differences in Data Collection
The differences between quantitative and qualitative data can be found in the way they are collected.
Quantitative data is usually collected using the following methods:
- Tests
- Surveys
- Questionnaires
- Experiments
Qualitative data, on the other hand, is usually collected using the following methods:
- Observations
- Interviews
- Content analysis
- Video recordings
7. Differences in Data Analysis Tools
The differences between quantitative and qualitative data can be seen in the way they are analyzed.
Quantitative data are typically analyzed using the following tools:
- Calculators
- Spreadsheets
- Statistical packages
- SPSS
Qualitative data, meanwhile, is usually analyzed using the following tools:
- Tally charts
- Awareness charts
- Protocols
Which One Should I Use between the Two?
As mentioned earlier, it is common for researchers to use both forms of data to understand their findings better. Both types of data are necessary to provide a more holistic interpretation of the subject’s behavior and opinion.
In other words, quantitative data is typically used to describe the “what” and “how” questions in research, while qualitative data is used to describe the “why” and “how” questions.
Conclusion
The differences between quantitative and qualitative data can be a bit confusing to some people at times. At the end of the day, the key to understanding their differences is to know the purpose of your research.
This way, you can choose the data that is most relevant to it, one that will really drive home the point of your findings. You also have to ensure that your questions are answered accordingly so that there will be no discrepancies with the results.
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