We can define two general classes of data: qualitative data and quantitative data. Each type of data has value in different ways. Researchers tend to be more comfortable with one or other other. However, the strongest studies often employ both types of data. Here we briefly overview each.
This data is the type typically familiar to most people. It consists primary of numbers. For example, if we are measuring whether an intervention improves student performance on assignments. Then the numerical grade received by the student is a type of quantitative data. The characteristics of quantitative data include:
- Controlled measure - meaning that researchers typically know exactly what information they are going to receive. In the example, the researcher knows exactly what information they will receive - one numerical grade between 0 and 100 for each assignment from each student.
- Tend to be objective - these types of measures tend to have less subjectivity in them compared with qualitative data. However, this rule is not absolute. If the researcher asks someone to rate on a scale of 1 to 5 how much they liked a new assignment, the measure would be quantitative but still subjective.
- Verification oriented - quantitative data is more often used when a researcher is trying to verify a claim or a hypothesis. This type of data often lends itself better to statistical analysis.
This data is typically less familiar to most people. It consists of information that is not numbers, e.g. text, pictures, observations. In the example above, if instead of studying whether the numerical grade of a student improves, the researcher is interested in the students’ opinions of the old and new approaches, the researcher could use a survey question that asked the student to explain the strengths and weaknesses of each approach. The responses to this question would provide qualitative data. The characteristics of qualitative data include:
- Naturalistic measure - as opposed to quantitative data, with qualitative data the researcher does not know exactly what information they will receive. It is less controlled.
- Tend to be subjective - similar to how quantitate measures tend to be more objective, qualitative data tends to be more subjective. However, this rule is also not absolute. It is possible to collect objective information in a qualitative format, just less common.
- Discovery oriented - as opposed to the quantitative data which is typically more verification oriented, qualitative data helps the researcher explore potential relationships and connections within their study domain. Often qualitative data is used when the researcher does not yet have a concrete hypothesis that can be tested with quantitative data.