There are two distinct types of data collection and study: qualitative and quantitative. Although both provide an analysis of data, they differ in their approach and the type of data they collect. Awareness of these approaches can help researchers construct their study and data collection methods.
In This Article:
- What Is the Difference Between Qualitative vs. Quantitative Research?
- Qualitative vs. Quantitative Outcomes
- Benefits and Limitations of Qualitative vs. Quantitative Research
- How To Analyze Qualitative vs. Quantitative Data
- Become a Qualitative or Quantitative Researcher
What Is the Difference Between Qualitative vs. Quantitative Research?
Because qualitative and quantitative studies collect different types of data, their data collection methods differ considerably. Quantitative studies rely on numerical or measurable data. In contrast, qualitative studies rely on personal accounts or documents that illustrate in detail how people think or respond within society.
Qualitative Research: Data Collection for Your Doctorate Degree
Qualitative research methods include gathering and interpreting non-numerical data. The following are some sources of qualitative data1:
- Focus groups
- Personal accounts or papers
- Cultural records
In the course of a qualitative study, the researcher may conduct interviews or focus groups to collect data that is not available in existing documents or records. To allow freedom for varied or unexpected answers, interviews and focus groups may be unstructured or semi-structured.
An unstructured or semi-structured format allows the researcher to pose open-ended questions and follow wherever the responses lead. The responses provide a comprehensive perspective on each individual’s experiences, which are then compared with those of other participants in the study.
Quantitative Research: Data Collection for Your Doctorate Degree
Quantitative studies, in contrast, require different data collection methods. These methods include compiling numerical data to test causal relationships among variables. Some forms of data collection for this type of study include1:
- Database reports
The above collection methods yield data that lends itself to numerical analysis. Questionnaires in this case have a multiple-choice format to generate countable answers, such as “yes” or “no,” which can be turned into quantifiable data.
Qualitative vs. Quantitative Outcomes
One of the factors distinguishing qualitative from quantitative studies is the nature of the intended outcome. Qualitative researchers seek to learn from details of the testimonies of those they are studying. Over the course of a study, conclusions are drawn by compiling, comparing and evaluating the participants’ feedback and input. Qualitative research is often focused on answering the “why” behind a phenomenon, correlation or behavior.
In contrast, quantitative data are analyzed numerically to develop a statistical picture of a trend or connection. Such statistical results may shed light on cause-and-effect relationships, and they may either confirm or disprove the study’s original hypothesis. Whether positive or negative, the outcome can enrich understanding of a subject and spark action. Quantitative research is often focused on answering the questions of “what” or “how” in regards to a phenomenon, correlation or behavior.
Benefits and Limitations of Qualitative vs. Quantitative Research
Another difference between qualitative and quantitative research lies in their advantages and limitations. Each form of research has benefits and shortcomings. Researchers must consider their hypotheses and what forms of data collection and analysis are likely to produce the most relevant findings.
Benefits of Qualitative Research
There are some significant benefits of qualitative research that should be considered when evaluating the difference between qualitative and quantitative research. The qualitative method allows for creativity, varied interpretations and flexibility. The scope of the research project can change as more information is gathered.
Limitations of Qualitative Research
Qualitative studies are more subjective in their results and interpretation than are quantitative studies. The expertise and perspective of the researcher may strongly influence the interpretation of results and the conclusions reached, because personal bias can be hard to manage. In addition, qualitative studies often test a smaller sample size due to the costs and efforts associated with qualitative data collection methods.1
Benefits of Quantitative Research
The similarities of qualitative and quantitative research do not encompass their respective benefits, because each approach has unique advantages. For example, unlike qualitative studies, quantitative studies produce objective data, and their results can be clearly communicated through statistics and numbers. Quantitative studies can be quickly analyzed with the benefit of data computing software.
Limitations of Quantitative Research
Yet, although objectivity is a benefit of the quantitative method, this approach can be viewed as a more restrictive form of study. Participants cannot tailor their responses or add context. Furthermore, statistical analysis requires a large data sample, which calls for a large pool of participants.1
How To Analyze Qualitative vs. Quantitative Data
Another of the similarities of qualitative and quantitative research is that both look for patterns in the data they collect that point to a relationship between elements. Both qualitative and quantitative data are instrumental in supporting existing theories and developing new ones. Ultimately, the researcher must determine which kind of research best serves the goals of their study.
Analyzing Qualitative Data
Because qualitative data doesn’t allow for numerical data analysis, any analytical approach must be developed with care and caution. Here are a few different methods of qualitative data analysis, as follows:
- Content analysis: Groups together similar concepts, themes and words that emerge from the data in order to understand interrelationships
- Discourse analysis: Evaluates the way in which people often express themselves in various contexts through the lens of cultural and power dynamics
- Thematic analysis: Seeks to understand the true meaning behind subjects’ words by uncovering recurrent themes in the data
Analyzing Quantitative Data
The question of how to analyze quantitative data is slightly more straightforward compared to the various approaches for qualitative data. When working with quantitative data, doctoral researchers will generally review the collected data and organize it into visual elements, such as charts and graphs.
The data can be evaluated using either descriptive or inferential statistics. Descriptive statistics provide an avenue for describing the population or data set. Inferential statistics can be used to generalize results, as well as to project future trends or predictions about a larger dataset or population.
Become a Qualitative or Quantitative Researcher
Some researchers choose to adhere to and hone a single methodological approach throughout their time as doctoral learners — or in their profession. Research skills are critical in a variety of careers.
If you have a desire to conduct research, a qualitative or quantitative doctoral degree can support your initiative. Throughout your program, you will learn methods for constructing a qualitative or quantitative study and producing written research findings.
Interested in starting your doctoral journey? Grand Canyon University has a wide variety of qualitative and quantitative programs and resources to help you. Fill out the form on this page to get started.
1 Mcleod, S. (2023, May 10). Qualitative vs quantitative research: methods & data analysis. Simply Psychology. Retrieved in May 2023.
Approved by the dean of the College of Doctoral Studies on Oct. 2, 2023.
The views and opinions expressed in this article are those of the author’s and do not necessarily reflect the official policy or position of Grand Canyon University. Any sources cited were accurate as of the publish date.