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How To Best Approach Qualitative Research

April 28, 2026 by: Trident University International Categories: Education, Research

What Is Quantitative Research? Types and Process

Quantitative research—that is, research that relies on numerical values—plays a significant role in evidence-based decision-making, as it enables decision-makers to extract actionable insights from data.1 Depending on the academic discipline you study, you may have to become not only familiar with but well-versed in quantitative research techniques and design.

In this article, we begin by defining quantitative research, distinguishing it from qualitative research, and clarifying the difference between primary and secondary research. We then give an overview of the primary types of quantitative research designs—descriptive, correlational, experimental and quasi-experimental—before closing out our discussion with a step-by-step overview of the quantitative research process.

What Is Quantitative Research?

Quantitative research—sometimes referred to as quantitative design, quantitative inquiry; quantitative method, or quantitative study—is a research method that relies on numerically measuring variables, statistically analyzing those measurements and reporting the results of that analysis.2 Essentially, it is a structured way for researchers to gather, measure, and analyze and interpret data. It is but one of three main types of research study classifications: quantitative, qualitative and mixed-methods (which combines both quantitative and qualitative methods).3

Quantitative research examples are everywhere. Common ones that may come to mind include clinical trials and customer-satisfaction surveys (think questionnaires/online polls that ask you to numerically rate your satisfaction with a product or service).

Reflection: Can you think of other quantitative research examples?

Quantitative vs. Qualitative Research

How is quantitative research different from qualitative research? The most basic difference between quantitative vs. qualitative research is that where the former is numbers-based, the latter is not. Qualitative research gathers information on “participants’ experiences, perceptions, and behavior.”4 It “asks open-ended questions whose answers are not easily put into numbers, such as ‘how’ and ‘why,’” rather than asking “how many” or “how much.”4

Earlier, we noted that clinical trials are an example of quantitative research design. However, modern clinical trials may take a mixed-methods approach to capture both measurable outcomes (quantitative) and contextual insights (qualitative), thus leading to a more complete understanding of complex research questions.1

Primary vs. Secondary Research

Understanding what quantitative research is also requires that we understand the difference between primary and secondary research.

Primary research refers to “[t]he generation of new data in order to address a specific research question, using either direct methods such as interviews, or indirect methods such as observation. Data are collected specifically for the study at hand, and have not previously been interpreted by a source other than the researcher.”5 Or, to put it more succinctly, primary research concerns the collection and analysis of data for the purpose of answering a specific research question in the present moment.

Secondary research, or secondary analysis, is “[t]he further analysis of an existing data set with the aim of addressing a research question distinct from that for which the data set was originally collected, and generating novel interpretations and conclusions.”6 Note that this definition does not specify who collected the data. The data used in conducting secondary analysis can be your own or that of other researchers—what makes the research “secondary” isn’t that the data comes from someone else but rather that it is being used to answer a different research question from the one it was originally intended to answer.

Reflection: Can you think of potential benefits and pitfalls of primary research? Of secondary research?

Types of Quantitative Research Designs

Descriptive

This type of quantitative research design is observational (non-experimental). Its purpose is to detail behaviors, situations, events and outcomes—not to make theoretical predictions or identify cause-and-effect relationships. In descriptive research design, data integrity is maintained by “avoiding manipulation of the research context and prioritizing the subjects’ experiences.” Descriptive research can be carried out through observation, case studies, and surveys of individuals or large groups.7

Correlational

Correlational quantitative research design aims to understand and explain the relationships between variables, as opposed to simply describing the variables. However, as with descriptive research design, relationships in correlational research design are assessed without the researcher’s controlling or manipulating variables.8

Variables can be positively correlated, meaning that that the variables move in the same direction—for example, high values of one variable are associated with high values of another. Variables can be negatively correlated, meaning that they move in opposite directions—for example, high values of one variable are associated with low values of another.9 Variables may also be uncorrelated (no predictable relationship between them) or independent (variables are unrelated).

Experimental

In contrast to non-experimental research designs, which do not involve manipulation of variables or random assignments of subjects to different groups, the classic experimental research design involves at least two groups: the experiment group and the control group.10 Through manipulation and control of independent variables, experimental design allows for the examination of cause-and-effect relationships on dependent variables.9 Other conditions must be satisfied as well: the variables must be accurately and precisely measured, the statistical test to be used must be determined in advance of starting the experiment and the experiment must (ideally) be repeatable.10

Quasi-Experimental

The quasi-experimental research design is as its name suggests—a research design that lies somewhere between a true experimental design and an observational (non-experimental) design. This research method can be used when an experimental design is infeasible or unethical: “quasi-experimental studies are often used in real-world settings and can leverage events, such as examining health outcomes following a hurricane or other natural disasters.”11

Unlike a classic experimental research design, the quasi-experimental design does not require that subjects be randomly assigned to groups, the researcher does not control the treatment and inclusion of a control group is not mandatory.12

Reflection: Do you think ethical issues could influence whether a non-experimental or experimental
quantitative research design is chosen for a study? If so, how?

The Quantitative Research Process—Step by Step

The quantitative research process involves multiple steps. Exactly how many steps are involved in the process can vary depending on how discretely each step is broken down, what is being studied, etc. Here we have distilled the process down to seven steps:

  1. Identify the Research Question. “A research question is what a study aims to answer after data analysis and interpretation.”13 Because the research question serves as the foundation for development of the hypothesis, it should clearly identify the issue or knowledge gap that your research will address. The fact that a topic interests you is only a starting-off point for defining the research problem—developing a strong research problem requires a comprehensive literature search and an in-depth understanding of the problem being investigated.13
  2. Develop a Hypothesis. A hypothesis is defined as “a proposed explanation for something (such as a phenomenon of unknown cause) that is tentatively assumed in order to test whether it agrees with facts that are known or can be determined.”14 It is a formal prediction whose two main features are falsifiability and testability; whether a hypothesis is determined to be true or rejected as false hinges on scientific evaluation of research results.15
  3. Select the Research Design and Methodology. Because the research design will serve as the blueprint for your research, you will have to decide what is the most suitable type for your particular project (e.g., descriptive, correlational, experimental, quasi-experimental). To help you decide, you should consider things such as: What is being measured? Is a control group needed? How can bias be minimized?
  4. Determine Sampling Design. Whether we are talking about patient populations or consumers or something else, the “sample” is a representative subset of the larger population. Sampling design involves considerations like sample size and the method of selecting the sample size (the sampling technique)—for example, random sampling/probability sampling, non-random sampling/non-probability sampling, or systematic/mixed sampling.16
  5. Determine Data Collection Methodology. After you have identified your research sample, you can focus on determining the type of data to be collected, the research instruments to be used (surveys, questionnaires, etc.), obtaining authorizations from the participants and determining the data-collection procedure itself.16
  6. Conduct Data Analysis. After choosing a statistical analysis program that is capable of answering the research question and testing the hypothesis, it is time to conduct the actual data analysis. The data analysis process comprises several steps: (1) organizing the data, (2) analyzing the data and (3) reporting the research outcome. Descriptive statistics and/or inferential statistics also come into play at this stage. Descriptive statistics include distribution (the frequency of a variable), central tendency (mean, median, mode), and variability or spread (standard deviation, variance, minimum/maximum values, etc.). Inferential statistics are used by researchers to make data-based predictions about the wider population—but to use inferential statistics, the research sample must have been selected using a random and unbiased sampling technique.16
  7. Report Results. The final step in the quantitative research process is to objectively and clearly report your research findings and conclusions to the target audience. Including an opening statement, using headings and subheadings, incorporating tables and figures, and concluding a summary of your findings can help you to accomplish this goal.

A quantitative research report should state the research question you set out to answer and your hypothesis; explain your research design, sampling design, and data collection methodology and techniques; include all relevant information about the statistical tests used and why you chose them; identify any unexpected incidents or limitations (such as missing data); and lay out your findings and conclusions as they relate to your research question and hypothesis (i.e., whether your hypothesis is supported, not supported or partially supported).16

Frequently Asked Questions

This is called a longitudinal quantitative research study. In longitudinal research, the same subjects are tracked over a prolonged period of time, whether days, months or years.17

Quantitative research can pose tricky problems. Some potential pitfalls include reliability challenges (figuring out how to measure something the same way each time, without introducing any changes) and validity challenges (figuring out a way to measure exactly what the researcher intends to measure).18

Recall that quantitative research asks “how many” or “how much,” while qualitative research asks “how” or “why.” In marketing research, which of these questions you ask will help you decide whether to rely on close-ended customer surveys or web analytics (both quantitative), or on open-ended surveys, focus groups, interviews or observational studies (observing subjects using a product or service in their natural environment) (all qualitative).19

Continue Your Education at Trident

Trident University International offers online degree program options for those who are interested in research and the healthcare field through our College of Health and Human Services:

You can also check out our complete listing of undergraduate and graduate online degree programs or request more information.

Trident cannot guarantee employment, salary, or career advancement. Not all programs are available to residents of all states. REQ2216070 4/2026

1 Weng Marc Lim, “What Is Quantitative Research? An Overview and Guidelines,” Australasian Marketing Journal, vol. 33, issue 3, Aug. 2025, https://journals.sagepub.com/doi/full/10.1177/14413582241264622.
2 APA Dictionary of Psychology, “Quantitative Research” (updated Apr. 19, 2018), https://dictionary.apa.org/quantitative-research.
3 Marlon L. Bayot et al., “Human Subjects Research Design” (updated Jan. 12, 2026), https://www.ncbi.nlm.nih.gov/books/NBK537270/.
4 Steven Tenny, Janelle M. Brannan & Grace D. Brannan, “Qualitative Study,” NIH NCBI Bookshelf (updated Sept. 18, 2022), https://www.ncbi.nlm.nih.gov/books/NBK470395/.
5 Claire Hewson, “Primary Research,” The SAGE Dictionary of Social Research Methods 237–38 (2006), https://doi.org/10.4135/9780857020116.n156.
6 Claire Hewson, “Primary Research,” The SAGE Dictionary of Social Research Methods 274–78 (2006), https://doi.org/10.4135/9780857020116.n185.
7 Elizabeth Rholetter Purdy, PhD, & Elena Popan, MA, “Descriptive Research,” EBSCO (2023), https://www.ebsco.com/research-starters/social-sciences-and-humanities/descriptive-research.
8 Pritha Bhandari, “Correlational Research: When & How to Use,” Scribbr (updated June 22, 2023), https://www.scribbr.com/methodology/correlational-research/.
9 Janet Salmons, PhD, “Quantitative Research with Nonexperimental Designs,” Sage Research Methods Community (Feb. 3, 2023), https://researchmethodscommunity.sagepub.com/blog/quantitative-research-with-non-experimental-designs.
10 Janet Salmons, PhD, “Experiments and Quantitative Research,” Sage Research Methods Community (Feb. 5, 2021), https://researchmethodscommunity.sagepub.com/blog/experiments-quantitative-methodologies.
11 Bernadette Capili & Joyce K. Anastasi, “An Introduction to the Quasi-Experimental Design (Nonrandomized Design),” American Journal of Nursing, vol. 124, issue 11, pp. 50–52 (Oct. 24, 2024), https://pmc.ncbi.nlm.nih.gov/articles/PMC11741180/.
12 Lauren Thomas, “Quasi-Experimental Design: Definition, Types & Examples,” Scribbr (updated Jan. 20, 2024), https://www.scribbr.com/methodology/quasi-experimental-design/.
13 Edward Barroga & Glafera Janet Matanguihan, “A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles,” Journal of Korean Medical Science, vol. 37, issue 16, pp. e121 (Apr. 12, 2022), https://pmc.ncbi.nlm.nih.gov/articles/PMC9039193/.
14 Merriam-Webster Online Dictionary, “Hypothesis,” https://www.merriam-webster.com/dictionary/hypothesis (last visited Apr. 10, 2026).
15 Kara Rogers, Brittanica Editor, “Scientific Hypothesis,” Brittanica (Mar. 6, 2026), https://www.britannica.com/science/scientific-hypothesis.
16 Anahita Ghanad, “An Overview of Quantitative Research Methods,” International Journal of Multidisciplinary Research and Analysis, vol. 6, issue 8 (Aug. 8, 2023), https://doi.org/10.47191/ijmra/v6-i8-52.
17 Janine Ungvarsky, “Longitudinal Study,” EBSCO (2023), https://www.ebsco.com/research-starters/social-sciences-and-humanities/longitudinal-study.
18 The London School of Economics and Political Science, “FAQ 4: How Should Quantitative Research Be Evaluated?” https://www.lse.ac.uk/media-and-communications/assets/documents/research/eu-kids-online/toolkit/frequently-asked-questions/FAQ-4.pdf.
19 Andrada Comsa, “11 Types of Qualitative Research Marketers Navigate Every Day,” Attest (Apr. 7, 2026), https://www.askattest.com/blog/articles/types-of-qualitative-research.