Qualitative vs. Quantitative Research in Biotechnology

If you’ve read (or taught) a biology textbook you’ve probably come across a section on qualitative and quantitative data. Chances are it was brief with basic definitions and maybe a mention that that both types of data are important to science. But if you’re here on our blog you’ve likely leaped a more hands-on, experiment-centric curriculum and are looking for a deeper dive into the two q’s of data. Read on!

THE BASICS

Qualitative and quantitative describe distinct types of data as well as slightly different approaches to research. Here’s how they differ:

The Data

• Qualitative research focuses on non-numeric data. It involves collecting and analyzing descriptive, narrative, or textual information, often in the form of words, images, or observations. Qualitative data can be open-ended, subjective, and rich in detail.
• Quantitative research deals with numeric data. It involves collecting data in the form of numbers, such as measurements, counts, or ratings. The data is typically analyzed using statistical techniques. A consequence of this is that quantitative research often involves larger sample sizes and data sets to ensure statistical validity.

The Methods

• Qualitative research methods include observations as well as case studies, interviews, and focus groups. Researchers seek to understand and interpret underlying meanings, patterns, and contexts. Researchers use themes, patterns, and narrative explanations to make sense of the data.
• Quantitative research methods include experiments, structured observations, surveys, and data analysis through statistical tools and techniques. Researchers aim to quantify relationships and trends in data. Analysis in quantitative research involves statistical tests and calculations to assess relationships, significance, and patterns within the numerical data. Researchers use themes, patterns, and narrative explanations to make sense of the data but these findings are supported by calculated values like means and correlation coefficients.

The Objectives

• Qualitative research is exploratory. It’s often used to generate hypotheses, uncover new insights, and develop a narrative. Qualitative data in medical diagnosis involves the subjective assessment of symptoms, patient narratives, and contextual information. Some diagnosis tests are also qualitative or a hybrid of the two methods (semi-quantitative).
• Quantitative research is used to test hypotheses, establish relationships, and make predictions. It focuses on measuring variables, determining cause-and-effect relationships, and generalizing findings for large data sets. Quantitative data in medical diagnosis involves the numerical analysis of measurable parameters, such as laboratory values or imaging results, providing objective and standardized information to support clinical assessments.

Researchers choose between qualitative and quantitative methods based on their research questions, objectives, and the nature of the data they want to collect and analyze. In some cases, a mixed-methods approach, combining both qualitative and quantitative methods, is used to provide a more comprehensive understanding of a research topic.

In biotechnology, both types of data are often used together. Qualitative data may help researchers identify interesting phenomena or patterns, while quantitative data allows for precise measurement and statistical analysis. For example, qualitative observations of abnormal cell morphology might lead to quantitative measurements of cell counts or the concentration of a specific molecule to understand the underlying causes of the observed changes. The combination of qualitative and quantitative data is a powerful approach to biotechnology research and applications.

Examples of Qualitative Research in Biotechnology

Qualitative data in biotechnology often involve descriptive observations of biological processes. This can include visual assessments of cell morphology, tissue structure, or the appearance of microorganisms. Qualitative data can also include the presence or absence of specific molecules or genes in a biological sample (although depending on how this presence/absence data is processed it can also be quantitative). Qualitative data may involve the assessment of phenotypic characteristics like color, shape, growth patterns, or other observable traits in organisms or cell cultures. Microscopy and staining is a common method in biotechnology to obtain qualitative data. Researchers can use various staining techniques to visualize cellular structures, pathogens, or cellular localization of specific molecules. Techniques like PCR (Polymerase Chain Reaction) and ELISA (Enzyme Linked Immunosorbent Assay) can be used to detect the presence of specific DNA sequences or molecules.

Examples of Quantitative Research in Biotechnology

Quantitative data in biotechnology involves measuring biological variables using numeric values. For instance, researchers may measure the concentration of specific molecules or sequences or quantify the number of cells in a culture. Popular biotechnologies that enable quantitative research are: Spectrophotometric analysis (used to quantitatively determine the concentration of substances by measuring the absorption of light at specific wavelengths), Real-time PCR (used to quantitatively measure the amount of DNA or RNA in a sample), ELISAs with a standard curve (use to measure the concentration of certain molecules) and Flow Cytometry (used to measures the characteristics of cells or particles in a fluid stream, such as cell size, granularity, and the presence of specific surface markers).

Last, but not least, help to remember the difference!

Qualitative starts with “Qual,” and you can associate it with “Quality.” Think of qualitative data as focusing on the quality of information, emphasizing descriptive details, and the “how” and “why” of a phenomenon. Quantitative starts with “Quant” and you can associate it with “Quantity” (the amount of something) or even just the presets of a “N” for numbers. Or you can try this little rhyme or any part thereof:

Qualitative is tales and tales,
while Quantitative counts and scales.

Qualitative, tales we create, in colors and details, it’s truly great.
Quantitative, counts on a scale, with numbers precise, it’ll never fail.

Qualitative is a colorful show, it tells the ‘what’ with a creative flow.
Quantitative, numbers align, it counts the ‘how much,’ it’s data’s goldmine.

In Qualitative, details bloom, painting pictures that chase away the gloom.
Quantitative, numbers at play, measuring data in a structured array.

Check out some of our popular qualitative and quantitative experiments for the classroom.