Are you trying to wrap your head around empirical research methods? You keep reading about quantitative and qualitative research methods but what is the difference?
Don’t panic, you will get an easy answer to this question over the next few minutes.
In this video you will learn about the 5 crucial differences between quantitative and qualitative research methods. So not only will you be able to distinguish these two approaches in your sleep, but hopefully you’ll get some valuable ideas for choosing the method for your next scientific work.
What is empirical research?
Before we dive into the differences between qualitative and quantitative research methods, we need to clarify what they have in common. They are both part of what is called empirical research. This means, in a very simplified way, the systematic collection of data to gain knowledge.
In a figurative sense, the “experiences”, i.e. the data, are used to derive new knowledge. This always involves some sort of observations in the real world or with real people. For example, social sciences but also the natural sciences are dominated by empirical research.
In contrast, a mathematician or philosopher, who reaches insights only by thinking and logical reasoning, is not considered empirical. That does not mean one is better or more scientific than the other. They are just different ways to gain scientific knowledge.
In philosophy of science, the question about how researchers can gain knowledge in the first place is subject to epistemology. Look up this term if you want to dive deeper into this.
The two paradigms (quantitative and qualitative)
The distinction between quantitative and qualitative research is the result of more than one century of debates between researchers about what science is and how research should be conducted.
In a nutshell, two positions emerged based on different philosophical assumptions about how the world is made up (in philosophical terms, this is called ontology). The more sciency scientists were convinced that there is an objective reality that is independent from us humans (in philosophical terms, this world view is called realism). This reality can be measured by using numbers and statistics (in philosophical terms, this world view is called positivism). This was the starting point for quantitative research.
As this thinking was dominant in the academic landscape of the early 20th century, emerging disciplines adopted the same principles. For example, psychologists studying the inner workings of the human mind applied the same natural science-based approach.
Later, this natural science approach to social science led to the emergence of other positions that were not at all happy with this type of thinking.
“Wait a minute,” they said, “don’t you think social phenomena are constructed differently by different groups and individuals?”
They had a point.
A stream of research emerged that was not interested in statistically computing the personality traits of teenagers or how the management of an IBM computer worked (the relevant philosophical terms here are constructivism and interpretivism).
One milestone in advancing the qualitative paradigm was Glaser and Strauss’ (1967) Grounded Theory Methodology. It reversed the deductive logic of testing theory to an inductive logic of generating theory. Until this day, the Grounded Theory Methodology is an important part of qualitative research.
The 5 Differences between quantitative and qualitative research
Now, let’s look at 5 different characteristics of both approaches.
#1 Object of study
Quantitative research investigates large samples and assumes more of an outside view
Qualitative research investigates small samples and assumes more of an inside view
#2 Types of data
Quantitative research relies on numerical data (“hard” and replicable)
Quantity as a characteristic means measuring the amount of a certain unit. Quantitative data is therefore available in large quantities in the best case. But not only the quantity is decisive, but also the quantifiability. This means that these data are unambiguous.
If a test person answers question 1 in a questionnaire with the answer option 3, then this data is unambiguous.
A measurement method of a sensor or the number of comments on a Twitter message is also unambiguous. In the language of statistics, different types of data can be categorized as nominal, ordinal, and metric.
And this brings us to the great advantage of quantitative data: You can apply statistical techniques to analyze it.
Qualitative research relies on linguistic data (“soft” and unique)
Qualitative data are always context-dependent, i.e. the basic conditions of your data collection environment must be taken into account during the investigation. This is particularly important in case studies.
The great advantage of qualitative data is that they can be rich. As a researcher you really get underneath the surface level and can attempt to explain “why” things are the way they are.
#3 Analytical Logic
Quantitative research typically measures things and follows a deductive logic
Qualitative research typically interprets things and follows an inductive logic
Deductive logic means using a general (mental) model to form a specific conclusion. (For example, using a theory to derive hypotheses)
Inductive logic means starting from a very specific example or case and forming a general conclusion. (For example, using interview data to generate a theory)
#4 Methods (Examples)
Quantitative research uses methods such as surveys, experiments, or simulations
Qualitative research uses methods such as interviews or observations
#5 Theoretical Contributions
Quantitative research typically contributes to theory by testing propositions or hypotheses
Qualitative research typically contributes to theory by introducing new concepts, models, or mechanisms
How to choose between quantitative and qualitative methods
If you are faced with the challenge of conducting empirical work, then choosing the right research design is one of the most important decisions of all. It all comes down to your research objectives, i.e. answering your research question(s).
Which research method can best achieve this goal?
This question is the basis of your consideration. I would like to make it clear that scientific work does not have to be empirical. In many disciplines this would not make sense at all.
Moreover, most scientific disciplines welcome both quantitative and qualitative research. In fact, many researchers see great value in combining quantitative and qualitative research methods. This is called “Mixed Methods”.
The next step you can take is grabbing Creswell’s (2014) classic textbook and dig deeper into what you just learned.