What Is The Difference Between Quantitative And Qualitative Research?

numbers on a screen
Photo by Mika Baumeister on Unsplash.

In the social sciences, an unresolved question remains whether or not we can measure things like love or racism the same way we can measure temperature or the weight of a star. Social phenomena--things that happen because of and through human behavior--are especially difficult to grasp with typical scientific models.

This is why psychology is often derided as an "almost-science": aside from brain scanning methods, can we really measure psychological things when we have no direct access to them? Psychologists rely on a few things to measure behavior, attitudes, and feelings: self-reports (like surveys or questionnaires), observation (often used in experiments or field work) and implicit attitude tests (the sort of test that measures your timing in responding to prompts).

Most of these are quantitative methods: the result is a number that can be compared to other numbers to make assessments about differences between groups.

But here's the problem: most of these methods are static (such as survey instruments), inflexible (you can't change a question because a participant doesn't understand it), and provide a "what" rather than a "why".

But sometimes, researchers are more interested in the "why" and the "how". That's where qualitative methods come in. Qualitative methods are about speaking to people directly and hearing their words. They are grounded in the philosophy that the social world is ultimately unmeasurable, that no measure is truly ever "objective", and that how humans make meaning is just as important as how much they score on a standardized test.

Let's take a deeper look at each approach.

Quantitative Research Methods

Quantitative methods have existed ever since people have been able to count things. But it is only with the positivist philosophy of Auguste Comte that it became a "scientific method".

The scientific method follows this general process:

  • Generation of theories or hypotheses (i.e. predicting what might happen)
  • Development of instruments to measure the phenomenon (a survey, a thermometer, etc.)
  • Development of experiments to manipulate the variables
  • Collection of empirical (measured) data
  • Analysis of data (did what you predicted happen?)

Quantitative methods are about measuring phenomenon, not explaining them. Most social and human quantitative research compares two groups of people on interesting variables: do men and women react to criticism differently? Is there a difference in happiness between people who looked at nature and people who looked at buildings? There are all sorts of variables you could measure, and many kinds of experiments to run using quantitative methods.

These comparisons are generally explained using graphs, pie charts, and other visual representations that give the analyst a sense of how the various data points relate to one another.

Quantitative methods assume a few things:

  • That the world is measurable
  • That humans can observe objectively
  • That we can know things for certain about the world from observation

In some fields, these assumptions hold true. Whether you measure the size of the sun 2000 years ago or now, it will always be the same. But when it comes to human behavior, it is not so simple.

As decades of cultural and social research has shown, humans behave differently (and even think differently) based on historical context, cultural context, social context, and even identity-based contexts like gender, social class or sexual orientation. Therefore, quantitative methods applied to human behavior (as used in psychology and some areas of sociology) should always be rooted in their particular context. In other words: there are no, or very few, human universals.

Use of Statistics

Statistical information is the primary form of quantitative data used in human and social quantitative research. Statistics provide lots of information about tendencies over large groups of people, but can never describe every case or every experience. In other words, there are always outliers.

Correlation Is Not Causation

A basic principle of statistics is that correlation is not causation. Researchers can only claim a cause-and-effect relationship under certain conditions:

  • The study was a true experiment
  • The independent variable can be manipulated (for example gender cannot be manipulated by experimenters, but seeing a primer such as a picture of nature or a building picture can)
  • The dependent variable is a ratio or a scale

So when you read reports about "gender was linked to whatever", you need to remember that gender is NOT a cause of the "whatever" in question here. There is just an apparent relationship, but the true cause of the difference is hidden.

What's Missing?

Quantitative methods are one way to approach the measurement and understanding of human and social phenomenon. But what's missing from this picture?

As noted above, statistics do not tell us about personal, individual experiences and meanings. While surveys can give us a general idea, having to choose only between a few responses can make it difficult to understand the subtleties of different experiences.

That's where qualitative methods come in.

Qualitative Research Methods

Qualitative data is not made out of numbers but rather of descriptions, metaphors, symbols, quotes, analysis, concepts and characteristics. It uses interviews, written texts, art, photos, and other "thick" materials to make sense of human experiences and to understand what these experiences mean to people.

In other words, while quantitative methods ask "what" and "how much", qualitative methods ask "why" and "how".

Qualitative methods are about describing and analyzing phenomena from a human perspective. There are many different philosophical views on qualitative methods, but in general, they agree on one thing: that some things are too complex or impossible to measure with standardized instruments. They also accept that it is impossible to be completely objective in observing phenomena: people come with their own thoughts, attitudes, experiences, and beliefs about things, and they always color how we interpret the things that happen around us.

Approaches

There are many different approaches to qualitative research, with their own philosophical bases. It would take too long and be too complicated to describe them all here. Different approaches are best for different kinds of projects: case studies and narrative studies are best for single individuals; phenomenology aims to explain experiences; grounded theory develops models and describes processes; ethnography describes cultural groups; etc.

In short, there is not a single model or method that can be used for every qualitative project. Depending on the research question, the people participating, and the kind of information they want to produce, researchers will choose the appropriate approach.

This means that qualitative researchers must be aware of several different methods and know each thoroughly enough to produce valuable research. Some researchers specialize in a single method, but other researchers tend to specialize in a topic or content area and use many different methods to explore the topic, providing different information and a variety of points of view.

Up to Interpretation

Qualitative research does not look into causal relationships between variables, but rather into themes, values, interpretations, and meanings. As a rule, then, qualitative research is not generalizable (cannot be applied to people outside the research participants). However, the insights gained from qualitative research can extend to other groups with proper attention to specific historical and social contexts.

The Relationship Between Quantitative and Qualitative Research

The way it's described here, it sounds like quantitative and qualitative research do not play well together. They have different philosophies, different data, and different outputs.

However, this could not be further from the truth. These two general methods complement each other. For example, a psychologist wanting to develop a new survey instrument about sexuality, for example, might gather a few dozen people and ask them questions about their sexual experiences. This gives the researcher some information to begin developing questions for their survey.

Following research done with the survey, the same or other researchers might want to dig deeper into some issues brought up by the quantitative data. Questions like "how does it feel when?" or "what does this mean to you?" or "how did you experience this?" can only be answered by qualitative research.

By using both quantitative and qualitative data, researchers have a more holistic, well-rounded understanding of a particular topic or phenomenon.

Was this page helpful?