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The word polar first meant the end of an axis. Visualize a world globe. Locate the North and South Poles and notice how they are geographic opposites on the axis around which the earth rotates once a day. After a time. the word polar was used to refer to things electrical. Visualize an AA or AAA battery, with its positive and negative poles, true opposites on an axis.

Somewhere in the mid-eighties, polar came to mean “directly opposite in character or tendencies.” Metaphysically, think of polar opposites as any diametrically opposed attitudes or behaviors. A favorite polar opposite of many is the notion of what would happen when an irresistible force meets an immovable object, something pondered by stoners in the freshman dorm. 

Qual and Quant are terms used by the research industry because qualitative and quantitative are hard to say

These abbreviated versions (one syllable vs. four) are also used to describe practitioners of one method or the other.

Choosing between qualitative research and quantitative research is making a choice between quality and quantity

It helps to think about qualitative research as seeking to understand a group’s essential characteristics and quantitative research as measuring the relationships between them.

Qual research vs. quant research is exploratory research methods vs survey research methods

Quals use individual and small group interviews to investigate things we have little or no information about. Quants use statistics. The whole point of surveys is to use higher order mathematics to measure study subjects’ answers to our questions and apply whatever we find to larger populations.

Quals ask “How?” while quants ask “How many?”

Qualitative descriptions are based upon in-depth observations and interpretations of characteristics and qualities that can’t be quantified. Qual is critical because it provides exploratory data that are used to generate testable hypotheses and design better surveys. As a face-to-face method, qual provides context, detail, and insights that quant can’t. Qual findings are expressed in words while quants use numbers.

Qualitative data collection is the more intimate of the two

The National Institutes of Health (NIH) define qualitative research as “a type of research that explores and provides insights into real-world problems with richness and depth.” The data collected are typically written, spoken, and/or observational. 

Swedish sociologists Patrik Aspers and Ugo Corte tell us there wasn’t much in the literature that described precisely what qualitative research is

So they analyzed a sample of 89 sources in an attempt to define the term. What they found led them to formulate their definition of qualitative research as “An iterative process in which improved understanding is achieved by making new and significant distinctions resulting from getting closer to the phenomenon studied.”

Quantitative research 

This is the use of surveys and questionnaires to collect and analyze numerical data.Surveys require the use of interval scales, continuous sequences where it is assumed that the distance between adjacent variables is the same, no matter if you’re using a 4- point, 5-point, 7-point, or 10-point scale.

Did you know that high-level statistics work only when the magnitude of the intervals (distances between choices) are all exactly the same?  

Semantic differential scales are designed to measure the strength of study subjects’ ratings

Professionals who use semantic differential scales insist that researchers follow strict rules for building the scales, including linguistic testing and establishing what is called semantic bipolarity. Most survey designers of B2B and B2C surveys have no idea such standards as these exist, which means their surveys are handicapped from the beginning — and no one knows it.

I’ve interacted with hundreds of people in the research industry and no more than a handful know what any of these things are

Those organizations that are spending millions on research are clueless about these and many other rules, principles, and protocols. When client companies don’t ask any tough questions about what goes on in the sausage factory, most of the companies providing B2B and B2C research services today benefit, not you.

Most quals and quants view each other with suspicion 

They may not be polar opposites, but they are feuding camps, especially in academica, just like the friction that exists between artists and scientists (aka quals and quants). If you’re planning on earning an advanced degree in Sociology, you’ll need to decide if you want to study How or How Many.

If you want to be able to understand why people think the way they do and why they behave as they do, go qual. Most of the top programs are on the West Coast. If you want to test things that can be counted, measured, and rated using numerical data, go quant. Good programs are everywhere.

I got around the either/or conundrum by learning both

I concentrated on learning qualitative research theory, methods, interview techniques, and so on as an undergraduate Sociology student in Kentucky and Tennessee. Then I learned quantitative research theory, methods, and statistical techniques in the Sociology Department’s doctoral program at Indiana University.

Most of today’s sociologists are people facile with numbers

The bigwigs in sociology in the U.S. have been the quants for more than 50 years because that’s where most of the money for sociological studies goes. The quants say qual is too touchy-feely and the quals counter with how quant is too mechanical, often losing sight of the fact that those numbers are real people. Qual interviews are invitations to people to tell their stories their own way and in their own words. Quant survey questions are structured so every participant is asked the same questions the same way in the same sequence. Most quants see most quals as non-scientific, scruffy, second-class weirdos. Most quals see most quants as narrow-minded pinhead slaves to their machines.

Bipolar is a word most of us are familiar with only within a mental health context

It refers to two states of mind, mood, and behavior: manic and depressive, considered to be opposite ends of the same spectrum. In survey research, bipolar describes an either/or proposition, such as our Hot/Cold semantic differential scale.

Let’s say a survey designer wants to know about the temperature of something and presents survey takers with a 4-point scale where 1 is Hot, 2 is Warm, 3 is Cool, and 4 is Cold

Do you see the same problem I do? I will never be convinced that the gap between Hot and Warm is the same as the one between Warm and Cool. Hot and Warm are closer because they’re both shades of heat. Warm and Cool are farther apart because they’re distinctly different things. It seems only natural that there must be some neutral state in between, where people are neither warm nor cool.

How about if we change to a 5-point scale where our descriptive term for the value between warm and cool is Neither Hot Nor Cold?

Do you think all the increments are the same now? What about lukewarm, blazing hot, freezing cold, and tepid? Where are they on our scale?

In all likelihood, your research provider doesn’t know this and a dozen other things that have a profound affect on the value you get from your quantitative studies

And as they say, if you don’t know it’s a problem, you can’t do anything about it.

Hybrid research

The best researchers are highly qualified at both qual and quant, aware of the strengths and weaknesses of both methods, and not hobbled by knowing only one or the other. The most valuable B2B and B2C research studies use both methods to study the right things, starting with the kind of qual that makes the quant better. This is called hybrid research by some and multi-method research by others.

As an undergraduate, I was drawn to the qualitative side of sociology from the start

I was really interested in listening to what people have to say. I learned a lot more about people and interviewing them from Studs Terkel’s book, Working: People Talk About What They Do All Day and How They Feel About What They Do than I ever did reading fan-folded printouts with perforated margins, and it was lots more fun and engaging to listen to people telling stories than sit in the basement running computer printouts all day. Read what Studs had to say about work, knowing that nothing like this comment ever comes from a survey.

Did you know that scientific method used by quants starts with predictions about what the research will reveal? 

These predictions are called hypotheses. Ohio State University’s Quantitative Methodology Center says a hypothesis is a statement or assumption that you can test, evaluate the outcome, and base your decisions on. In academia, every study needs to have a null hypothesis and an alternate hypothesis. Businesses and organizations don’t bother. 

Strictly speaking, quant is used to test hypotheses generated from what you already know about your customers, your category, and your customers

Start by going through your organization’s research library — if you can find it. Hypotheses propose relationships between dependent and independent variables. Once you’ve decided what your hypotheses are, use your knowledge and experience to predict what the outcome will be. These days, many researchers will throw hypothesis generating at an A.I. tool with little or no idea what happens or why.


In May of 2019 I wrote and published an article titled How Did Businesses Waste $3 Billion on Surveys? A week earlier, I wrote and published How Did Businesses Waste $2 Billion on Focus Groups?  For the past five years, these two articles have been of great interest to those who want to learn more about how to conduct research, those who contract with others to do the research and want to learn how to get what they’re paying for, those who will be using research and need it to be of high quality, and business leaders everywhere who are looking to understand more about their category, competitors, and customers.

It is not important to know all the technical terms

But it is important to be aware of the concepts and rules rather than remaining blissfully ignorant and let your research suffer.

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My position on qual vs. quant is that I no longer get involved with planning any research unless it is designed to use the best of both qual and quant methods as they are meant to be used.

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