I don’t know how many times I’ve read that qualitative research is for the why, and quantitative research is for the what. That’s just wrong.
We love qualitative research for its ability to deeply dig into people’s thoughts, feelings, and emotions. When people take part in focus groups and personal interviews, a good moderator can make people divulge their most private selves. To do this well, to gain a thorough understanding of a good range of reasons why people do, think, or feel things requires ‘large’ sample sizes (let’s say 30 means large) and lots of time (let’s say a couple hours each) with research participants. It’s not a simple task and not every research project has the time or money to do this in the most fabulous way possible. But at the end of all that, we’ll have discovered a bunch of reasons ‘why.’
But to be fair, quantitative research is also extremely capable of digging deeply into people’s thoughts, feelings and emotions to discover the whys. A highly skilled researcher can help people realize and share these feelings, even with a questionnaire that is heavily quantitative. To do this well, questionnaire designers can create thoughtful, thorough, and well-developed questions that allow people to divulge their inner-most thoughts and feelings about even the most private and sensitive topics. A well-designed quantitative questionnaire can reveal the why.
We don’t need to silo qual into ‘why’ and quant into ‘what.’ Both approaches to research can uncover the why and the what as long as the researcher is an expert who is focused on answering their specific question and obtaining quality data. It’s not that we should try to hit every qual question with a quant solution, or every quant problem with a qual solution. We simply need to be more aware that both qualitative and quantitative approaches do a great job of discovering the who, when, where, how, what, AND why of human behaviour.
So if it’s not the why, what is the real difference between qual and quant research? There is just one. Quantitative research quantifies. If your research intent is to understand frequencies among a population, to predict to a population, or to run an experiment, the only option you have is to conduct quantitative research. This assumes that, as part of that research, you will achieve a (somewhat) random sample of the population to which predictions will be made. That’s it. Numbers.
As we always try to do, the right research method is the one that is best suited to answer the research problem. Let’s not automatically choose qual because we need to know ‘why.’ Let’s choose qual because it is the best solution for the problem.
Yup, I heard that from a speaker on stage at the recent AAPOR conference. You see, because if you’re smart, then you’re probably doing quantitative research. Because quant is for smart people and qual is for dumb people. Because qual requires no skills, or at least the skills are basic enough for non-mathematical people to muddle through. Because qual isn’t really a valid type of research. Because nonprobability research is worthless (yup, I heard that too).
Perhaps I’ve taken the statement out of context or misrepresented the speaker. Perhaps. But that’s no excuse. Qual and quant both require smart people to be carefully trained in their respective methods. Each research method is appropriate and essential given the right research objective.
The marketing research industry has improved greatly in this pointless debate of whose method is better and right. (Neither) Now it’s time for the polling industry to do the same.
[tweetmeme source=”lovestats” only_single=false]Let’s start from the very beginning, a very good place to start. A long time ago, in a galaxy far, far away, scientists did scientific research. They measured volumes, weights, wavelengths, and temperatures of liquids, solids, and gases. They invented scientific instruments that could assign numbers to those physical measurements and those measurements remained 100% reliable in the centuries that followed, new discoveries exempted.
Market research is a different story. We aren’t measuring biological or physical truths. We are measuring psychological tendencies. There is nothing pure nor static about human behaviour. We think, we suppose, we ponder, and we do it differently every single day.
Like the biological scientist, smrt market research scientists have spent many years and much brain power building scientific tools for measurement. It started with the very first psychology research method of “introspection.” Yes, this scientific method comprised thinking very carefully about why you did something. And that was the scientific process.
We’ve progressed over the years and have built much more solid and reliable tools since then, but, even so, those tools aren’t accurate in the same way that a weight scale or height scale is accurate. And, our MR tools aren’t measuring factors which are stable from day to day or even second to second.
The field of marketing research relies not on the science of assigning numbers to truths, but on the science of assigning numbers to thoughts, ideas, and memories. These are things with no truths, just trends and tendencies.
So really, the debate of whether you are qual or quant seems moo. Aren’t we all just variations on qual?
(There are at least four really bad TV/movie references in here. My sincere apologies.)
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Is it lost or did it barely exist to begin with?
As I think back through my academic career, I realize that qualitative research was the one major missing piece. I took innumerable courses on statistics and design, but the focus without exception was always quantitative.
As part of my undergraduate studies, I did contribute to an ethnographic study of small companies, and also for a content analysis study about babies who failed to thrive. Both led to fascinating discoveries about the respective topics simply through the analysis of words.
But, these studies were not part of the curriculum. They were simply some of my after school activities. They were just things I volunteered to do because they were interesting and I felt they enhanced my course work.
I don’t know why curriculums are set up like this, set up where you only need to know one side of the coin. With social media research just over the horizon and ready to pounce with force never before seen, perhaps it’s time for a change.
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Quantitative research is better because it follows statistically reliable procedures that permit predictions within predetermined confidence levels. It allows you to know precisely how the average person feels, as well as how various demographic groups differ.
Qualitative research is better because it gets right down to the nitty gritty of how individuals feel and behave, with feelings completely laid out and behaviours completely described. No top level descriptions here, just full, deep, and wide understandings.
I’m curious though – why is it a dichotomy? Why must it be one or the other?
I will admit that my skill set is closer to quantitative. I have far more experience and skill in quantitative methods. It makes it far easier for me to do the pro quantitative argument. But, I will also admit that I wish I had more experience in qualitative methods and it is something I admire in others who do have those skills.
I do feel that qual and quant researchers have a general understanding of the other dimension, but they simply have insufficient skill to fully appreciate it. We all know that one is used to benefit the other, whether qual happens first and is generalized in quant or quant happens first and is flushed out in qual.
Let’s just hold hands and sing Kumbaya.