Speaker 1: People use the word qualitative and quantitative in a couple of different ways. One way is to think about data. There is quantitative data and qualitative data. And another way is to think about the actual research methods. Like, what are we doing to this data to get to the claims that we're going to talk about? We have quantitative research methods and we have qualitative research methods. Let's talk about the data stuff first. Quantitative data is anything that can be counted. Anything that can be quantified. Anything that you can put a number on. So the score that you got on a math test or the number of hours that you logged at work. How much in debt am I to my creditors? That's all quantitative data. Even something like, did you vote this year, yields a quantitative outcome. So you either did vote, which in most statistical models would be represented with a one. Or you didn't vote, which would be represented with a zero. Qualitative data is the opposite of that. It's something that cannot be quantified. Cannot be counted in that way. A lot of times we're talking about words or behaviors that we're observing. So essays, forum posts, video and audio recordings. All of these are fundamentally qualitative data. The important thing to remember here is that we can transform qualitative data into quantitative data. For instance, we can read this essay and we can see what reading level it is. Or we can give this essay a grade, which would be a different way of quantifying the essay. If we're observing this bird of paradise, we could count like, how many times does this bird wiggle its butt? That would be quantifying qualitative data. With that discussion of data out of the way, maybe you are getting some hints about the differences in terms of research methods. Once you have quantitative data, you can do quantitative things to it. So you can count, you can count them up. You can add things together. You can take averages. You can get standard deviations. You can run statistical tests. You can develop mathematical models of the situation. The results of quantitative research usually look something like this. At least in the social sciences. Correlation coefficients and confidence intervals, NFP values and regression models. I'm skipping over a lot of the details here. When you think about quantitative methods, you want to think about things like randomized controlled trials in the social sciences or in the natural sciences. Data mining, laboratory research, longitudinal studies often include a lot of quantitative data. So all of these are quantitative research approaches. The result of qualitative research can vary, but a lot of times researchers are trying to deeply understand a specific situation. They're looking for patterns or themes to emerge as they're reading all of this qualitative data. Observational studies, case studies, ethnographies, discourse analysis, interviews, open-ended survey questions. They're all examples of qualitative research. Quantitative research tends to focus on populations and averages, although not exclusively. Qualitative research tends to focus on meaningful comparisons, sometimes just between two different things or even just one thing and just looking at one thing very closely. And there's also a tendency to focus maybe more on the extremes of the distribution or overlooked areas of the distribution. Quantitative research can be very powerful, very powerful, but there's some stuff that it just can't do. So for instance, we can look at this essay and give it a grade or we can count the average number of grammatical mistakes that students make in their essays. But that's not going to tell us what the meaning of the essay is. The meaning is more of a qualitative question. Qualitative methods have important limitations as well. Sometimes the variables that they're examining aren't well defined and a lot of times researchers have to make hard decisions about what to focus on. It's a lot easier to analyze, say, a thousand Scantron multiple choice tests that you can just enter into a machine and see which ones students got right and which ones they got wrong. It's a lot harder to sit down and analyze a thousand essays and look for themes and patterns that emerge from them. These research approaches can complement each other very well. You might use the quantitative data or the quantitative approach for looking at the beginning and the end of a process and you might take the qualitative approach to look at the process itself. So for instance, you might have students or research participants answer a series of problems and so whether they got the problem right or not, that's a question of the quantitative data, right? And you might analyze that. You can take averages or compare two groups' performances with different conditions but then you also might have them think aloud as they solve those problems. Well, their descriptions of their thinking, that's qualitative data and you can analyze that using qualitative research methods and look for themes and patterns that emerge in terms of people's insights or misconceptions or misunderstandings of the situation. The qualitative data is going to tell you the path that people took to solve the problems while the quantitative data is telling you, well, did they actually solve it or not? In other cases, qualitative research tends to come before quantitative research. So if you don't know anything about a situation and there's not a bunch of prior research on it, you're usually not going to take a quantitative approach. You don't even know what the right variables are to measure. Exploratory research tends to be qualitative. By exploratory, I mean you're trying to figure out what the heck is going on in a situation. So that tends to be qualitative and as you improve your understanding, sometimes then you can create meaningful quantitative measures and get more precise in what you're measuring to complement the qualitative research that you did earlier. If this video tickled your fancy, please click the like button and maybe it'll tickle other people's fancy as well. And if you're interested in research and applying research to your life, you might consider subscribing to my channel where I talk about such things. That's all I got. See you next time.