This lesson will define and discuss hypotheses (independent and dependent variables), sampling, and snowball sampling as they pertain to sociological research. Max Weber's ideas of value-free and value-relevant research will also be addressed.
Source: Intro Music by Mark Hannan; Public Domain
Hello, and welcome to Sociological Studies. As always, thank you for taking the time out of your busy day to study society. The topic of today's lesson is going to be conducting sociological research. We're going to look at the process of sociological knowledge making and come to understand how we get from broad questions and interest to actual codified sociological knowledge.
Let's start by looking at two areas of concern with social research that were first identified by German sociologist Max Weber and his famous essay "Objectivity in the Social Sciences." And those are the issues of value-relevant research versus value-free research. So value-relevant research, again, this idea given to us by Max Weber, value-relevant research is a recognition that your values guide you to your research topics.
So for instance, I'm concerned about economic equality in the United States. So I might be interested in how wealth and success transfers from generation to generation. So this was an example of how my values oriented me in the direction of what I want to study. I mean, I'm not going to devote so much time to studying something I don't really think is valuable or interesting. So Weber recognized that and he knew that.
But then given that, that doesn't let us just let our values cloud and bias our research. So that's what he means by value-free research. So this states that research should be objective. We don't let the values that guided us to our research topics bias the research itself. So I'm not going to let my concern for the poor in this country lead me to fudge my results and bias my research. So Weber made sure it was clear that we didn't let our values cloud our research.
Once you've decided on your research questions, again often by your values, we select variables to study and hypotheses to test. Well, a variable is a characteristic, such as your age, your class, your income level, or level of education, whether you're married or single, et cetera. A characteristic that varies throughout the population as a whole, it's something that changes and is different and we can use to study differences between people and groups.
So that's a variable. And honing in on particular variables then allows us to isolate them in order to analyze their influence and determine what we want to know. A hypothesis, which is commonly known as an educated guess, is a statement or conjecture about how variables are related. So with my study that was interested in the effects of wealth transfer through generations, I might look at how your father's education level relates to your life earnings or income level. I want to know if how educated your father is, how that affects your income later on.
I hypothesize, then, that if your father was educated, you're going to have higher life income. So I made a statement about how the variable father's education was related to the variable your income level. Not all variables are created equal. Some are really important for explaining your life income level, and some really aren't all that important, meaning they don't strongly relate to the outcome that we're trying to explain, which is your life income level.
So variables are different. We have independent variables and dependent variables. An independent variable is the thing that causes the change, or it causes the outcome. You can look at it as the cause. So in our example, the independent variable is father's education level. It changes. It's different.
The independent variable then is what drives the change in the dependent variable. So you can think of the dependent variable as the effect or the variable that is influenced by the other. OK, so in this case, the dependent variable is your income level. We are hypothesizing that father's education level affects your income level.
Well, you might be asking, what do we do when we gravitate towards a topic, come up with a hypothesis, and hypothesize a relationship between an independent variable and a dependent variable? How do we go from there? Well, we need to get a sample. We need to get a sample of the population as a whole.
A sample is just that. It's a smaller group of subjects that ideally represents the population as a whole. We sample because it is impossible to go and ask everyone, so we can't. So we have to just take a slice of the population as a whole. The goal then is to have a representative sample where all facets of interest of the study are included.
So in my study about father's education and your income, I wouldn't have a representative sample if I went out and got data from 100 people with highly educated fathers and two people with fathers that didn't finish high school. How could I make conclusions on just the two? So I would ideally want 33, 33, and 33.
And I might have a more representative sample. Representativeness is what we strive for with sampling. An effective way to get a sample is through a technique called snowball sampling, which is where you find your initial respondents or subjects through acquaintances that you might already have in your network. And then use those acquaintances to find acquaintances of acquaintances, and it just snowballs and on and on and on.
Well, I hope you enjoyed learning about how values influence research and how we need to keep those values at bay when we're actually conducting our research, ideas given to us by German sociologist Max Weber, as well as ideas of a variable, independent variable, dependent variable, and sampling. Thank you for joining me, and have a great rest of your day.
A sampling technique where initial subjects are found through acquaintances, and later subjects are found through acquaintances of acquaintances.
A smaller group of subjects that ideally represents the larger population as a whole.
The effect of the change.
The cause of the change, or what drives the change in the dependent variable.
Commonly known as an educated guess; a statement about how two or more variables are related.
A characteristic such as age, education, income, married, or single that can vary throughout the population.
Research must be objective and should not be biased by our values, principles, or beliefs.
An acknowledgment that our values guide us to our research topics; we study what we find valuable and interesting.