Sociology Research Methods: Crash Course Sociology #4


Do you think you’re middle class? If you’re American, there’s a pretty good
chance that you do. In a survey conducted by the Pew Research
Center in 2015, 87% of those surveyed identified
themselves as middle class. That’s a pretty big middle. But your intuition about what the middle class is –
like who it includes, and what constitutes a middle
class lifestyle – probably isn’t the full picture. And a lot of questions that sociologists try to
answer are questions just like this – questions that
you think you know the answer to already. Many a person has played the armchair
sociologist at some point in their lives – spouting off about how they think “Society
Really Works” because of their own experience. Or the experience of their friend’s brother’s
roommate. We all do it. But having personal opinions about the world
doesn’t make you a sociologist. Sorry. This is where sociological research comes
in: It helps us understand society’s patterns,
even when they go against our intuitions. Rather than using our gut to answer questions, we
use a research method, a systematic plan for gathering
and analyzing observations about the world. This is where we’re gonna learn how to do
sociology! [Theme Music] First things first: Research starts with a
question. And the key to deciding on a question is defining
the concepts that you’re studying, and making sure
that both you and your audience agree on what
those concepts mean. It’s like that thing with The Dress. Some people thought it looked black and blue,
and other people thought it looked white and gold. It turns out that some things that seem totally
objective just aren’t. And this becomes infinitely more complicated when you replace the concepts of blue or gold with concepts like the economy, poverty, parenting, education, or love. So, what if the way I am defining poverty
isn’t how you’re imagining poverty? What if we’re all seeing different levels of well-being
as being “poor,” but we refer to them all as “poverty”? That won’t work. So you have to define your concepts, which
becomes even more important when you get to
the next part of the research process: Stating a hypothesis – a statement of a
possible relationship between two variables. A variable is just something that can take
on many different values – it varies. Hence, the name! So before you can assign a value to a variable,
you have to operationalize it. That is, you have to define the exact variable you’re
going to measure, and exactly how you will measure it. For example, you can operationalize a variable
that you want to use to understand relationships,
by defining it as “reported marital status.” Only then can you assign each person in your sample
a number corresponding to their relationship status. Like 0 if they’re married, 1 if they’re
divorced, 2 if they’ve never been married,
etc., etc., until every person is labelled. And what value a variable takes on is called
its measurement. You can measure someone’s height, you can
measure someone’s income, and you can measure
someone’s relationship status. It doesn’t matter how many categories your
variable has: 0, 1, 2, 3, 4 whatever. What’s important is that the way you define
your categories is both reliable and valid. Suppose you decide to use Facebook relationship
status as your measure of relationship status among
your subjects. For your measurement to be reliable, you have
to be consistent in how you measure the variable. So, here’s what not to do: Say you have two categories for relationship
status: Single or Not Single. Two different sociologists are going through the
data, assigning values based on Facebook status. One decides that people who say “It’s
Complicated” get the label “Not Single,” while the other decides that these people
should be called “Single.” That’s not consistent. Every person with the same characteristics
– in this case, the same relationship status –
needs to be assigned the same value. And for your measurement to be valid, it has to
actually measure something that directly reflects
the concept that you’re trying to study. Facebook relationship status may be a useful
measure of whether someone’s single or not, but it’s not a valid measure of, say, their
political views. Once you know how you want to measure your variables, your hypothesis will be an educated guess about how they’re related – often using an if-then statement. Here’s an example of a hypothesis, based
on what I was talking about earlier: If someone lives in a city, then they are less
likely to refer themselves as middle class. In this case, geographic location is what
we call the independent variable; it’s the variable that we think is affecting
the change in how people describe themselves. But you can also have variables that you believe
are affected by changes in your independent variable;
these are your dependent variables. Your hypothesis is that they change when the
independent variable changes. But you have to be careful because correlation
does not always equal causation. Correlation is what happens when two variables
move together. It can be easy to misinterpret a correlation
to conclude that one thing causes the other,
when it really doesn’t. For example, murder rates tend to be high
when ice cream sales are high. But it’s ridiculous to think that more ice
cream causes more violence – or vice versa. What’s missing is a third variable: heat. More people commit crimes during hot months,
and more people buy ice cream then too. OK! Once you have your hypothesis, and you
know what types of variables you need to test it,
you’re at your next step: Collecting your data. There are four main ways that sociologists
collect data: Experiments, Surveys, Participant Observation,
and Existing Resources. Experiments in sociology work much as they
do in the natural sciences, just with humans as
subjects instead of mice or atoms of beryllium. Let’s go to the Thought Bubble to see a real life
example of how a sociology experiment works! In the 1990s, the US Department of Housing
and Urban Development conducted an experiment
known as The Moving to Opportunity study. In it, social scientists randomly assigned
low-income families into a control group or
one of two experimental groups. One group was a control group, which means
nothing was changed in their environments. This allowed for a comparison between them
and the experimental groups. They received a housing voucher that
allowed them to move to cheaper housing – often in a better neighborhood than they
were currently in – if they wanted to. Then, a whole bunch of data was collected
– and is still being collected – on many different short and long term
outcomes, including earnings, children’s educations,
and health outcomes. These outcomes are the experiment’s
dependent variables. So we have one independent variable –
receiving the voucher or not – and a bunch of possible dependent variables,
like earnings, education, and health outcomes. In an experiment, if the change you predicted occurs
for the experimental group but not for the control group,
then your experiment supports your hypothesis. And in the HUD experiment, sociologists compared
how the measures of well-being changed for the control
group, compared to those for the experimental group. One of the findings: those who received a voucher had better
mental health outcomes – such as lower rates
of depression – than those who didn’t. The data from Moving to Opportunity continues to
be studied to this day and is a key source of research
into how neighborhoods affect families’ well-being. Thanks Thought Bubble! The second method that researchers use is
a survey, where people respond to a set of
prepared questions. Typically, researchers are interested in the
responses of a specific group of people –
what we call the population of interest. Women aged 18 to 35. Veterans.
Left-handed people. Youtubers. Whoever your research question is about, this
is your population. But it’s unlikely you’ll be able to survey
the WHOLE population. Even government-run surveys, like the Census,
don’t reach everyone. So instead, you survey a sample – a smaller
group that’s representative of the population. And a survey can take many forms. There can be open-ended questions, or Yes
or No questions. The questions can appear in many different
orders, or be phrased in different ways. So, sociologists have to think carefully
about these things – and about whether the structure of their survey
might bias the respondents’ answers. Now, some research takes place in a much less
controlled environment. Tons of sociology research is done “in the field,”
through our third method, participant observation. Participant observation is when researchers
observe people by joining them in their daily routines. The result of this type of research is called
an ethnography. Researchers try to integrate themselves into
a community, hanging out with their subjects,
working with them, and so on. They’re both observers and participants. This type of data-collection tends to be exploratory
and descriptive. You’re not trying to prove a specific hypothesis. Instead you’re trying to understand the
lifestyle of your subject. Some say that this type of research is too subjective, but a major benefit of doing fieldwork is that it
lets you to gain insights into people’s behavior, in the
real world, in a way that experiments won’t. Take, for example, sociologist Alice Goffman’s
field work in Philadelphia. She spent six years living in a low-income,
crime-ridden neighborhood in West Philadelphia where she befriended and lived with two
young African American men and documented the ways the criminal justice system intersected and disrupted the lives of them, their families, and other members of the neighborhood. The documentation of lived experience like
that can provide insights that you just couldn’t
get simply from looking at statistics. Now, there’s one thing that’s important
note about these three types of research: When researchers interact with their subjects,
whether it’s through an experiment, an interview, or participant observation, they have to take
seriously the ethics of their research. Sociologists are answerable to an
Institutional Review Board, which ensures that all researchers take the privacy
and well-being of their subjects into consideration
when they design their research methods. For example, informed consent of the subject
is a must. This means that your subjects must know you’re
observing them, and must be made aware of any
risks they take by being part of your study. Not all research methods require you to interact
with subjects though, or even collect your own data. Many sociologists analyze existing sources
of data, collected by others. The most common of these sources is government
agencies, which collect statistics on income, health,
education, employment, marriage, fertility – I could keep going. The point is, these data sets are much larger
and cover more years than an individual researcher
could collect on their own. Plus, it saves time and money for the researcher. Once you’ve collected your data using one of these
methods, the final step is turning that data into
information that helps answer your question of interest. You can do this in two ways: through inductive
or deductive logical thought. Inductive logical thought takes your observations
and uses them to build a theory. You start with data and then use them to form
an idea about how the world works. For example, seeing the results of the Moving to Opportunity study might prompt a researcher to theorize that the neighborhood a person lives in is a key factor in their mental health. Deductive logical thought, meanwhile, uses an
existing theory to inform the hypothesis you test. In this case, you start with a theory and you
collect data that allows you to test the theory. Theories about the relationship between where you live and your child’s well-being is part of what prompted the government to not just collect data on the heads of household in the HUD study, but also on their children. And these two types of reasoning are not mutually
exclusive; within one study, a researcher will use both
to develop theories about the social world. And guess what?
You’re done! Today we discussed the research method: form a question and a hypothesis, collect
data, and analyze that data to contribute
to your theories about society. Crash Course Sociology is filmed in the Dr. Cheryl
C. Kinney Crash Course Studio in Missoula, MT,
and it’s made with the help of all these nice people. Our animation team is Thought Cafe and Crash
Course is made with Adobe Creative Cloud. If you’d like to keep Crash Course free for everyone, forever, you can support the series at Patreon, a crowdfunding platform that allows you to support the content you love. Speaking of Patreon, we’d like to thank all of our
patrons in general, and we’d like to specifically thank
our Headmaster of Learning David Cichowski. Thank you for your support.