-: Hello, this is the video lecture on survey research
and it's gonna give you information on surveys
and how to do surveys,
as well as looking at different variable types
that you might get from a survey,
and to help you to identify
what kind of variable we have,
because that's a very important factor
in what kind of analysis that we will do with those data,
and something that we'll build on as we go.
So we're gonna look briefly at the idea of a survey
and what sort of topics they can cover.
We'll look at some tips on questionnaire construction,
the strengths and weaknesses of a survey,
and then look at variable types.
So I imagine many, if not all of you, have taken a survey.
It's a very well known method
and the basic definition is that the researcher
designs a standardized set of questions
that are then sent to and responded to
by a number of subjects.
So this is a good way of getting original data
from a fairly large group,
many of the same kind of questions
that you would ask in interviews, behaviors, beliefs,
awareness, attitude, knowledge,
things like that are the types of things
that we ask in social science research.
And because you can both, you get information
from a fairly large group because it tends to be organized
into fairly neat variables and such
that in many cases you can do statistical analysis
and even inference to larger groups in certain cases.
So surveys fall on the right-hand column of this continuum.
This is a chart that you should be pretty familiar with
and know by now, but you tend to get quantitative data
in a nomothetic approach.
You more often ask closed ended questions.
You analyze it through statistics
and they tend to be more reliable.
So this is a slide that you should be pretty familiar
and comfortable with and if you're not,
then we should spend some time in class
making sure that you are,
or you can come to my office hours and we can go over it.
So as we learned in interviews,
there's two main forms,
there's open-ended and there's closed-ended.
Generally speaking, interviews have more open-ended,
tell me about this, what are your experiences?
Whereas surveys tend to be closed-ended
where you have them write in, say a specific number,
like what year were you born or check from a list,
what is your race, what is your gender?
How strongly do you agree?
But for the most part, surveys have closed ended question.
So you get reliable, predictable data.
Each person only has the option
of a certain number of responses
and that makes it easier in certain ways
to analyze them, to count how many said what
and do a sort of correlation across variables.
So again, sometimes you do include an open-ended question
where you let the respondents say what,
put it into their own words.
And again, this sort of veers into qualitative work
and tends to be more valid,
whereas closed ended are more common in surveys.
Probably most of the surveys that you have taken
or administered have more closed ended.
And here you give the respondents a set of options
and they pick one or more that's best for you.
You wanna always sort of have,
either give a complete set of everything
that they might think, or say, give 'em the option of other,
and be clear if you want them to choose one
or choose all that apply to them.
If it is, choose one,
make sure that it's, they're mutually exclusive,
and because they are going to select
from a certain number of answers,
data that you get from closed ended questions
tends to be more reliable.
So here are some considerations
that the questions should be clear,
that just because you understand it,
just because you know what things mean,
that doesn't mean the respondents do,
you may need to define things.
You wanna avoid double barrelled questions such as
should we cut defense spending and fund education?
Maybe some want to do one or the other,
cut defense, but not for fund education,
not cut the defense but do fund education
so split that into two different questions.
You don't wanna lead on, sort of have your opinion,
you know, is CDAE the best department in the world
or things like that, where you know
it's clear where you're sort of going with this,
you want them to be much more neutral
and it's absolutely imperative that your respondent
is able to answer the question,
if not, then it's a completely useless exercise.
So they have to understand the question
and they have to know what the right answer is for them
and they must be able to respond
and sort of pick that right answer for them.
Sometimes you may need a I don't know option
and that can be an important thing.
You also want the survey to be as short as it can be.
And so you want the the respondent
to be able to fairly quickly read and answer,
read, know what the right response is for them
and choose that and not get bogged down
taking a very long survey
because in many cases if they get frustrated
they will just stop and you won't get a full set of answers.
So we talked about this before, these top three
are ones that we've already talked about,
general to specific, more important and safe to risky.
I prefer to put the demographics last.
Sometimes folks say at first because they are pretty easy
and they draw you in, but I think it's better to do it last.
The reason last, is if you ask
a bunch of demographic questions first,
especially things that sort of have to do
with their identity, maybe race, ethnicity,
religion, gender, gender identity, things like that,
then it may be that that is going
to sort of flavor their responses,
and they will think well, this is how someone
of my race, of my gender et cetera,
should be answering that.
So that is why I tend to put them last.
Have clear instructions, like, put an X
or click on this, et cetera.
It's good to break it up into subsections.
So sort of logical parts so they know sort of where they are
and where they're going,
and make sure that there are clear instruction.
Do you want them to only choose one versus all that apply,
if you rank sort of how well you do that or rating,
but just make sure that the instructions are very clear,
it's very important to pilot surveys.
Even if you think there are no errors,
it's very clear everything makes sense,
if you send it to folks and have them take it,
and send you feedback, they, in my experience,
they almost always find things wrong
that you can then fix and that's a good thing.
So it's good to do something,
like give it to 10 people who aren't your actual respondents
and you can ask 'em three things.
How long did it take you?
Because if it took you a lot longer,
it took them a lot longer than you thought,
again maybe become annoyed or demoralized
and not finish it.
Ask if there was anything unclear,
and then ask if they saw any errors,
any typos or spelling errors or anything like that.
All else, equals shorter is better,
15 to 20 minutes is probably the max,
and like get the information that you need
but don't ask things that you don't need,
because again it makes it longer,
and there's the risk that they will stop taking it.
So let's move to what are the strengths
and weaknesses of a survey?
So you get a larger number of responses
and in many ways the analysis is more straightforward.
You can look at frequencies and means things like that.
You can look at correlations,
and it's much more straightforward,
and you get much more reliable data.
The weaknesses are a lack of depth.
So if you choose, say choose from one of these five things,
maybe none of those five things
are really exactly what they think or feel,
so it may be less valid and you might miss things.
And last, it's hard to change things in midstream
that with an interview you can in some cases go back
and say, hey there's this a new question we have
based on what we learned that we know is important
and we want to ask it to you now,
much harder to add questions on a survey like that.
So now let's talk about the four types of variables
that you can get from a survey
or four types of variables in general,
and they are nominal, ordinal, interval and ratio.
Note that an interval is the rarest kind.
It's not really one that you and encounter much,
but they do exist and I will mention them,
but the other kinds are much more common
and it's very important that you are able
to identify what kind of variable is this
so that you can do the right analysis.
So we're really going to be building on this part
for much of the rest of the class
and it's important that you understand.
So we'll start with nominal,
these are also called categorical,
and you're just naming things.
So note that there's no higher or lower,
there's no more or less, there's no ranking.
And these are things like you know, nominal,
like, they only have names.
So if you say what state were you born in?
It's not like one state is is higher or lower
or et cetera.
What's your gender,
What's your eye color, your favorite sports team,
major et cetera, that these have no sort of ranking,
there's no numerical data, it's just pick one
that's right for you,
or pick one or more that's right for you.
Ordinal as you might guess have order.
So here this tends to be you're either ranking or rating,
so you can, you know that one is higher
or lower than another, but you can't tell
how far apart they are.
So let's say that you ask
what's your favorite ice cream flavor?
And someone says one, chocolate,
two, strawberry, three, vanilla.
So you know that they like chocolate more than strawberry,
and they like strawberry more than vanilla,
and you also know they like chocolate more than vanilla,
but two things that you don't know
are how far apart are they?
So you might really love chocolate
and then you only like strawberry
a little bit more than vanilla.
We often do as well a rating on a scale.
How do you agree, how often, things like this.
And in that same way you don't know how far apart
four and five are, and your strongly agree
and my strongly agree aren't necessarily the same.
You just know that I agree with,
if I say it's a 5, I strongly agree,
I agree with it more than if I had said 4, 3, 2 or 1.
And note that neither nominal nor ordinal have any units
and we're gonna see that the next two do.
So an interval is you can tell how far apart they are
and note that these have units.
Two very well known ones are degrees fahrenheit
or degrees celsius and year of birth.
So if it's for degrees,
if it was 20 degrees today and 40 yesterday,
you can say it's 20 degrees cooler,
but you can't say it's twice as cold or twice as warm,
same as year of birth.
So degrees is a unit, year is a unit.
But you can't say that someone
who was born in the year 1000
is twice as old as the person
or as young as the person born in the year 2000,
it sort of doesn't make sense in that way.
Ratio you can express.
So ratio not only has units, it has a true zero.
So if we look at how far apart
are Philly and Boston from Burlington
that you can say not only,
you could express it as an interval, it's 400 miles more,
but it's also a ratio 2.85 times farther.
So a ratio, so it has units.
So in these examples, it's miles, dollars and points.
And not only can you tell how far apart they are,
but you can express it as a ratio
and say this is twice as big or five times as,
or 3.12 times, et cetera.
So it can be expressed as a ratio.
And note that all these things have true zeros,
something could could be zero miles away,
someone might earn $0, and a team might allow zero points.
At least theoretically, these things make sense
whereas born in the year zero really does not make sense.
So here is a recap.
Again, make sure that you understand these,
and know what they mean,
and are able to identify and name them.
So if I would say on an exam,
look at this, what kind of variable is it?
That's something that you should know how to do.
If I would say give me an example
of an ordinal variable,
that's something that you should know how to do.
So make sure that you do and talk to me if you can't,
and we'll get you through it
'cause that's gonna be a really important task
and a bit of knowledge that you'll need
both for the exams and for the class project,
when we do our survey and we analyze the data.
That is what we did.
Here are the key things and thank you for your time.