-: Hello and welcome to this video lecture on indexes,
scales and typologies.
And these are tools that we can use
to sort of understand attributes
in our research subjects.
Are they high or low?
And sort of how can they compare with other subjects?
So indexes and scales, which is gonna be the majority
of this talk, are both ordinal variables.
That means that we can tell the order of things
that on a scale of one to five, if I like,
if I say this is a five and this one is a two,
it means that I like the one I gave a scale of five better
to two, but they don't have units.
And your five and my five may not be the same thing,
that you can order them from things
that I feel most strongly about
to things I feel least strongly about.
But it's very hard to compare your answers to mine.
And we'll see a few examples of this.
And both indexes and scales are ordinal.
So indexes tend to be more of a composite score of things,
a composite rating.
So one example of if you wanted to sort of measure
how much of an NFL football fan is someone,
well, one of the ways is, so here's an example
of five questions that you can ask.
Have you ever attended a game live?
Do you at least name one per week, watch one game per week?
And then by adding up all the yeses, that might be one way
of saying this person is a very, you know, strong fan
or big fan and this person is not a fan at all,
and a number of points in between.
And they should be sort of equal intensity,
that if you would ask a question like,
can you name every single player on every single team,
hardly anyone will be a yes there.
So that's really not a useful question.
And something like, have you ever heard of the NFL,
almost everybody will be a yes.
So those would not be very useful in sorting people
and sort of rating how much of a fan they are.
Note that in this example,
that everything gets an equal weight,
that you would just add up the number of yeses
and that would be their score, that would be their index.
But it's also possible to assign different weights to them,
that if you think one question does a better job
of answering than another,
you could give that a greater weight
and sort of make it like twice as important
or something like that.
The key is to be clear on why you select those questions
and why you assign those weights,
that we all wouldn't do it exactly the same way.
But it's important that a reader
or someone who's looking at your work understands
why you did it that way, that it's logical,
that it makes sense.
So when you're thinking about these questions,
there's a few factors.
First, is it logical, does it make sense?
Does it tell us something about what we want to measure?
You know, if we're measuring NFL fans
and you ask, are you wearing blue socks,
that doesn't have anything to do with it.
So it wouldn't be logical.
So you wanna ask questions that really do a good job
of understanding it and you want them to vary,
that what you want out of an index
is to sort of divide your subjects into some sort of high,
medium, low, to rate them on some overall number,
maybe zero to 100 is often a way to do it.
And like where the zeros are, they are not that thing at all
and 100s are wow, they are really that thing,
they're like the most, and then many points in between.
So here's another example about job related depression.
You can add all these up
and sort of see how much of an issue is this?
Is this person experiencing job related depression?
That those that would have a low score,
this really is not a big problem for them.
Those that have a high score, this is a big issue
and it needs to be dealt with.
Here's another example of an index
that measures the gender gap in development across nations.
So very often in social science
we use what are called Likert scales.
Maybe the most common thing is a five point scale
where you ask some sort of a statement
and you ask on this five point scale
where one equals strongly disagree,
two equals somewhat agree, three equals neutral,
four equals somewhat agree, five equals strongly agree,
and you let somebody sort of rate themselves on that scale.
They can also ask sort of likelihood,
how likely are you to do this thing?
How often do you do this thing?
You could rate a quality of something
from very poor to very good.
How important is this thing?
There's many, many ways
in which these Likert scales can be used,
and we use them a great deal in social science
to sort of map out where does someone fall on this?
How important is this, how likely are you?
Things like that.
The five star is a five point scale.
How would you rate this Airbnb,
this delivery service, this app, all kinds of stuff.
It's become a very well-known scale of five stars.
One star, you know, one star is very bad,
five star is great, and then points in between.
So I think you're probably already familiar
with these things.
So, so far we've been looking at, at least in scales,
sort of one dimension at a time.
One of the things that we can do
are perceptual maps or typologies.
The term perceptual map is often used in marketing,
whereas typology is used in more
in social science and psychology,
and it sort of measures someone across multiple dimensions.
So here is a two dimensional map of cereal,
where the Y axis is taste and the X axis is nutrition.
And you can tell sort of where do various cereals lie.
And this is also used in social science too.
Here is one of a political map
where the Y axis is authoritarian and libertarian
and the X axis is more sort of left, right in the economic.
And have a look at things like that.
Many of you may have taken a Myers-Briggs test.
So this is a four dimensional, which looks at four sort
of psychological personality,
whether you're an introvert or extrovert
or whether you see the big picture or details,
whether you sort of go by sort
of rational things or emotions
and whether you like to make a plan
or just go with the flow.
And there are a lot of these two that one can use.
So that is what we did.
We talked about indexes, we talked about scales,
and we talked about typologies, thank you.