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RESEARCH METHODS EXAM #29 STUDY GUIDE FULLY COVERED
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RESEARCH METHODS EXAM #29 STUDY GUIDE FULLY COVEREDVariable - correct answer A variable refers to a grouping of several characteristics.
Attributes are those characteristics.
A variable's attributes determine its level of measurement. There are four possible
levels of measurement; they are nominal, ordinal, interval, and ratio.
Nominal: This is the most basic level of measurement. Relationship status, gender,
race, political party affiliation, and religious affiliation are all examples of nominal-level
variables. One unique feature of nominal-level measures is that they cannot be
mathematically quantified.
Ordinal: level can be rank ordered, though we cannot calculate a mathematical distance
between those attributes. We can simply say that one attribute of an ordinal-level
variable is more or less than another attribute.
Examples of ordinal-level measures include social class, degree of support for policy
initiatives, television program rankings, and prejudice.
Measures meet all the criteria of the two preceding levels, plus the distance between
attributes is known to be equal. IQ scores are interval level, as are temperatures.
Interval-level variables are not particularly common in social science research, but their
defining characteristic is that we can say how much more or less one attribute differs
from another.
We cannot, however, say with certainty what the ratio of one attribute is in comparison
to another.
For example, it would not make sense to say that 50 degrees is half as hot as 100
degrees.
Attributes can be rank ordered, the distance between attributes is equal, and attributes
have a true zero point.
Thus with these variables, we can say what the ratio of one attribute is in comparison to
another.
Examples of ratio-level variables include age and years of education. We know, for
example, that a person who is 12 years old is twice as old as someone who is 6 years
old.
Levels of measurement: nominal - correct answer Nominal is the most basic level of
measurement, and every level after this assumes the properties of the level before it. So
ordinal has the properties of nominal (as well as a new property), interval has the
properties of ordinal AND nominal and so forth.
Cases are classified into two or more "unordered categories". We can only say that
cases in these categories are different from one another, but there is no inherent
contimuum.
The phrase "nominal" means "referring to name or names." This may help you
remember that the nominal level of measurement only allows us to distinguish (or
"name") things. This means we can only classify data into two or more "unordered"
categories. Although this may not even seem like "measurement" per se, it really is.
Ex: Consider that you are doing a survey of people to ask about their hobbies and
commitments. You know that many people have pets and you ask them what kind of
pets the have. You find that people have cats, dogs, "other pets", and some people
,have no animals. The variable in this case is "pet species" or "pet types" with the
response categories or attributes of the variable being "cat," "dog", "other", and "none".
These data are nominal because we can only say that with regard to this variable, our
respondents are merely different from one another. We can't say one is "better" or
"more" than the other.
These data have no mathematical properties. We can't get into "greater than" or "less
than" statements or put the data in any type of order. Another way of thinking about this
is that there is no clearly inherent continuum to this measure.
Real life use: But this crudest form of measurement is very useful. For example, if you
were a pet sitter you may want to order products for your clients and it would be good to
measure what percentage of your clients have cats or dogs or fis
Levels of measurement: ordinal - correct answer Like the nominal level of
measurement, we continue to use categories, but now we can place those categories
into an order that begins to measure an inherent continuum.
In Sociology we are really interested in Social Class, and we talk about things like
lifestyle differences between lower, middle and upper class individuals.
One of the important things to see about these ordered categories is that again there is
NO mathematical property we can use to say how much more one category is than
another. A person with a college degree doesn't have, for example, twice as much
education as someone with only a high school degree. We just know they have more.
Levels of measurement: interval - correct answer Interval measures have exactly what
they say the do - intervals... Measurable intervals between categories.
In our previous examples of nominal and ordinal measures we either couldn't imagine a
continuum along which to rank categories, or we didn't know where on such a
continuum to place the categories.
But sometimes we have measures that have clearly identified scales where we can say
how much greater is one category over another.
Example: You are familiar with "temperature" where you know that 100 degrees is 10
degrees greater than 90 degrees, or where you know that 100 degrees is two times 50
degrees. In the social sciences we are less likely to be thinking about "temperature" and
more likely to be thinking about things like "household size", "age of mother at first
birth", or maybe "square footage of someone's home".
Interval scales are very common when social scientists are interested in comparing
larger aggregates like cities, counties, or states. For example, if we were interested in
comparing countries' crime rates we might measure the number of crimes per 100,000
residents. With this kind of measure, we can make statements like "the rate doubled" or
"this rate is twice that rate".
Interval scales don't have to start at zero. For household size, or mother's age at first
birth, or square footage of one's home, the lowest number has to be something greater
than zero. But if you think about a national crime rate, conceivably it could be zero.
Levels of measurement: ratio - correct answer If an interval scale has a zero at it's
lowest end of the continuum, then it is more precisely referred to as a ratio scale. So the
, ratio level of measurement has all the properties of the other levels of measurement but
with this one added quality - a zero end-point.
Other variables in the social sciences have this quality: age, number of times married,
number of traffic tickets, etc. All conceivably have a zero as a possible score.
Reliability vs validity concerns - correct answer One common problem of reliability with
social scientific measures is memory. If we ask research participants to recall some
aspect of their own past behavior, we should try to make the recollection process as
simple and straightforward for them as possible.
With validity we need outside sources. We can't trust the validity of something just from
data. The data could be missing something important.
Reliability - correct answer Reliability in measurement is about consistency. If a
measure is reliable, it means that if the same measure is applied consistently to the
same person, the result will be the same each time.
One common problem of reliability with social scientific measures is memory. If we ask
research participants to recall some aspect of their own past behavior, we should try to
make the recollection process as simple and straightforward for them as possible.
Addresses the stability and consistency of the measure across time, different subjects,
and when using multiple indicators (ie looks at the repeatability of the measures)
With the scale if every time you get on it it says something different but it is all around
the same number that is your true weight the scale is not reliable but it is somewhat
valid.
Addresses the stability and consistency of the measure across time, different subjects,
and when using multiple indicators (ie: looks at the repeatability of the measures)
Validity - correct answer While reliability is about consistency, validity is about shared
understanding. What image comes to mind for you when you hear the word alcoholic?
Are you certain that the image you conjure up is similar to the image others have in
mind? If not, then we may be facing a problem of validity.
To be valid, we must be certain that our measures accurately get at the meaning of our
concepts.
At its core, validity is about social agreement.
One way to think of validity is to think of it as you would a portrait. Some portraits of
people look just like the actual person they are intended to represent. But other
representations of people's images, such as caricatures and stick drawings, are not
nearly as accurate. While a portrait may not be an exact representation of how a person
looks, what's important is the extent to which it approximates the look of the person it is
intended to represent. The same goes for validity in measures. No measure is exact,
but some measures are more accurate than others.
Addresses how good the fit is between the measure and the concept it is intended to
measure (ie: are we measuring what we want?")
With validity we need outside sources. We can't trust the validity of something just from
data. The data could be missing something important.
With a scale. If every time you get on it it says the same incorrect weight then the scale
is reliable at least but it's not valid because you yourself know it's not your true weight.
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