Russel-Research-Method-in-Anthropology

The Foundations of Social Research 47
When you assign the numeral 1 to men and 2 to women, all you are doing is
substituting one kind of name for another. Calling men 1 and women 2 does
not make the variable quantitative. The number 2 happens to be twice as big
as the number 1, but this fact is meaningless with nominal variables. You can’t
add up all the 1s and 2s and calculate the ‘‘average sex’’ any more than you
can add up all the telephone numbers in the Chicago phone book and get the
average phone number.
Assigning numbers to things makes it easier to do certain kinds of statistical
analysis on qualitative data (more on this in chapter 17), but it doesn’t turn
qualitative variables into quantitative ones.
Ordinal Variables
Like nominal-level variables, ordinal variables are generally exhaustive
and mutually exclusive, but they have one additional property: Their values
can be rank ordered. Any variable measured as high, medium, or low, like
socioeconomic class, is ordinal. The three classes are, in theory, mutually
exclusive and exhaustive. In addition, a person who is labeled ‘‘middle class’’
is lower in the social class hierarchy than someone labeled ‘‘high class’’ and
higher in the same hierarchy than someone labeled ‘‘lower class.’’ What ordinal
variables do not tell us is how much more.
Scales of opinion—like the familiar ‘‘strongly agree,’’ ‘‘agree,’’ ‘‘neutral,’’
‘‘disagree,’’ ‘‘strongly disagree’’ found on so many surveys—are ordinal measures.
They measure an internal state, agreement, in terms of less and more,
but not in terms of how much more.
This is the most important characteristic of ordinal measures: There is no
way to tell how far apart the attributes are from one another. A person who is
middle class might be twice as wealthy and three times as educated as a person
who is lower class. Or they might be three times as wealthy and four times as
educated. A person who ‘‘agrees strongly’’ with a statement may agree twice
as much as someone who says they ‘‘agree’’—or eight times as much, or half
again as much. There is no way to tell.
Interval and Ratio Variables
Interval variables have all the properties of nominal and ordinal variables.
They are an exhaustive and mutually exclusive list of attributes, and the attributes
have a rank-order structure. They have one additional property, as well:
The distances between the attributes are meaningful. Interval variables, then,
involve true quantitative measurement.
The difference between 30C and 40C is the same 10 as the difference