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Nominal variables
allow for only qualitative classification. That is, they can be measured only
in terms of whether the individual items belong to some distinctively different
categories, but we cannot quantify or even rank order those categories. Typical
examples of nominal variables are gender, race, color, city, etc.
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Ordinal variables
allow us to rank order the items we measure in terms of which has less and
which has more of the quality represented by the variable, but still they do
not allow us to say "how much more.” A typical example of an ordinal
variable is the socioeconomic status of families. An ordinal scale is an
ordered set of categories. Ordinal
measurements tell you the direction of difference between two individuals
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Interval variables
allow us not only to rank order the items that are measured, but also to
quantify and compare the sizes of differences between them. An interval
scale is an ordered series of equal-sized categories. Interval measurements identify the direction
and magnitude of a difference. The zero
point is located arbitrarily on an interval scale. For example, temperature, as
measured in degrees Fahrenheit or Celsius, constitutes an interval scale.
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Ratio variables are
very similar to interval variables; in addition to all the properties of
interval variables, they feature an identifiable absolute zero point, thus they
allow for statements
such as x is two times more than y. Ratio
measurements identify the direction and magnitude of differences and allow
ratio comparisons of measurements. Typical examples of ratio scales are measures
of time or space.
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