From Steinberg (2011):
A nominal scale classifies cases into categories.
For that reason, it is also sometimes called a categorical scale.
- m = male, f = female
- 1 = married, 2 = divorced, 3 = separated, 4 = never married
- tel = owns a telephone, notel = does not own a telephone (p. 13)
An ordinal scale ranks people according to the degree to which they possess some measured trait.
Persons are first measured on some attribute (e.g., height). Then, they are assigned ranks according to how much of the attribute they possess (p. 13).
- 1 = tallest, 2 = second tallest, 3 = third tallest, and so on.
- 1 = highest grade point average (GPA), 2 = second highest GPA, 3 = third highest GPA,= and so on.
- 1 = fastest runner, 2 = second fastest runner, 3 = third fastest runner, and so on.
With an interval scale, the distances between adjacent scores are equal and consistent throughout the scale. Equal intervals on the scale imply equal amounts of the variable being measured. For this reason, the interval scale is sometimes referred to as the equal-interval scale (p. 14).
- Scores on the final exam in this course
- Scores on an intelligence test
- Degrees Fahrenheit or Celsius
- Scores on certain personality or career interest tests
- Because interval scales are consistent throughout the scale, it makes sense to compare scores by adding or subtracting them.
A ratio scale is like an interval scale, in that the distance between adjacent scores is equal throughout the distribution. However, unlike an interval scale, in a ratio scale there is an absolute zero point. That is, there is a point at which a person does not have any of the measured traits. Because the trait’s starting point is known, the scale reflects that zero point. Ratio measurement typically applies to measures in the physical sciences. Because there is an absolute zero point, it makes sense to compare scores by multiplying or dividing them (p. 15)
Steinberg, W. J. (2011). Statistics alive (2nd ed.). Thousand Oaks, CA: Sage Publications.