Survey questions often use nominal and ordinal scales.
Nominal and ordinal refer to two of the four ways in which researchers "scale" data. Along with interval and ratio, nominal and ordinal are known as levels of measurement.
Nominal Rating Scale
According to the University of California-Davis (UCD) psychology department, a nominal level of measurement organizes data by name. Numbers assigned to these data are arbitrary. An example of a nominal scale is gender, with the choices labeled "male" or "female."
Ordinal Rating Scale
Ordinal data has all of the qualities of nominal data, but also indicates direction, notes UCD researchers. Psychological scales often use ordinal scales, such as indications of preference (e.g., low/medium/high).
Interval Rating Scale
Interval data has all of the qualities of ordinal data, except the distance between all scale items is the same, or has equal intervals. For example, temperature is an example of an interval scale because the difference between two degrees and three degrees is the same as the difference between 60 and 61 degrees.
Ratio Rating Scale
Ratio level data is the most complex of the four levels of measurement. Ratio level scales own all of the qualities of nominal, ordinal and interval data, but they also have an absolute zero. According to UCD, age, time, number of children and grade point average are examples of ratio level scales.
Understanding Nominal and Ordinal
Classifying someone as "extroverted" or "introverted" is an example of using a nominal scale, according to UCD. Setting up a similar scale as such--1 for shy, 2 for neither shy or outgoing and 3 for outgoing--indicates an ordinal level of measurement.
Tags: Rating Scale, between degrees, data qualities, difference between, difference between degrees