For example, the difference between the two income levels “less than 50K” and “50K-100K” does not have the same meaning as the difference between the two income levels “50K-100K” and “over 100K”.

Note the differences between adjacent categories do not necessarily have the same meaning. Socio economic status (“low income”,”middle income”,”high income”), education level (“high school”,”BS”,”MS”,”PhD”), income level (“less than 50K”, “50K-100K”, “over 100K”), satisfaction rating (“extremely dislike”, “dislike”, “neutral”, “like”, “extremely like”). Genotype, blood type, zip code, gender, race, eye color, political partyĪn ordinal scale is one where the order matters but not the difference between values. You can code nominal variables with numbers if you want, but the order is arbitrary and any calculations, such as computing a mean, median, or standard deviation, would be meaningless. Knowing the scale of measurement for a variable is an important aspect in choosing the right statistical analysis.Ī nominal scale describes a variable with categories that do not have a natural order or ranking. These are still widely used today as a way to describe the characteristics of a variable. In the 1940s, Stanley Smith Stevens introduced four scales of measurement: nominal, ordinal, interval, and ratio.

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