With nominal data, each category is mutually exclusive to the next and there is no crossover between the respective categories. Examples of such nominal scale variables include such factors as gender, employment status or college graduate. This is not a hugely informative measure as a category is simply selected and detailed information is lacking.
A useful way of remembering the meaning of a nominal scale variable is that a category is ‘nominated’ in each scenario hence nominal. In fact, the word nominal derives from the late word for ‘name’ which is nomin.
Nominal scale variables occur where data is put into a certain set of categories. Further examples would include categorizing the type of internet provider you use from a selection or the type of insurance you possess. In econometrics, these nominal scale variables are known as dummy variables.
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