CEVAP:

Nominal scales are used for labelling variables. Some examples of nominal data are gender (male, female),traffic light colors (red, yellow, green) and blood type (0, A, B, AB).

In ordinal data, the order of labels is known and important, but the difference between each label is not clearly known. Suppose that you issue a query to a commercial search engine and you receive a list of documents. You can rank the relevance of each document in the list as “2” for highly relevant, “1” for relevant, “0” for irrelevant. The data collected by this assessment are the examples of ordinal data. Here, the relevance grades have an order or rank; that is, a grade of “2” is better than a grade of “1.” However, even though you have assigned a relevance grade to a document, this number is not a quantitative measure: Although a grade of “2” is clearly more relevant than a grade of “1,” it is not necessarily twice as relevant. The numbers are not mathematically measured or determined, but are merely assigned as labels for relevance grade.