The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the United States. These parks can be ranked from one to five based on size and biodiversity, but the differences among those ranks cannot be measured. Another example of ordinal scale data is a cruise survey where the responses to questions about the cruise are “excellent,” “good,” “satisfactory,” and “unsatisfactory.” These responses can be arranged from the most desired response to the least desired. However, it is not possible to measure the differences between any two pieces of data. Ordinal scale data cannot be used in calculations like the nominal scale data.
This text is adapted from Openstax, Introductory Statistics, Section 1.3 Frequency, Frequency Tables, and Levels of Measurement
