Different Scale of Measurements – nominal, ordinal, interval and ratio scales

The level or scale of measurement depends on the properties of the data. There are four
types of scales are used in business research. These include nominal, ordinal, interval and ratio scales. Variables can be classified as discrete or continuous.

What is a Nominal Scale?

A nominal scale is the simplest type of scale. The numbers or letters assigned to objects serve as labels for identification or classification. For example, names, player list, gender are categorical variables; and one can put the level ‘M’ for Male and ‘F’ for Female, or ‘1’ for male and ‘2’ for female, or ‘1’ for female and ‘2’ for male. Other examples include marital status, religion, race, colour and employment status, and so forth.

What is an Ordinal Scale?

When a nominal scale follows an order then it becomes an ordinal scale. In other words, an ordinal scale arranges objects or categorical variables according to an ordered relationship. Ordinal data are often referred to as ranked data because the data are ordered from highest to lowest, or biggest to smallest.  So, the ranking of nominal scales is an essential prior criterion for ordinal scales. A typical ordinal scale in business research asks respondents to rate career opportunities and company brands as ‘excellent, ‘good’, ‘fair’ or ‘poor’. Other examples would be (i) result of examination: first, second, third classes and fail; (ii) quality of products.

What is an Interval Scale?

The interval scale indicates the distance or difference in units between two events. In other words, such scales not only indicate order but also measure the order or distance in units of equal intervals. It is important to note that the location of the zero points is arbitrary. To take an example, in the price index, the number of the base year is set to be usually 100. Another classic example of an interval scale is the temperature where the initial point is always arbitrary.

What is a Ratio Scale?

Ratio scales have absolute rather than relative quantities. In other words, if an interval scale has an absolute zero then it can be classified as a ratio scale. The absolute zero represents a point on the scale where there is an absence of the given attribute. Ratio data have all four properties of measurement—identity, magnitude, equal unit size, and absolute zero. For examples, age, money and weights are ratio scales because they possess absolute zero and interval properties.