Scales of measurement project how the variables are defined and characterized. Any measurement can be evaluated on the basis of type, magnitude, intervals and true zero. These parameters are fundamental to any data analysis.

Identification of these parameters led to the definition of four scales of measurement, which are elaborated below –

Nominal scale of measurement

Some qualities or variables are not quantifiable. They cannot be put into comparative or measurable structures and can be understood as a type of data. Such data is commonly referred to as nominal data, and variables pertaining to nominal data are studied as a part of the nominal scale of measurement. A simple example of a nominal scale of measurement is the nationality of a person.

Ordinal scale of measurement

Some qualities or variables are not quantifiable but are comparable. Hence these data have a type and magnitude. Each value can be ranked with respect to one another and ordered in a sequence. Consider user feedback after a product service. The customer is very dissatisfied, dissatisfied, neutral, satisfied or very satisfied in the same order. This data can be compared but can’t be quantified. If User A is satisfied and User B is dissatisfied, the company can figure out that User B is unlikely to use the service.

Interval scale of measurement

Interval scale of measurement deals with qualities or variables which are quantifiable and comparable. They can be segregated into blocks of values, and the data can be captured in those different blocks. This scale of measurement has elements of nominal and ordinal data along with the segregation of intervals. For example, the user age group is an example of an interval scale of measurement. Consider the product to be consumed by people in the age group of 20 to 50. A better determination of demographic consumption can be determined by segregating the customers into groups of five years. Example – 20-25 years, 25-30 years and so on.

Ratio scale of measurement

The ratio scale of measurement takes into account all other three types of scales. These values are quantified and comparable. They always have a baseline value – a true zero. These values can be added, subtracted, divided and multiplied, and the output is also useful information. Example – distance travelled. The distance can be added to quantify cumulative distance. The distance can be divided by time to get the speed.

These scales of measurement provide the researchers with excellent means to study different types of data and summarize the results conclusively by providing a semblance of structure to unstructured information.

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