Measure Variables in terms of Nominal, Ordinal, Interval, or Ratio Scaling in Accounting

Measure Variables in terms of Nominal, Ordinal, Interval, or Ratio Scaling - NetizenMe online magazine
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A common feature of marketing research is having respondents communicate their feelings, attitudes, opinions, and evaluations in measurable form. Hence, a range of scales is needed, including nominal, ordinal, interval, and ratio scaling. These four are often referred to as measure levels because each provides more information on the variable than the preceding one. This article will discuss examples of four variables that could be measured: nominal, ordinal, interval, and ratio.

Measure Variables in terms of Nominal, Ordinal, Interval, or Ratio Scaling

Nominal Scale

The nominal scale, also known as the unordered categorical or discrete scale, is often regarded as the most basic form of measurement. Researchers can use it to classify individuals, companies, products, brands, and other entities without implied order.

“Numbers, such as driver’s license and product serial numbers, are used to name or identify people, objects, or events” (Lee, 2014).

This scale assigns events or objects into discrete categories, “labeling variables without any quantitative value” (Guy, 2020). It labels each distinct type using unique identifiers and involves a simple count of the frequency of cases assigned to various types.

Examples of this scale include gender (male, female), race (black, white, other), political party (democrat, republican, other), etc.

Ordinal Scale

The ordinal scale involves ranking individuals, attitudes, or items along a continuum of scaled characteristics.

“Numbers represent rank order and indicate the order of quality or quantity, but they do not provide an amount of quantity or degree of quality” (Lee, 2014).

“Ordinal scales are typical measures of non-numeric concepts like satisfaction, happiness, discomfort, etc.” (Guy, 2020).

Examples of ordinal scales are rankings, top 10 brands, top 10 companies with the best customer service, etc. 

An ordinal scale provides all the information a nominal scale would have. Positional statistics such as the median, quartile, and percentile can also be determined, ascertaining the degree to which two or more survey respondents agree on their ranking of a set of items.

Interval Scale

The interval scale refers to the level of measure where there is order, and the difference between two variables is meaningful and equal. However, the scale lacks a true zero. This scale provides the order and exact differences between the values, giving you more information than the ordinal scale. An example of an interval scale is the Celsius temperature because the difference between each value is the same.

Ratio Scale

The ratio scale is the highest level of measurement, with all the properties of interval variables plus a natural absolute zero. It permits the researcher to compare differences in scores and their relative magnitude.

“Physical characteristics of persons and objects can be measured with ratio scales, and, thus, height and weight are examples of ratio measurement” (Lee, 2014).

“Ratio scales tell us about the order, they tell us the exact value between units, AND they also have an absolute zero–which allows for a wide range of both descriptive and inferential statistics to be applied” (Guy, 2020). 

Practical considerations of which scale to use

The marketing research type falls under comparative and non-comparative scaling. In relative scaling, respondents are asked to compare one brand to the other.

With non-comparative, respondents only need to evaluate a single brand independent of the other. Then, depending on the variable that needs to be measured, a choice is made on which scale to use.

There are two large supercategories of variables: qualitative and quantitative. The four levels of measure fall into these two groups.

For example, interval and ratio variables are quantitative, while nominal and ordinal are qualitative. Quantitative variables have numbers that can be added up, divided, averaged, etc. However, it’s a bit trickier with qualitative variables.

However, no variable is better than the other, and the choice of which to use depends on the research being carried out. Nominal scales label a series of values. Ordinal scales provide information about the order of options.

Interval scales give both the order of importance and the ability to quantify the difference between them, while ratio scales provide the order with interval values and the ability to calculate ratios.

Check the following reference articles for the Measure Variables in Nominal, Ordinal, Interval, or Ratio Scaling.

  1. Guy, M. R. (2020, October 5). Types of Data & Measurement Scales: Nominal, Ordinal, Interval, and Ratio. My Market Research Methods. (URL)
  2. Lee, J. A. (2014, November 7). Measurement scale | statistical analysis. Encyclopedia Britannica. (URL)
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