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

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

A common feature of marketing research is making respondents communicate their feelings, attitudes, opinions, and evaluations in some measurable form. Hence the need for a range of scales, 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 preceding it. We will discuss examples of four variables that could be measured by nominal, ordinal, interval, and ratio in this article.

Nominal Scale

The nominal scale is also called the unordered categorical or discrete scale. It is often regarded as the most basic form of measurement. Researchers can use it to classify individuals, companies, products, brands, and other entities into categories where no order is implied. “Numbers, such as driver’s license numbers 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 uses simple unique identifies to label each distinct type 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 the characteristic being scaled. “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 given. Together with this, it is also possible to determine positional statistics such as the median, quartile, and percentile, Thus 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, the difference between two variables is meaningful and equal, but 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. They permit the researcher to compare both differences in scores and the relative magnitude of scores. “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 type of 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 you can add up, divide, get averages, etc. With qualitative variables, it’s a bit trickier.

However, no variables are 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 provides info about the order of options. Interval gives both the order of importance and the ability to quantify the difference between them while ratio provides the order with, interval values, and the ability to calculate ratios.

Check the following reference articles to learn more about the Measure Variables in terms of 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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