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There are four primary scales of measurement used for classification purposes:
In this article we will specifically be delving into ‘ordinal data’ and its examples.
The word “ordinal” roots from the late latin word “ordinalis” meaning ‘relating to order in a series’. Therefore, as the name suggests, ordinal data is data/information that has a set order or scale to it. Being widely used in market research, it is a categorical & statistical data type in which variables are ordered without defined distances between the known categories.
Ordinal data is represented using “ordinal scales”. Ordinal scales allow you to determine whether an object has less or more of a certain characteristic than another. However, it is important to note that ordinal scales don’t outline how much less or more this difference is.
Two important factors that must be considered in regard to ordinal data:
To better understand these factors, let’s look at a popular form of ordinal data; the likert scale. This scale is used in market research surveys or questionnaires and is usually a five point scale where the respondents can choose from ‘strongly disagree’, ‘disagree’, ‘neutral’, ‘agree’, and ‘strongly agree’. This scale has a clear order. However, there is no way of identifying how different variables on this scale are from each other. The difference between “strongly agree” and “agree” may be more or less than the difference between “disagree” and “strongly disagree”.
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Let’s look at the following example to better understand the characteristics of ordinal data:
Choose a response based on how you feel about the following statement.
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A researcher conducts a study on social attitudes toward Marijuana and the following is a question in a survey for the research:
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