Characteristics of Ordinal Data
Ordinal data is a vital data type in various fields, including market research, social sciences, and psychology.
- Ordinal data has a distinct order or ranking among its categories means each category has a designated position in relation to the others.
- Ordinal data does not have persistent, measurable differences between categories, in contrast to interval or ratio data. Even while you are aware that one category is ranked higher than another, you are unable to pinpoint the precise measurement or value difference between the two.
- Ordinal data is inappropriate for meaningful mathematical operations like addition, subtraction, multiplication, and division because it lacks equal intervals and exact quantification. When attempting to compute proportions or averages using ordinal data, inaccurate conclusions may be reached.
- It allows researchers to measure partialities, sentiments, and attitudes of individuals or groups by capturing their relative rankings. For instance, in marketing, ordinal data can help understand customers’ preferences for different products or services.
What Is Ordinal Data?
Ordinal data is a form of categorical data that has a meaningful order among its categories. But, it lacks any numerical values or a fixed interval that can separate them from each other. In simple terms, ordinal data represents variables that can be ranked or ordered, but the precise difference between the ranks is not known. In this article, we will explore What is Ordinal Data, Its Characteristics, Analysis and Application of Ordinal Data.