I. Nominal Scale
The nominal scale of measurement is the simplest level of measurement in statistics. It categorises data into distinct categories or labels, where each category represents a different attribute or group. Nominal data lacks any inherent order or ranking, and there are no meaningful numeric values associated with the categories. It is primarily used for classification and organising data into discrete groups. Nominal data is suitable in various situations when dealing with categorical or qualitative variables that can be divided into distinct, non-overlapping categories or groups.
Examples of Nominal Scale
- Gender: The categories of male, female, and non-binary represent a nominal scale. These categories are distinct, but there is no inherent order or numeric value associated with them.
- Types of Fruit: Categorising fruits into groups like apples, bananas, and oranges is another example. These categories are distinct and used for classification, but they do not represent any numeric values or ordering.
- Marital Status: Marital status categories such as single, married, divorced, and widowed are nominal. They classify individuals into different marital groups, but there is no inherent order among them.
Characteristics of Nominal Scale
- Mutually Exclusive Categories: Each data point can belong to only one category, and categories are mutually exclusive. For example, an individual cannot be both male and female simultaneously.
- No Inherent Order: The categories do not have a natural order or ranking. In the gender example, there is no inherent order among male, female, and non-binary.
- No Arithmetic Operations: Nominal data does not support meaningful mathematical operations like addition, subtraction, or multiplication. You cannot perform calculations like finding the average (mean) or taking the difference between categories.
- Mode as the Measure of Central Tendency: The most suitable measure of central tendency for nominal data is the mode, which simply identifies the most frequently occurring category.