Nominal level of measurement is the lowest level of measurement and is characterized by categorical data without any inherent order or magnitude. Variables at the nominal level can be classified into distinct categories or groups, but these categories do not have any quantitative value or ranking associated with them. In nominal measurement, variables are typically represented by labels or codes.
Key characteristics of nominal variables are:
1. Distinct Categories: Nominal variables have mutually exclusive categories that do not overlap. Each category represents a different attribute or group.
2. No Order or Ranking: The categories of nominal variables do not have any inherent order or ranking. They are simply labels or names to differentiate between groups.
Examples of nominal variables include:
• Gender: Categorical categories of male and female.
• Marital Status: Categories such as single, married, divorced, or widowed.
• Ethnicity: Categories representing different ethnic or racial groups.
• Types of Animals: Categories like cat, dog, bird, or fish.
• Colors: Categories representing different colors such as red, blue, or green.
In statistical analysis, nominal variables are often used for qualitative or categorical data. They can be summarized using frequencies and proportions or displayed in bar charts or pie charts. However, mathematical operations like addition, subtraction, or calculation of means are not applicable to nominal variables because they lack numerical values or an inherent order.
