Nominal is a type of variable that is not quantifiable by numerical values. Instead, they are categorized into labels or categories. Examples of nominal variables include gender, blood group, and occupation.

Key characteristics of nominal variables:

• Categorical: Values are grouped into categories or labels.
• Non-numeric: Cannot be arranged in numerical order.
• Discrete: Values can only take on specific discrete categories.
• Examples: Gender, blood group, color of hair.
• Analysis: Primarily used for descriptive statistics and categorization.

Examples of nominal variables:

• Gender (male, female, non-binary)
• Blood group (A, B, AB, O)
• Occupation (engineer, teacher, doctor, etc.)
• Color of hair (black, blonde, red, etc.)
• Marital status (single, married, divorced)

Statistical analysis:

Nominal variables are primarily analyzed using descriptive statistics such as frequency tables, crosstabulations, and proportions. They can also be used in categorical regression models.

Data representation:

Nominal variables are typically represented using categorical data structures, such as arrays or lists. Each category is assigned a unique numerical code or label.

Note:

Nominal variables do not have an inherent order or sequence, therefore they are not suitable for analysis using statistical methods that require numerical data.