Scales of Measurement

Scales of measurement refer to the different ways in which variables can be categorized, ranked, or quantified. There are four main types of measurement scales in statistics and research:

1. Nominal Scale (Categorical Data)

Used for labeling or categorizing data without any quantitative value.

No inherent order or ranking among categories.

Example: Gender (Male, Female), Blood Group (A, B, AB, O), Eye Color (Brown, Blue, Green).

2. Ordinal Scale (Ranked Data)

Data is arranged in a meaningful order, but differences between values are not uniform.

Rankings convey relative position but not the exact degree of difference.

Example: Education Level (Primary, Secondary, Higher), Customer Satisfaction (Satisfied, Neutral, Dissatisfied), Class Rank (1st, 2nd, 3rd).

3. Interval Scale (Equal Differences, No True Zero)

Differences between values are meaningful and equal.

No true zero point (zero does not indicate absence of the variable).

Example: Temperature in Celsius or Fahrenheit (0°C does not mean no temperature), IQ scores, Years in a timeline.

4. Ratio Scale (Absolute Zero, Quantitative Data)

Has all properties of interval scale but includes a true zero, meaning "zero" represents the absence of the variable.

Permits all mathematical operations (addition, subtraction, multiplication, division).

Example: Height, Weight, Age, Income, Speed, Distance.