Scales of Measurement
Muhammad Abdullah Abrar
DevOps Engineer | AWS | Kubernetes | Docker | Linux | Python
These notes are inspired by today's data analytics lecture from Dr. Muhammad Aammar Tufail
If you want more information go ahead and check my blog about Scales of Measurement.
When we collect data, we need to understand what kind of data we have. This helps in choosing the appropriate method of analysis. There are four basic concepts: name, structure, interval, and shape.
1. Nominal measurements
Definition: A nominal scale is used for labeling variables that have no quantitative value. It’s like grouping data.
Examples:
Gender: male, female
Blood types: A, B, AB, O
2. Gradual scale
Definition: An ordinal scale is used to sort or order variables, but the difference between ranks is not equal.
Examples:
Education level: Primary, Secondary, Elementary
Customer satisfaction: poor, fair, good, excellent
3. Interval scale
Definition: An interval measure measures a variable in which the difference between two values is meaningful. However, it doesn’t really have a zero point.
Examples:
Temperature: 10°C, 20°C, 30°C
Dates: 2000, 2010,
4. Communication Scale
Definition: A ratio criterion is like an interval criterion but it actually has a zero point. This means that we can make statements about how often one value overlaps with another value.
Examples:
Weight: 50 kg, 100 kg, 150 kg
Height: 150 cm, 160 cm, 170 cm