---
title: "Attribute types: nominal, ordinal, interval, ratio"
subject: "Data Mining"
chapter: 2
key: "semester_7/data_mining:data-attribute-types"
source: https://www.bctengineer.com/q/semester_7/data_mining/data-attribute-types
site: BCT Engineering
---

# Attribute types: nominal, ordinal, interval, ratio

Data Mining · Chapter 2: Data Pre-processing

- Asked in: year not given
- Video: [Attributes (Nominal, Ordinal, Binary, Numeric) [Data Mining](HINDI)](https://www.youtube.com/watch?v=ss3mDm3mjsc) — 5 Minutes Engineering
- Answer checked by Claude Opus 5.5 (high effort) on 2026-10-14
- Page: https://www.bctengineer.com/q/semester_7/data_mining/data-attribute-types
- Whole chapter: https://www.bctengineer.com/md/semester_7/data_mining/chapter-2

## Question

What do you mean by attribute? Explain Nominal, Ordinal, Interval and Ratio attribute types.

## Short answer

An attribute is a property of a data object (e.g., age, color). Four types: Nominal (labels only, equality), Ordinal (ordered labels, ranking), Interval (ordered, meaningful differences, no true zero), Ratio (true zero, meaningful ratios). Nominal/ordinal are categorical; interval/ratio are numeric. Each type permits operations of weaker types.

## Answer

An **attribute** (also called variable, feature or field) is a property or characteristic of a data object, for example the *age*, *colour* or *marks* of a student. The set of attribute values describes one object (record).

The four classical types, from weakest to strongest, differ in which operations are meaningful.

| Type | Meaning | Operations | Examples |
| --- | --- | --- | --- |
| **Nominal** | Names/labels only; no order | =, ≠ (mode) | eye colour, gender, zip code, ID number |
| **Ordinal** | Labels with a meaningful order; gaps not meaningful | =, ≠, <, > (median) | grade (A, B, C), rank, small/medium/large |
| **Interval** | Ordered, differences meaningful, no true zero | +, − (mean, std. dev.) | temperature in °C or °F, calendar dates |
| **Ratio** | Interval plus a true zero, so ratios meaningful | +, −, ×, ÷ | height, weight, age, salary, length, counts |

#### Points to remember
- **Nominal and ordinal** are *categorical (qualitative)*; **interval and ratio** are *numeric (quantitative)*.
- 40 °C is not "twice as hot" as 20 °C because 0 °C is arbitrary (interval); 40 kg is twice 20 kg because 0 kg means no weight (ratio).
- Each type allows all the operations of the types above it in the table, so a ratio attribute can be treated as interval, ordinal or nominal, but not the reverse.
- The type decides which statistics and which mining algorithms can be applied.

## Check yourself

The answer's key points as multiple-choice questions, with the correct option and why.

1. What is an attribute?
   A. A whole database
   B. A type of query
   C. A property or characteristic of a data object, e.g. age or colour of a student
   D. An algorithm
   Answer: C. Attributes (also variables, features, fields) describe objects. (Key point: Attribute)

2. Which attribute is ordinal?
   A. Eye colour
   B. Zip code
   C. Weight in kg
   D. Grade (A, B, C)
   Answer: D. Ordinal has a meaningful order, but gaps are not meaningful. (Key point: Ordinal type)

3. Why is 40 C not twice as hot as 20 C?
   A. 0 C is arbitrary (no true zero), so temperature is interval
   B. Temperature is nominal
   C. Temperature is ordinal
   D. Celsius is discrete
   Answer: A. Ratios are meaningful only with a true zero, as in ratio attributes like weight. (Key point: Interval vs ratio)

4. Which types are numeric (quantitative)?
   A. Nominal and ordinal
   B. Interval and ratio
   C. Nominal and ratio
   D. Ordinal and interval
   Answer: B. Nominal and ordinal are categorical; interval and ratio are numeric. (Key point: Categorical vs numeric)

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