Classification of Data – Types & Rules 🗂️📊

Raw data looks like this:
22, 28, 31, 29, 25, 27, 40, 18, 33…

Not very meaningful!

Classification turns this into valuable information by arranging it into groups and categories.

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What Is Classification?

Definition:

Classification is the process of arranging data into groups or classes based on similarities and differences.

Why classify?

✔ Simplifies large data
✔ Helps comparison
✔ Aids tabulation
✔ Supports analysis (mean, SD, correlation)

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Types of Classification 🧩

Classification can be done in several ways:

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1. Chronological Classification (By Time)

Data arranged according to time periods.

Example:

Year	Sales (₹ lakh)
2020	120
2021	150
2022	180

Used in:

• Time series
• Forecasting

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2. Geographical / Spatial Classification (By Location)

Data arranged by place.

Examples:

• State-wise literacy
• Country-wise GDP
• City-wise pollution levels

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3. Qualitative Classification (By Attributes)

Classification based on non-measurable attributes.

Examples:

• Gender → Male/Female
• Marital Status → Married/Unmarried
• Employment → Employed/Unemployed

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4. Quantitative Classification (By Numbers)

Based on numerical characteristics.

Examples:

• Age
• Income
• Weight

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5. Discrete vs Continuous Classification

Discrete

Values are whole numbers.
Examples:

• Number of children
• Number of cars

Continuous

Values can take fractions.
Examples:

• Height
• Weight
• Income

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6. Frequency Classification

Data grouped into class intervals.

Example:

Age Group	Frequency
10–20	4
20–30	7
30–40	3

This is used in histograms, mean, SD, etc.

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Rules of Classification ✔️

1. Exhaustiveness

Every item of data must fall into some class.

2. Mutually Exclusive

No item should fall into two classes.

3. Homogeneity

Each class should represent one characteristic only.

4. Clarity & Simplicity

Classes must be easy to understand.

5. Stability

Classification should not change midway.

6. Appropriate Number of Classes

Not too many, not too few.

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ASCII Diagram — Rules of Classification

Exhaustive
↓
Exclusive
↓
Homogeneous
↓
Clear
↓
Stable
↓
Logical

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Summary ✨

• Classification arranges raw data into meaningful groups.
• Includes qualitative, quantitative, chronological, geographical, and frequency classifications.
• Follow rules: exhaustive, exclusive, homogeneous, clear, stable.

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Quiz Time! 🎯