L1.3: Introduction and Types of Data - Classification of Data

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Learning outcomes

• classify data as categorical or numerical
• identify nominal and ordinal data
• identify discrete and continuous numerical data
• avoid common classification mistakes

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Main data classes

• Categorical data: labels or groups
• Numerical data: numbers that represent quantity or measurement

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Categorical data

• Used to place cases into groups or classes.
• Arithmetic operations are not meaningful on the labels themselves.

• blood group
• department
• gender
• type of vehicle

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Nominal data

• Categories with no natural order.

• blood group
• branch
• city name

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Ordinal data

• Categories with a meaningful order or ranking.
• But the gaps between categories are not necessarily equal.

• poor, average, good
• rank in class
• satisfaction level: low, medium, high

• Ordered categories are still categorical, not numerical.

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Numerical data

• Represents numerical magnitude.
• Arithmetic operations are meaningful.

• age
• height
• income
• number of books

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Discrete data

• Countable values, usually whole numbers.

• number of siblings
• number of calls received
• number of students present

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Continuous data

• Measured values that can take many possible values within an interval.

• height
• time
• weight
• temperature

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Code numbers and hidden traps

• Sometimes categories are coded as numbers:
  • 1 = male, 2 = female
  • 1 = rural, 2 = urban

• The numbers act as labels, not quantities.

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Mixed examples

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Exam hints and traps

• If the value counts items, it is often discrete.
• If the value measures on a scale, it is often continuous.
• Ordered labels remain categorical.
• Not every number should be added or averaged.

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Quick practice

1. favourite subject
2. number of absences
3. monthly income
4. t-shirt size (S, M, L, XL)
5. rating: poor / fair / good / excellent

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Answer key

1. categorical nominal
2. numerical discrete
3. numerical continuous
4. categorical ordinal
5. categorical ordinal