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Distinguish discrete and continuous data

Discrete data consist of separate, countable values, such as the number of siblings or books, whereas continuous data arise from measurement and can take any value within an interval, such as height, time, or temperature. The distinction depends on how the quantity is generated, not merely on whether recorded values contain decimals: measurements may be rounded, and counts are not made continuous by notation; this understanding supports choosing appropriate statistical representations and interpreting data distributions.

Detailed Explanation: Distinguish discrete and continuous data

Discrete data are values you count. They are separate values, usually whole numbers, such as (0,1,2,3)(0,1,2,3).

Continuous data are values you measure. They can take any value within a range, including decimals, such as (150.4 cm)(150.4\text{ cm}) or (12.73 s)(12.73\text{ s}).

A useful question is:

Is this quantity counted, or is it measured?

Worked example

A teacher records two pieces of information about each student:

  1. The number of pets the student owns
  2. The student’s height

Step 1: Examine the number of pets

Pets are counted. A student might have (0,1,2,)(0,1,2,) or 33 pets, but not (2.5)(2.5) pets.

Therefore, the number of pets is discrete data.

Step 2: Examine the student’s height

Height is measured. A student’s height could be (150 cm)(150\text{ cm}), (150.5 cm)(150.5\text{ cm}), or (150.53 cm)(150.53\text{ cm}).

Therefore, height is continuous data.

Even if the teacher records height only to the nearest centimetre, such as (151 cm)(151\text{ cm}), height is still continuous because it was produced by measurement.

Remember

  • Counted values \rightarrow discrete
  • Measured values \rightarrow continuous
  • Rounding a measurement does not make it discrete.

Learn by doing: Distinguish discrete and continuous data

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Probability Discrete vs Continuous - Random Variable to Discrete or Continuous


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