Discrete data consist of separate, countable outcomes, 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, mass, or time. The distinction depends on what the variable represents, not whether recorded values are whole numbers or decimals; rounded measurements remain continuous. Formal set-theoretic and advanced statistical treatments are not included.
Detailed Explanation: Distinguish discrete and continuous data
Data can be classified by asking what the variable represents:
Discrete data are counts. They have separate, countable values, such as (0,1,2,3,…).
Continuous data come from measuring. They can take any value within a range, even if the recorded value is rounded.
Worked example
A teacher records the following information about students:
The number of pets each student owns
Each student’s height, recorded to the nearest centimetre
Classify each variable as discrete or continuous.
Step 1: Identify what is being recorded
“Number of pets” is a count.
“Height” is a measurement.
Step 2: Decide whether values are countable or measurable
The number of pets can be (0,1,2,3,…). You cannot have (2.5) pets in this count, so it is discrete data.
Height could be (160.2 cm), (160.25 cm), or another value between two measurements. Even though it is recorded to the nearest centimetre, it is still continuous data.
Answer
Number of pets: discrete
Height: continuous
Remember: whole-number recordings do not automatically mean the data are discrete. Ask whether the variable is being counted or measured.
Learn by doing: Distinguish discrete and continuous data
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Practice:
Probability Discrete vs Continuous - Random Variable to Model Type