B. Explanation: Discrete data refers to data that can only take on specific, countable values, usually whole numbers, meaning you can't have values in between (like fractions or decimals). This aligns with the concept of counting the frequency of each value, where you can only count whole occurrences of a specific value.
Breakdown of the other options:
A. Non-numeric data used to describe attributes of a population sample: This describes qualitative data, not discrete data.
C. Numeric values that can be measured on a continuous scale: This describes continuous data, where values can fall anywhere within a range, not discrete data.
D. Non-numeric data used to describe attributes of a population sample ranked in a specific order: This describes ordinal data, a type of qualitative data with a ranking system, not discrete data.
Example of discrete data: The number of cars in a parking lot (you can only have a whole number of cars, not a fraction of a car).
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