Discrete samples are best described as?

Discrete samples are best described as data with specific, separate values because discrete data consists of distinct and separate values or categories. For example, the number of students in a classroom (which can only be whole numbers) or the result of rolling a die (which can only yield certain, distinct outcomes) are both examples of discrete data.

This distinction is important because it underscores how discrete data is not able to take on fractional or continuous values. Each value in a discrete dataset represents a specific integer or category, making it easy to count and manage. This characteristic contrasts with continuous data, which can take on any value within a range and includes measurements that can vary infinitely (like height or temperature). Therefore, the key understanding lies in recognizing that discrete samples represent distinct counts or categories rather than measurements along a continuum.