Which of the following best describes discrete data grouping?

Discrete data consists of distinct and separate values, which means that each unique value can be identified individually without any intermediate values in between. When grouping discrete data, it is common to place each unique value into its own class or category. This approach ensures that each distinct number is represented without merging it with others, allowing for clear analysis and interpretation of the frequency of those specific values.

In contrast, other grouping methods mentioned in the options do not align with the characteristics of discrete data. For example, values divided into bins typically apply to continuous data, where ranges or intervals are used because the data can take on an infinite number of values within a range. Approximating values is also more relevant to continuous data, where precise values may not be available. Continuous values can represent a range of numbers, unlike discrete values that are countable and specific. Therefore, option A best captures the essence of discrete data grouping by emphasizing the classification of each distinct value.