Why is it generally recommended that the number of classes in a frequency distribution be between $5$ and $20$?

• A. Because using fewer than $5$ classes guarantees that all data values are unique.
• B. Because the number of classes must always equal the number of data points.
• C. Because too few classes may oversimplify the data, while too many classes may make patterns difficult to detect.
• D. Because having more than $20$ classes always results in a perfectly uniform distribution.

Answer: (C)

Verified step by step guidance

1. Understand that a frequency distribution groups data into classes or intervals to summarize and visualize the data effectively.
2. Recognize that having fewer than 5 classes can oversimplify the data, causing important details and patterns to be lost because many data points get lumped together.
3. Know that having more than 20 classes can make the distribution too detailed, causing the data to appear cluttered and making it harder to identify overall trends or patterns.
4. Realize that the recommended range of 5 to 20 classes strikes a balance between simplicity and detail, allowing meaningful patterns to emerge without overwhelming the reader.
5. Therefore, the choice of the number of classes is about optimizing clarity and interpretability of the data, not about matching the number of data points or guaranteeing uniqueness.