A narrow range indicates that the data points in a dataset are closely clustered around the mean.

When we refer to the range in a dataset, we are discussing the difference between the highest and lowest values. A narrow range signifies that this difference is small, suggesting that the values are not widely dispersed. For instance, consider the test scores of $78$, $80$, $82$, and $79$. The range is calculated as $82 - 78 = 4$. This indicates that the scores are relatively similar to one another.

In practical terms, a narrow range can imply consistency or uniformity within the data. For example, if a class of students scores between $75$ and $85$ on a test, it suggests that the students share similar levels of understanding of the material. This information can be particularly valuable for a teacher who seeks to determine whether the class is generally keeping pace with the lessons.

Conversely, a narrow range might also reflect a lack of diversity in the data. If you were analyzing the heights of a group of individuals and discovered that all heights fell within a very narrow range, this could indicate that the group lacks diversity in terms of height.

Understanding the range is essential for interpreting the spread and variability of the data, which is crucial for making informed decisions based on that data.