What statistical measure provides an indication of how closely the data points cluster around the mean?

The standard deviation is the statistical measure that provides insight into how closely data points are clustered around the mean. It quantifies the amount of variation or dispersion present in a dataset. A low standard deviation indicates that data points tend to be close to the mean, while a high standard deviation suggests that the data points are spread out over a wider range of values. This measure is crucial for understanding the distribution of data, helping analysts assess the consistency or reliability of the data collected.

While other options like variance are also related to data spread, the standard deviation offers a more intuitive understanding because it is expressed in the same units as the original data, making it easier to interpret in context. The median, being a measure of central tendency, does not provide information about the spread of the data points. The range, while indicating the difference between the maximum and minimum values, does not give a comprehensive view of how data points cluster around the mean. Therefore, standard deviation is the most appropriate measure for this context.