Which statistical measure indicates the average amount of deviation of values from the mean?

The standard deviation is the statistical measure that provides insight into the average amount of deviation of individual values from the mean of a dataset. It quantifies how much the values in a dataset typically vary or spread out. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation suggests that the values are more spread out from the mean.

In this context, the standard deviation is especially useful for understanding the distribution of data points around the mean in a clear and concise manner. It is calculated as the square root of the variance, which means it offers a direct representation of the dispersion in the same units as the data.

Other measures listed, such as the median, range, and variance, serve different purposes. The median provides the middle value of a dataset when arranged in order, thus giving insights into the central tendency without being affected by extreme values. The range indicates the difference between the maximum and minimum values, offering a simple measure of variability but does not reflect the dispersion of all values. Variance, which is related to standard deviation, measures the average squared deviation from the mean, which is not directly interpretable in the same units as the data and is less intuitive for understanding average deviation. Consequently, standard deviation