What term describes the measure of the average deviation from the mean in a dataset?

The correct answer is the standard deviation. This term represents a widely used statistical measure that quantifies the amount of variation or dispersion in a set of values. Specifically, it tells you how much individual data points typically deviate from the mean of the dataset.

To understand why standard deviation is the right choice, it helps to know that it is calculated by taking the square root of the variance. Variance itself measures the average of the squared differences from the mean, but it is often expressed in squared units, making it less intuitive to interpret than the standard deviation, which is in the same units as the data.

Standard error, on the other hand, refers to the standard deviation of a sample mean estimate, which gauges the variability between sample means rather than individual data points. Average absolute deviation measures the average of absolute deviations from the mean, but is less commonly used than standard deviation in statistical analysis.

Thus, the standard deviation is the most direct measure of average deviation from the mean since it provides insight into the typical distance of data points from the mean in a dataset, making it a fundamental concept in statistics.