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? Mean deviation and standard deviation are two of the most commonly used measures of variability in statistics. They are both measures of how much a set of values differ from the average. However, there are some key differences between the two. Mean deviation is the average of the absolute values of the differences between each data point and the mean. It is the simplest measure of variability and is calculated by taking the sum of the absolute values of the differences and dividing by the number of data points. This measure is useful for quickly identifying outliers in a data set. Standard deviation is a more complex measure of variability and is calculated by taking the square root of the average of the squared differences between each data point and the mean. It is a measure of how much the data points differ from the mean. This measure is useful for determining the spread of the data and for making predictions about future data. In summary, mean deviation is a simpler measure of variability that is useful for quickly identifying outliers in a data set. Standard deviation is a more complex measure of variability that is useful for determining the spread of the data and for making predictions about future data.