The absolute deviation of a data value from the mean is the distance that the data value is away from the mean of the data set. Because it is a distance, absolute deviation cannot be negative.
To find the absolute deviation of a data value from the mean, take the absolute value of the deviation of the data value from the mean.
The mean absolute deviation is a measure of variability that describes how much the data values are spread out from the mean of a data set. The mean absolute deviation is the average distance that the data values are spread around the mean.
To find the mean absolute deviation, find the sum of the absolute deviations. Then divide by the number of data values.
Sum of the absolute deviations:
table with 9 rows and 2 columns , row1 column 1 , 3 , row2 column 1 , 2 , row3 column 1 , 2 , row4 column 1 , 1 , row5 column 1 , 0 , column 2 meanabsolutedeviationequals . fraction sumoftheabsolutedeviations , over totalnumberofdatavalues end fraction , row6 column 1 , 1 , column 2 equals , 16 over 9 , row7 column 1 , 1 , column 2 almost equal to 1.8 , row8 column 1 , 3 , row9 column 1 , fraction plus 3 , over 16 end fraction , end table
The greater the mean absolute deviation, the higher the variability in the data set.