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The mean absolute deviation (MAD) measures the average distance between each data point and the mean of the data set. To calculate the MAD, we first need to find the mean of the dataset:
(125 + 198 + 209 + 213 + 101 + 178) / 6 = 1024 / 6 = 170.67
Next, we calculate the absolute deviation for each data point by subtracting the mean from each data point and taking the absolute value:
|125 - 170.67| = 45.67
|198 - 170.67| = 27.33
|209 - 170.67| = 38.33
|213 - 170.67| = 42.33
|101 - 170.67| = 69.67
|178 - 170.67| = 7.33
Then, we find the average of these absolute deviations:
(45.67 + 27.33 + 38.33 + 42.33 + 69.67 + 7.33) / 6 = 230.67 / 6 = 38.4
Therefore, the mean absolute deviation of the dataset is 38.4 rounded to the nearest tenth.