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The primary purpose of the mean absolute deviation (MAD) in forecasting is to: estimate the trend line. eliminate forecast errors. measure forecast accuracy. seasonally adjust the forecast. remove random variations.

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The primary purpose of the mean absolute deviation is to measure the accuracy of the forecast.

The average distance between every information value and the median is characterized as the mean absolute deviation (MAD) of a set of data. A measurement of variability in a given dataset is the mean absolute deviation. We can estimate what "spread out" the variables in a data gathering are by checking at the mean absolute deviation. Determine the average of the data set firstly, then utilize that number to determine the median absolute deviation of the data. Divide the entire amount of information elements by the amount of the specific data values. And using the formula |data value - mean|, determine the exact number of each data value's variance from the mean.

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