If the actual value of a time series at time t and the forecast value for time t is denoted by At and Ft respectively, then the formula for the mean absolute deviation over a range of forecasted values is .
A) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|A_{t}-F_{t}\right|}{n} $

B) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left(A_{t}-F_{t} \mid\right)^{2}}{n} $

C) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n} \sqrt{\left|A_{t}-F\right|}}{n} $

D) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|\frac{A_{t}-F_{t}}{2}\right|}{n} $

Question

If the actual value of a time series at time t and the forecast value for time t is denoted by At and Ft respectively, then the formula for the mean absolute deviation over a range of forecasted values is . 
A) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|A_{t}-F_{t}\right|}{n} $

B) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left(A_{t}-F_{t} \mid\right)^{2}}{n} $

C) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n} \sqrt{\left|A_{t}-F\right|}}{n} $

D) $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|\frac{A_{t}-F_{t}}{2}\right|}{n} $

Quizplus · Accepted Answer

The formula for mean absolute deviation (MAD) is the average of absolute forecast errors over a given range. Absolute forecast error is the absolute difference between the forecast value and the actual value at a given time. Therefore, formula A $ \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|A_{t}-F_{t}\right|}{n} $ is the correct formula for calculating MAD.

If the Actual Value of a Time Series at Time MAD=∑t=1n∣At−Ft∣n \mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|A_{t}-F_{t}\right|}{n} MAD=n∑t=1n​∣At​−Ft​∣​

If the Actual Value of a Time Series at Time $\mathrm{MAD}=\frac{\sum_{t=1}^{n}\left|A_{t}-F_{t}\right|}{n}$