1. MAD is preferred over MSE because the latter has some undesirable qualities in comparison to MAD. In this forecasting method MAD is a better option over MSE as it puts a very high weight on large deviations, so the MSE-optimal forecast will have fewer large errors but may have much more small errors than a MAD-optimal forecast. So, it could be estimated that MAD performed best and MES the worst.
2. MAD is a measure for forecasting error and in this case the absolute value of the forecast error had been taken for the entire forecasting period which is week 11 and 12. Taking an absolute value of a number disregards whether the number is negative or positive and, in this case, avoids the positives and negatives canceling each other out. When we analyze the bias value we can see among moving average period of 3 ,4 and 5 there is a difference. Moving average 3 show case 36.03while moving average 4 has an MAD of 23.62 and moving average of 5 has 60.89. We can see in all cases there is a large difference in the MAD value and hence forecasting error is large.
3. The smoothing method is better than regression because the former when properly applied give clearer result and trend analysis. The regression method is the older version of smoothening method .The smoothening method is recommended as it is gives estimation about the important data of the statistical analysis.

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