In this course, you were introduced to two methods of measuring the accuracy of forecasts/predictions, namely the Mean Absolute Error (MAE), Mean Square Error (MSE) and Root Mean Square Error (RMSE). The formulas for the three measure are provided below: MAE = Zizilyi - Dil n MSE = in RMSE = Etz(Vi - Di)2 in For each measure, a smaller value indicates better forecast/prediction. Consider the forecasts generated using the following two methods: Method 1 and Method 2 which are presented in Table 1. Year AC Screenshot(Alt + A) redicted Sales: Predicted Sales: (vi) | Method 1 ( P;) Method 2 ( Di) 2015 5 7 6 2016 8 8 10 2017 4 5 7 2018 10 8 5 2019 6 3 4 (a) Compute MAE for each method and determine which method is a better sales predictor (b) Compute MSE for each method and determine which method is a better sales predictor (c) Are your results for parts (a) and (b) conflicting with respect to which method is a better predictor? (d) Calculate the Root Mean Square Error (RMSE) for each method. Note that RMSE is just the square root of MSE. (e) Would you expect RMSE and MSE to give the same conclusions with respect to which method is a better predictor