01 9 10 11 12 13 14 15 A product has a consistent year round demand. You are responsible for the forecast and have been tasked with experimenting with some time series analysis. Using this previous monthly demand, calculate the following forecasts for each period possible. A) 4 Period Simple moving average B) Two Period Weighted moving average using weights of.7.3, C) three-period weighted moving average with weights of .5,3,2 and D) Exponential Smoothing forecast using an Alpha of .40 and a Week 1 forecast of 800 units. Round all forecasts to whole numbers. WMA SMA 4 Period WMA .5,3, 2 EXP Sm.40 800 57,.3 15 17 18 19 20 21 22 23 24 25 26 27 28 29 Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Demand 725 680 720 800 902 876 825 950 956 1021 995 1050 Q2 For each of the forecasts and demand below, calculate the Mean Absolute Deviation, Mean Squared Error and Mean Absolute Percent Error. Use the ABS formula for Absolute Value. NOTE: Use formulas for each calculation. MAD Error (e) 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 Absolute Error MSE e^2 MAPE Abs e/A Week 1 2 3 4 5 6 ANSWER Demand 360 390 410 385 420 405 Forecast 425 400 450 350 380 400 44 45 46 47 48 49 50 51 Q3 The Actual demand for snowboards from a large GTA Sporting Goods chain is shown below for 2020. Calculate the Seasonal Index for last year for each of the four seasons. Use the seasonal Index to calculate the demand for each of the seasons for this coming year (Table #2) based on a new ANNUAL demand of 3200 snowboards. Use two decimal places for your seasonal factor. Round your final forecasts to whole numers. Last Year 2020 Sold Average Seasonal Factor 900 678 450 720 Fall Season 52 53 Winter 54 Spring 55 Summer 56 57 58 Table 2 59 Season 60 Winter 61 Spring 62 Summer 63 Fall Averare Seasonal Factor Forecast Sheet2