A B C D E F G H K L M N O Forecasting with Trend using Exponential Smoothing Step 1. Complete table below filling in yellow cells with appropriate formulas. 3 B 0.3 0.2 Month Period | Sales Level Trend Forecast Error Error squared Avg through April 0 780 100 May 1 880 June 2 910 July 3 990 August 1080 September 1116 October 6 1220 November 1299 December 1402 January 1540 February 10 1620 March 11 1705 April 12 1813 NOTE: Use your forecast to estimate Sales for May (month=13). Using this estimate, you May 13 can then forecast an additional month into the future, June (14). Know that your accuracy June 14 decreases as you extend further into the future. 23 Forecast equation yethit = let hb. Mean Squared Error Step 2. After calculating with the given alpha and beta, find the minimum MSE by optimizing alpha and beta using Excel's Solver tool. Submit Level equation 4 = aye + ( 1 - a ) (4 1 + 6, 1 ) (MSE) your work with only this answer. 25 26 Trend equation by = B"( 4 - 4 1) + (1 -B") be-1, 27 28 NOTE: MSE is a simple average of the Error-squared above.Trend and Seasonal Effects Step 1. Complete tables to right and below filling in yellow cells with appropriate formulas. Trend Season Forecast Squared Error Average Initial Values when M = 4 (Quarterly) v, Average of Season Orange cells the initial values that must also be computed. Trend Adjusted Exponential Smoothing model. In addition to a trend, the model also adds a smoothed adjustment for seasonality. This template is a quarterly model, where the number of seasons is set to 4. There are three smoothing constants associated with this model. Alpha is the smoothing constant for the basic level, delta smoothes the trend, and gamma smoothes the seasonal index. Again, the weighting or smoothing factors, alpha, delta and gamma can never exceed 1 and higher values put more weight on more recent time periods. resulting MINIMUM MSE solution. Step 2. After calculating with the given alpha, beta and gamma, find the minimum MSE by optimizing alpha, beta, and gamma using Excel's Solver tool. Submit your work with only the Yo i S5 = Vae) ~% = overoge(as Yo = Useformulaforseasonalvalue: Sg =7 (Yolle) + (1-7) Ses L= a (YS + (1-a) (Liy 4+ Teq) T =B (Ll ) + (1-B) Ty S, =y (Y/L) + (1-7) Sy Frak = (L vK*T)* Sppan Note 1: Y is actual demand, not "year". Note 2: k is # of periods in the past (typically =1)