Month	1	2	3	4	5	6	7
Value	23	12	19	11	18	22	14

\fUse a smoothing constant of :2- = 0.4 to compute the exponential smoothing forecasts. {Round vour answers to two decimal places.) Month Tim'falsueeries 1 23 2 12 3 19 4 11 5 18 6 22 T" 14 Does a srroothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE'? Explain. 111E exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using :2' = 0.4. 111e exponential smoothing using a = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using (I = 0.2. C'- The exponential smoothing using c: = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using :2- = 0.4. 111E exponential smoothing using a = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using :2' = 0.2. What type of pattern exists in the data? O The data appear to follow a horizontal pattern. O The data appear to follow a trend pattern. O The data appear to follow a seasonal pattern. O The data appear to follow a cyclical pattern. (b) Develop the three-month moving average forecasts for this time series. Month Time Series Value Forecast 23 2 12 3 19 4 11 5 18 5 22 7 14 Compute MSE. MSE = What is the forecast for month 8