My Notes 3. Consider the following time series data. Week 1 2 3 5 6 Value 19 12 11 17 14 (a) Construct a time series plot. 20 T 20 20 18- Time Series Value 16- Time Series Value Time Series Value 16 14 Time Series Value 5 6 2 3 5 6 2 3 5 6 3 5 6 7 0 2 3 Week Week Week Week What type of pattern exists in the data? O The data appear to follow a trend pattern. O The data appear to follow a cyclical pattern. The data appear to follow a horizontal pattern. The data appear to follow a seasonal pattern. (b) Develop the three-week moving average forecasts for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 1 19 2 12 3 15 4 11 5 17 6 14 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7?(c) Use or = 0.2 to compute the exponential smoothing forecasts for the time series. Week lslzie' Forecast 1. 19 2 12 3 15 4 11 5 17 s 14 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? {Round your answer to two decimai places.) (d) Compare the three-week moving average approach with the exponential smoothing approach using a = 0.2. which appears to provide more accurate forecasts based on MSE7 Bcplain. O The exponential smoothing using at = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach. 0 The threeeweek moving average provides a better forecast since it has a smaller MSE than the smoothing approach. 0 The threeeweek moving average provides a better forecast since it has a larger MSE than the smoothing approach. 0 The exponential smoothing using at = 0.2 provides a better forecast since it has a smaller MSE than the three-week moving average approach. (e) Use a smoothing constant of 11 : 0.4 to compute the exponential smoothing forecasts. week 11%? Foreast 1 19 2 12 3 15 4 11 5 17 5 14 Does a smoothing oonstant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Expiain. O The exponential smoothing using or = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.2. O The exponential smoothing using at = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using at = 0.4. O The exponential smoothing using at = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using at = 0.2. O The exponential smoothing using or = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.4