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Consider the following time series data. M mull-ll Using the naive method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. (a) mean absolute error (b) mean squared error \"55.: (c) mean absolute percentage error (Round your answer to two decimal places.) MAPE = :1 % (d) What is the forecast for week 7? 1:] For a set of time series data, the following measures of forecast accuracy were found using the naive method as the forecast for the next period. MAE = 4.60 MSE = 24.60 MAPE = 34.42% For the same time series data, the following measures of forecast accuracy were found using the average of all the historical data as the forecast for the next period. MAE = 3.24 MSE = 15.46 MAPE = 26.28% Which method, the naive method or using the average of all the historical data, appears to provide the more accurate forecasts for the historical data? Explain. O Using the naive method appears to provide more accurate forecasts, because MAE, MSE, and MAPE using that method are all higher than MAE, MSE, and MAPE using the average of all the historical data. O Using the naive method appears to provide more accurate forecasts, because MAE, MSE, and MAPE using that method are all lower than MAE, MSE, and MAPE using the average of all the historical data. O Using the average of all the historical data appears to provide more accurate forecasts, because MAE, MSE, and MAPE using that method are all higher than MAE, MSE, and MAPE using the naive method. Using the average of all the historical data appears to provide more accurate forecasts, because MAE, MSE, and MAPE using that method are all lower than MAE, MSE, and MAPE using the naive method.Consider the following time series data. Week Value (a) Construct a time series plot. 20 T Time Series Value Time Series Value Time Series Value Time Series Value 3 5 6 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 seasonal pattern. O The data cyclical pattern. O The data appear to follow a horizontal pattern. (b) Develop the three-week moving average forec Week Time Series Forecast 11 15 13 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (c) Use a = 0.2 to compute the exponential smoothing forecasts for the time series. Week Time Series Value Forecast 17 12 14 11 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (Round your answer to two decimal 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 MSE? Explain. O The exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach. O The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach. O The exp three-week moving average approach. O The three-week moving average p a larger MSE than the smoothing approach. (e) Use a smoothing constant of a = 0.4 to compute the e Week Time Series "Value Forecast 12 14 11 15 13 constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. r MSE than the exponential smoothing using a = 0.2. r MSE than the exponential smoothing using a = 0.2 MSE than moothing using a = 0.4. r MSE than the exponential smoothing using a = 0.4
