Please help me out and answer just as it is shown here:
1)
Consider the following time series data. Week 5 6 Value 25 22 12 20 24 16 (a) Construct a time series plot. 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 cyclical pattern. O The data appear to follow a seasonal pattern. (b) Develop a three-week moving average for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 25 2 13 3 22 12 5 20 24 16 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 8? (Round your answer to two decimal places.) (c) Use a = 0.2 to compute the exponential smoothing values for the time series. (Round your answers to three decimal places.) Week Time Series Value Forecast 25 2 13 3 22 12 5 20 74 16 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 8? (Round your answer to two decimal places.) (d) Compare the three-week moving average forecast with the exponential smoothing forecast using a = 0.2. Which appears to provide the better forecast based on MSE? The exponential smoothing using a = 0.2 provides a better forecast since it has a smaller MSE than the three-week moving average. O The three-week moving average provides a better forecast since it has a larger MSE than the exponential smoothing using a = 0.2. The exponential smoothing using a = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average. O The three-week moving average provides a better forecast since it has a smaller MSE than the exponential smoothing using a = 0.2. (e) Use trial and error to find a value of the exponential smoothing coefficient a that results in a smaller MSE than what you calculated for a = 0.2.Suppose the values of Alabama building contracts (in $ millions) for a 12-month period follow. 240 360 240 250 280 310 210 320 240 310 240 240 (a) Construct a time series plot. 400 400 T 400 T 400 T 350 350 350 350 300 300 300 250 250- 250 ue (in $ millions) 2 200- 200 200 "200 150 150- 150- 150 100- 100 100- 100 50 + 50 50 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1 2 3 4 5 6 7 8 9 10 11 12 13 0 1 2 3 4 5 6 7 8 9 10 11 12 13 Month Month Month Month What type of pattern exists in the data? O The data appear to follow a seasonal pattern. The data appear to follow a cyclical pattern. The data appear to follow a horizontal pattern. O The data appear to follow a trend pattern. (b) Compare the three-month moving average forecast with the exponential smoothing forecast using a = 0.2. (Round your answers to two decimal places.) Time Series 3-Month Moving 4 = 0.2 Month Average Forecast Forecast (in $ millions) (in $ millions) (in $ millions) 240 360 240 250 280 5 310 210 8 320 9 240 10 310 11 240 240 Which provides more accurate forecasts based on MSE? O Exponential smoothing is more accurate, since its MSE calculated over all of the forecasted months is smaller than the MSE using the three-month moving average. Exponential smoothing is more accurate, since its MSE calculated over all of the forecasted months is larger than the MSE using the three-month moving average. The three-month moving average is more accurate, since its MSE is larger than the MSE for exponential smoothing calculated over all of the forecasted months. O The three-month moving average is more accurate, since its MSE is smaller than the MSE for exponential smoothing calculated over all of the forecasted months. (c) Using the more accurate approach from part (b), what is the forecast (in millions of dollars) for the next month? (Round your answer to the nearest million dollars.) millionFor 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 = 5.40 MSE - 31.00 MAPE - 40.79% 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 = 3.40 MSE = 14.70 MAPE = 27.48% 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 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. 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 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
