Amy, Bob, Edna and Frank work for a company that contracts all their business at the beginning of each fiscal year so the demand time series will be stationary within each year. Although their company has seen growth from year to year, problems with their forecasts have been increasing every year over the past four years beginning with Yearl in the table below. Glenda, head of the forecasting committee, has called a meeting to discuss the quarterly forecasts for next year. Before the meeting, Glenda collected and distributed the following data of past sales and requested each member of the committee to analyze the time series and bring suggestions for the next year's quarterly forecasts to the meeting. Quarter4 Quarter1 Quarter2 Quarter3 Yearl 1280 960 560 400 Year2 2720 2040 1190 850 Year3 4160 3120 1820 1300 Year4 5600 4200 2450 1750 Glenda calls the meeting to order and asks each committee member for their suggestions. Amy reported using a random component to keep it simple and not to change the procedure of using a three-point moving average from previous years. Glenda reminds Amy that using a moving average that assumes only a random component results in only one forecast value which would be for the first quarter of year 5. Amy agrees but recalls that the forecast for quarter 1 of year 5 would be the forecasts for every quarter into the future until they observe more data throughout the year. Glenda then asks Amy for her forecasts for quarters 1,2,3,4, for year 5 based on a random component. Bob argues that seasonal and random components should be considered since seasonality in the sales data is likely. Glenda asks Bob for his forecasts for quarters 1,2,3,4, for year 5 based on seasonal and random components. Edna suggests random and linear trend components after noticing an increase from year to year in the table of data. Glenda asks Edna for her forecasts for quarters 1,2,3,4, for year 5 based on random and linear trend components. Frank proposes random, seasonal and linear trend components after looking at a plot of the data. Glenda asks Frank for his forecasts for quarters 1,2,3,4, for year 5 based on random, seasonal, and linear trend components. From the table, select the correct set of forecasts based on each person's assumptions and approach. Quarter 1 Quarter 2 Quarter 3 Quarter 4 A. Forecasts 7040 5280 3080 2200 B. Forecasts 4160 3120 1820 1300 C. Forecasts 7040 5280 3080 2200 D. Forecasts 2800 2800 2800 2800 E. Forecasts 3542 3705 3869 4033 F. Forecasts 11264 6336 2156 1100 G. Forecasts 3440 2580 1505 1075 H. Forecasts 4625 4850 5075 5300 I. None of the Above ... Question 3. Amy reported forecast set: A B C D E F G H I Question 4. Bob reported forecast set: A B C D E F G H I Question 5. Edna reported forecast set: A B C D E F G H I Question 6. Frank reported forecast set: A B C D E F G H