(a) What is the forecast for the total sales of the two products for the first quarter of 2019?

(b) What is the forecast for Quick Sheets for the first quarter of 2019 in '000 dollars?

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Mr. Bill Doors is trying to determine the forecasts for the first quarter of 2019 for his best-selling accounting software products, QuickSheets and QuickTax. he fırst uses seasonalized time series analysis to forecast the total sales of the two products (in '000 dollars). Then, separately, he uses exponential smoothing (with a = 0.80) on historical data to determine what fraction of total sales represented each product to predict the fraction for the future. Multiplying the forecast for total sales with that for the fraction of total sales represented by a specific product gives him the forecast for each product. The historical data for total sales is shown in Table 1 below. Table 1 Quarter 2016 2017 2018 1 1008 1162 1172 968 1046 1086 818 904 908 4 1288 1332 1370 A linear regression analysis suggests that the following line best fit the corresponding deseasonalized data series: D: = 1004 + 13 *t, where, t the time period (for the given data, the time periods go from 1 through 12 for the twelve quarters), and Dt = deseasonalized total sales in period t. 3. Mr. Bill Doors is trying to determine the forecasts for the first quarter of 2019 for his best-selling accounting software products, QuickSheets and QuickTax. he fırst uses seasonalized time series analysis to forecast the total sales of the two products (in '000 dollars). Then, separately, he uses exponential smoothing (with a = 0.80) on historical data to determine what fraction of total sales represented each product to predict the fraction for the future. Multiplying the forecast for total sales with that for the fraction of total sales represented by a specific product gives him the forecast for each product. The historical data for total sales is shown in Table 1 below. Table 1 Quarter 2016 2017 2018 1 1008 1162 1172 968 1046 1086 818 904 908 4 1288 1332 1370 A linear regression analysis suggests that the following line best fit the corresponding deseasonalized data series: D: = 1004 + 13 *t, where, t the time period (for the given data, the time periods go from 1 through 12 for the twelve quarters), and Dt = deseasonalized total sales in period t. 3.

Answer rating: 100% (QA)

A Forecast for total sales in Q1 of 2019 1004 1313 Here Q1 ... View the full answer