A local moving company has collected data on the number of moves they have been asked to perform over the past two years. Moving is highly seasonal, so the owner/operator, who is both burly and highly educated, decides to apply the multiplicative seasonal method to forecast the number of customers for the coming year. The equation for the trend line of yearly sales is Ft = 16 + 60t. Please forecast demand for each quarter in Year 3. (Round the forecasts to whole numbers and show all calculations). Complete the table below and forecast the sales of Year 3 by quarter. Year 1 Year 2 Year 3 Quarter Demand Seasonal Index Quarter Demand Seasonal Index Average Seasonal Index Forecast 1 20 1 27 2 40 2 45 3 45 3 55 4 31 4 41 Total Average

A local moving company has collected data on the number of moves they have been asked to perform over the past two years. Moving is highly seasonal, so the owner/operator, who is both burly and highly educated, decides to apply the multiplicative seasonal method to forecast the number of customers for the coming year. The equation for the trend line of yearly sales is Ft = 16 + 60t. Please forecast demand for each quarter in Year 3. (Round the forecasts to whole numbers and show all calculations). Complete the table below and forecast the sales of Year 3 by quarter. Year 1 Year 2 Year 3 Quarter Demand Seasonal Index Quarter Demand Seasonal Index Average Seasonal Index Forecast 1 20 1 27 2 40 2 45 3 45 3 55 4 31 4 41 Total Average

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter5: Business And Economic Forecasting

Section: Chapter Questions

Problem 2.1CE

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A manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives are SR1 = 0.9, SR2 = 0.95, SR3 = 1.05, and SR4 = 1.1. The trend equation is: Ft = 11 + 3t. Over the past nine quarters, demand has been as follows: %3D Period, t: 1 4 7 8 9. Demand: 15 17 20 23 25 29 34 36 39 Click here for the Excel Data File Compute the MAD and tracking signal for each period. (Negative values should be indicated by a minus sign. Round your intermediate calculations and final answers to 3 decimal places.) Period, t Demand MAD Tracking signal 1 15 2 17 3 20 4 23 25 6. 29 7 34 36 39 LO
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3. Rubax, a U.S. manufacturer of athletic shoes, estimates the following linear trend model for shoe sales: Qt = a+bt+c1D1+c2D2+c3D3Where, Qt = sales of athletic shoes in the t-th quartert = 1, 2, . . . . , 28 [2011(I), 2011(II), . . . . , 2017(IV)]D1 = 1 if t is quarter I (winter); 0 otherwiseD2 = 1 if t is quarter II (spring); 0 otherwiseD3 = 1 if t is quarter III (summer); 0 otherwiseThe regression analysis produces the following results: Is there sufficient statistical evidence of an upward trend in shoe sales? explain Do these data indicate a statistically significant seasonal pattern of sales for Rubax shoes? If so, what is the seasonal pattern exhibited by the data? Using the estimated forecast equation, forecast sales of Rubax shoes for 2018(III) and 2019(II).
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The Global Machine Manufacturing Company, Q5. manufacturing Heavy Machines in the Sultanate of Oman. The company has decided to buy a new advance machine to produce the different equipment's. The decision will rest partly on the anticipate sales of machines in the coming months. The actual numbers of machines sold during the past years are as follows: Year Number of machines (Actual) 2014 1000 |2015|1200 2016 1400 2017 1550 2018 1725 2019|1860 2020 2025 a. Forecast the sales for the year of 2021 using a 3-Year moving average method. b. Forecast the sales for the year of 2021 using a 3-Year weighted moving average, with weights of 5, 3 and 2. Using 5 for the most recent Year. c. Compute the forecast for the year 2021 using exponential smoothing with a = 0.5. (Assume the forecast for 2014 was 900 Machines) Compute the MAD based on calculation in c. с. d.
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