Problem 3-24 (Algo)Zeus Computer Chips, Inc., used to have major contracts to produce the Centrino-type chips. The market has been declining duringthe past three years because of the quad-core chips, which it cannot produce, so Zeus has the unpleasant task of forecasting nextyear. The task is unpleasant because the firm has not been able to find replacement chips for its product lines. Here is demand overthe past 12 quarters:TWOLASTTHISYEARYEARS AGOYEAR4,7753,5054,3052,9703,4652,6783, 5052,3703,1802,0702,7101,695IIIIIIIIIIIIIIIIVIVIVUse the regression and seasonal indexes to forecast demand for the next four quarters. (Round your Intermedlate calculatlons andanswers to 2 declmal places.)PeriodForecast (Units)IIIIIV

Answered: Problem 3-24 (Algo) Zeus Computer…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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Serena just visited a restaurant for dinner. During the dinner time, she overheard two customers saying that company TXL will expect its workforce to go on strike next week, which will halt manufacturing and distribution of products. When Serena gets back home, she immediately uses this information to update her analyst forecast on company TXL from a “buy” to a “sell”. Please explain which Standard is violated.
UltraPure used two different techniques (F1 and F2) to forecast demand for cases of bottled water. Actual demand and the two sets of forecasts are in the table below. PREDICTED DEMAND Period Demand F1 F2 1 68 67 60 2 75 67 67 3 70 71 70 4 74 69 72 5 69 71 77 6 72 70 77 7 80 72 75 8 78 75 83 a. Compute MAD for each set of forecasts. Given your results, which forecast appears to be more accurate? (Round your answers to 2 decimal places.)
Prepare a Demand Forecast for “Year 5” using Excel. Quarterly Data for Cars Sales Yt Year Quarter Sales (1000s) Year 1 1 4.80 2 4.10 3 6.00 4 6.50 Year 2 1 5.80 2 5.20 3 6.80 4 7.40 Year 3 1 6.00 2 5.60 3 7.50 4 7.80 Year 4 1 6.30 2 5.90 3 8.00 4 8.40 Year 5 1 2 3 4
Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Year 1 2 3 4 5 Sales 460 502 520 575 575 a) Forecasted sales for year 6 using the trend projection (linear regression) method are sales (round your response to one decimal place).
The following table shows the actual demand observed over the last 11 years: Year 1 Demand 8 2 9 3 5 This exercise contains only parts b, c, and d. b) Using the 3-year moving average, provide the forecast from periods 4 through 12 (round your responses to one decimal place). Year Forecast 4 5 4 10 6 5 13 7 6 7 8 7 11 9 8 14 10 9 8 11 10 13 12 11 8
Part C Exponential Exponential Gasoline Demand Gasoline Month smoothed forecast smoothed forecast Exponential smoothed forecast (a = 0.25) Demand (a = 0.25) (a = 0.45) Exponential smoothed forecast (a = 0.45) Mar 900 920 920 1200 Apr May 755 915.00 911.00 1100 1000 650 875.00 840.80 g20 915.00 846 80 755 818.75 754.94 904.76 835.12 Jun 550 818.75 754.94 800 320 751.56 66272 645.74 746.83 Jul 625 751.56 662.72 650 600 550 Aug Sep 730 719.92 645.74 820 722.44 683.66 400 D Oct 1100 746.83 745.01 200 1 Nov 835.12 904.76 Mar Apr May Jun Jul Aug Sep Oct Nov 1. Make a comparative analysis out of your answers in the plotted data. (3-5 5 sentences)
Problem 5 You are trying to determine what forecast method to use. Based upon the following historical data, calculate the following forecast and specify what procedure you would utilize. MAY JUNE MONTH JANUARY FEBRUARY MARCH APRIL DEMAND 62 65 67 68 71 73 MONTH JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER DEMAND 76 78 78 80 84 85 a. Calculate the simple three-month moving average for periods 4 to 12. b. Calculate the weighted three-month moving average for periods 4 to 12. Use weights of 0.50, 0.30, and 0.20 for the most recent, second most recent, and third most recent periods, respectively. c. Calculate the single exponential smoothing forecast for periods 2 to 12 using an initial forecast (F₁) of 61 and a of 0.30. d. Calculate the exponential smoothing with trend component forecast for periods 2 to 12 using an initial trend forecast (T₁) of 1.8, and initial exponential smoothing forecast (F₁) of 60, an a of 0.30 and ō of 0.30. e. Calculate the MAD for the forecasts made by each…
The following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 6 8 4 10 11 9 12 12 8 13 6 This exercise contains only parts b, c, and d. b) Using the 3-year moving average, provide the forecast from periods 4 through 12 (round your responses to one decimal place). Year 4 5 6 7 8 9 10 11 12 Forecast 66 7.337.33 8.338.33 1010 10.6610.66 1111 10.6610.66 1111 99 c) Using the 3-year weighted moving average with weights 0.15, 0.30, and 0.55, using 0.55 for the most recent period, provide the forecast from periods 4 through 12 (round your responses to two decimal places).
*** Can you please demonstrate how to do parts d, e, f? Given: Year Demand 1 7 2 9 3 5 4 9 5 Predict the value for Year 5: 2 year moving average What is MSE for 2 year moving average? 2 year moving average using 0.6 (weight for the oldest period) and 0.4(weight for most recent period Exponential smoothing, =0.2 and forecast for Year 1 = 5 Linear trend Which forecast method has the least amount of error using MAD? What is the coefficient?
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Given the following demand data, compute a simple exponential smoothing forecast for alpha values of 0.2 and 0.4. Use the actual value in Period 1 as your starting forecast in Period 2. (Round all answers to two decimal places. Use these rounded answers when computing subsequent answers.) Period Actual Demand 1 2 3 4 5 6 7 8 9 10 11 Period 1 2 3 4 5 6 7 8 9 10 11 12 SESS 10 10 10 10 57 56 оннNUUо 55 55 52 51 51 50 47 49 46 a = 0.2 Forecast α = 0.4 Forecast

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