George Kyparisis owns a company that manufactures sailboats. Actual demand for George's sailboats during each of the past fourseasons was as follows:YearSeason2341,4001,5001,0001,0001,600Winter1,200960Spring1,4401,500Summer2,1202,0402,000Fall680810650520George has forecasted that annual demand for his sailboats in year 5 will equal 6,000 sailboats.Based on the given data and using the multiplicative seasonal model, the demand level for George's sailboats in the spring of year 5will be 1775 sailboats (enter a whole number).

Find the given details below: Given details: Year Season 1 2 3 4 Winter 1400 1200 1000…

Answered: George Kyparisis owns a company that…

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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Demand for stereo headphones and MP3 players for joggers has caused Nina Industries to grow almost 50 percent over the past year. The number of joggers continues to expand, so Nina expects demand for headsets to also expand, because, as yet, no safety laws have been passed to prevent joggers from wearing them. Demand for the players for last year was as follows: a. Using linear regression analysis, what would you estimate demand to be for each month next year? (Do not round intermediate calculations. Round your answers to 2 decimal places.) b. To be reasonably confident of meeting demand, Nina decides to use 2 standard errors of estimate for safety. How many additional units should be held to meet this level of confidence? (Do not round intermediate calculations. Round your answer to the nearest whole number.)
The Fieldale Dairy produces cheese, which it sells to su-permarkets and food processing companies. Because of concerns about cholesterol and fat in cheese, the companyhas seen demand for its products decline during the pastdecade. It is now considering introducing some alternativelow-fat dairy products and wants to determine how much available plant capacity it will have next year. The com-pany has developed an exponential smoothing forecast with 0.40 to forecast cheese. The actual demand andthe forecasts from its model are shown as follows: Assess the accuracy of the forecast model using MAD and cu-mulative error, and determine if the forecast error reflects bias using a tracking signal and 3 MAD control limits. If the ex-ponential smoothing forecast model is biased, determine if a linear trend model would provide a more accurate forecast.
1. The following data table shows attendance in the class. Week 5 No. of Students 58 6 7 60 62 59 1 50 2 3 4 55 48 Estimate the attendance in the 8th week using a. Exponential smoothing assuming alpha=0.1 and forecast for 7th week was 58.
George Kyparisis owns a company that manufactures sailboats. Actual demand for George's sailboats during each of the past four seasons was as follows: Year D 2 1,240 1,440 2,140 770 George has forecasted that annual demand for his sailboats in year 5 will equal 6,000 sailboats. Based on the given data and using the seasonal model, the demand level for George's sailboats in the spring of year 5 will be a whole number and round all intermediate calculations to two decimal places). Season Winter Spring Summer Fall 1 1,440 1,560 1,040 680 3 1,080 1,620 2,040 650 4 960 1,540 1,960 500 sailboats (enter your final answer as
14 Community General Hospital finds itself treating many bicycle accident victims. Data from the last seven 24-hour periods is shown below: Day Bicycle Victims 1 8 2 14 3 8 4 14 5 18 6 15 With an alpha value of 0.31 and a starting forecast in day 3 equal to the 21 , what is the exponentially smoothed forecast for day 4? (Round to two decimal places) 15 What is the exponentially smoothed forecast for day 5? (Round to two decimal places) 16
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
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 9 13 8 11 14 9 13 7 Part 2 Using exponential smoothing with α = 0.40 and a forecast for year 1 of 5.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). Year 1 2 3 4 5 6 7 8 9 10 11 12 Forecast 5.0 5.45.4 6.46.4 5.55.5 6.96.9 9.39.3 8.88.8 9.79.7 11.411.4 10.410.4 11.511.5 9.79.7 Part 3 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers). Year 2 3 4 5 6 7 8 9 10 11 12 Forecast enter your response here enter your response here enter your response here enter your…
Sales for Pandora’s Jewellery for the past three months have been 200,350, and 287. Usea three-month moving average to calculate a forecast for the fourth month. If the actual demandfor month 4 turns out to be 300, calculate the forecast for month 5.
Given an actual demand this period of 143, a forecast value for this period of 119, and an alpha of .6, what is the exponential smoothing forecast for next period? 123.8 118.2 O 122.2 119.8 O 117.4
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).
4 Trinity General Hospital had the following number of patient admissions during the past 8 weeksWeek Patient Admissions1 1202 1453 954 1125 1306 1107 1008 140 a. Develop a 3-week weighted average forecast forWeek 4 through 9 with weightsW1 = 0.2W2 = 0.3W3 = 0.5 b. Forecast patient admissions for week 9 using simpleexponential smoothing with α = 0.2. Assume that the forecast for Week 2 (F2) is the naïve forecast.

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