b. Prepare forecasts for June through September by using an exponential smoothing model with α = 0.4. Assumethat the forecast for May was 2,100 (enter your responses rounded to the nearest whole number).MonthMarchAprilMayJuneJulyAugustSeptemberMarchAprilMayJuneDemandDemand1202,0301,1104,2103,2605,830c. Prepare forecasts for June through September by using an adjusted exponential smoothing model with α = 0.4and ß = 0.2. Assume that the unadjusted forecast for May was 2,100 and the trend factor T₁ for May was 900(enter your responses rounded to the nearest whole number).Month1202,0301,1104,210Forecast2,10017042707292840892,1001,704UnadjustedforecastAdjustedforecast

Here, for each month, I have been given the demand data, I would use techniques like simple…

Answered: b. Prepare forecasts for June through…

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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4 .Substitute for Problem # 4 on in attachment)-Calculate the MAD,revised MAD and the Revised Forecast for months 1-6 for the following three groups,where the Forecast stands for Forecast Demand.Has your forecast improved ? Tell me how would you go about improving the revised forecast( for each of the three groups)without actually doing so? Estate Planning Group Auditing and Accounting Group Business Consulting Group Month Actual Demand Forecast Actual Demand Forecast Actual Demand Forecast 1 100 125 270 230 140 135 2 90 125 240 230 130 135 3 110 125 280 230 160 135 4 115 125 260 230 180 135 5 130 125 300 230 200 135 6 115 125 220 230 190 135
4. The sales (in millions of dollars) for an 18-month period are as follows. Month Sales Month Sales 1 600 600 775 10 775 3 600 11 600 4 650 12 575 700 13 625 800 14 650 550 15 600 8 775 a. Compare a three-month moving average forecast with an exponential smoothing forecast. Use a = 0.1. Which provides the better forecasts based on MSE? b. Find the forecast for the next month using the best forecast method. 2.
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4. What is the difference between trend and seasonality in time series data? 5. Here are the errors associated with a particular forecast over the past 5 months, in chronological order: 5, 10, -15, 0, 8. In which month was the forecast perfectly accurate? In which month was the forecast the least accurate? In which month or months was the forecast too high? (Noteshaper Ramp Up # 23) 6. Tutoring Center needs to allocate tutors this week for office appointments, so it needs to forecast the number of students who will seek appointments. The director has gathered the following time series data recently: Time Period Code Student Appointments Jan 6 - 10 95 Jan 13 - 17 80 Jan 20 - 24 65 Jan 27 – 31 4 50 a) What is the naïve forecast for the number of student appointments for Time Period 5 (Feb 3– 7)? b) What is the 2 week moving average for Time Period 5? c) What is the 3 week moving average for Time Period 5? d) What is the forecast for Time Period 5 using exponential smoothing with alpha =…
eBook Problem 6-05 Consider the following time series data. 3 16 Week 1 Week 2 Value 18 13 a. Choose the correct time series plot (1) € (!!!) Time Series Value Time Series Value 28642986420 284H2G86420 1 4 11 2 {B} 2 TH 3 Week (t) Week (t) 5 6 € (iv) Time Series Value Time Series Value 28642 NO 28642 NO 1 2 2 4 3₁ Week (t) Week (t) 5 6
Here are the errors associated with a particular forecast over the past five months, in chronological order: 2, 5, 0, -5, -10. Which of the following statements is (are) true? I. The forecast was too high during the fifth month. II. The mean error over these five months is -2. III. The forecast was perfectly accurate during one of the months. a. I only Ob. Il only O. Il only d. I and III Oe.I, Il and II
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The following tabulations are actual sales of units for six months and a starting forecast in January. ACTUAL 124 FORECAST 104 120 133 109 86 105 January February March April May June a. Calculate forecasts for the remaining five months using simple exponential smoothing with a = 0.3. Note: Round your answers to the nearest whole number. February March April May June Saved Forecasts b. Calculate the MAD for all the forecasts, including January's. Note: Round your answer to 1 decimal place. MAD
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It wouldnt let me take a screenshot of the table so I had to copy and paste it in here. My question is: How do you Calculate a moving average forecast using the last 2 and 4 dates of stay. What is the prediction for 7/1/2021 for each technique? Discussion Question 1 - 200 room hotel Forecasts MA 2 Errors MA 4 Errors ES (0.8) Errors ES (0.5) Errors Date Day of Week Rooms Sold MA 2 MA 4 ES (0.8) ES (0.5) AE APE AE APE AE APE AE APE 6/1/2021 Tuesday 123 6/2/2021 Wednesday 109 6/3/2021 Thursday 140 6/4/2021 Friday 199 6/5/2021 Saturday 179 6/6/2021 Sunday 140 6/7/2021 Monday 117 6/8/2021 Tuesday 132 6/9/2021 Wednesday 108 6/10/2021 Thursday 151…
To have a stable forecasting tool when using the simple moving average method, what value of N (the number of periods) should a firm choose among the following choices? a. 3b. 2c. 8d. 6
2. Given the following data, use exponential smoothing with a = 0.2 and a = 0.5 to generate forecasts for periods 2 through 6. Use MAD and MSE to decide which of the two models produced a better forecast. Period Actual Forecast 1 15 17 2 18 3 14 4 16 5 13 6 16

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