A dry cleaner uses exponential smoothing to forecast equipment usage at its main plant. August usage was forecasted to be 45percent of capacity, actual usage was 52 percent of capacity. A smoothing constant of .05 is used.a. Prepare a forecast for September. (Round your final answer to 2 decimal places.)Forecast for Septemberpercent of capacityb. Assuming actual September usage of 52 percent, prepare a forecast for October usage. (Round your answer to 2 decimal places.)Forecast for Octoberpercent of capacity

Formula = Forecast for previous period+Smoothing constant(Actal usage- Forecast for previous period)…

Answered: A dry cleaner uses exponential…

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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A. Find the tracking signal for each month. B. Does the model provide acceptable answers!
2)Auto sales over a 4-month period were forecasted as follows: 89, 98, 105, and 97. The actual results over the 4-month period were as follows: 92, 96, 101, and 100. What was the MAD of the 4-month forecast? (use an excel sheet to make all calaculations and show formulas used in excel)
If excel required then attached screenshot
4. An electrical contractor's records during the last five weeks indicate the number of job requests: 1 3 20 18 Week Requests 2 22 4 21 5 22 Predict the number of requests for week 6 using each of these methods: a. Naive b. A four-period moving average c. Exponential smoothing with a = 30; use 20 for week 2 forecast
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
Which of the following is not true of qualitative forecasting methods? a. They generally work best when combined with a quantitative approach b. They are more objective than quantitative methods c. They are largely non-mathematical d. They are not restricted to only the quantifiable data e. They come with the danger of biasing the forecast due to subjectivity Explain both true and false options briefly
If we use a simple exponential smoothing method with ??=0.3, ??11=100 and ??12=120, what is your forecast for next year? A. 120 B. 126 C. 128 D. None of the above 10. Which one is NOT part of the reasons to keep inventory? A. To allow flexibility in production scheduling B. To meet variation in product demand C. To maintain dependence of operations D. To provide a safeguard for variation in raw material delivery time
You have a data set that includes time period and past sales data, and you want to use a time series forecasting technique. Which of the following forecasting methodologies is considered a time series forecasting technique? a.Group of answer choices b.Delphi method c.Simple movement smoothing d.Weighted moving average e.Simulation f.Exponential averaging
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
Assume that the data in columns A and B report the new constructions of residential homes, per month, in thousands, from 2015 to 2020 in the state of Oregon. a) Chart the data. Discuss any apparent trend and seasonal patterns. b) Use the "Tahoe Salt" method with linear trend to forecast new constructions for the 12 months of 2021. c) Add your model values and forecast to the data chart. d) Compute the MAD of your model. e) Compute and plot the tracking signal in a new chart. f) Discuss the quality of this model. What is the flagrant flaw? g) Suggest an approach that would yield better results in terms of forecast values, MAD, and tracking signal. An appropriate narrative argument is sufficient (i.e., one or two sentences). You do not need to do calculations for this part.

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