Consider the following actual and forecast demand levels for Big Mac hamburgers at a local McDonald's restaurant:DayMondayTuesdayWednesdayThursdayFridayActual Demand Forecast Demand88.0072.0068.0048.0088.0088.0084.0080.00?The forecast for Monday was derived by observing Monday's demand level and setting Monday's forecast level equal to this demand level. Subsequent forecasts were derived by using exponential smoothingwith a smoothing constant of 0.25. Using this exponential smoothing method, the forecast for Big Mac demand for Friday is Big Macs (round your response to one decimal place).

The Formula for exponential smoothing forecast is:Ft+1 = Yt + ( 1 - ) FtHere, Ft+1 is the Forecast…

Answered: Consider the following actual and…

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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The manager of the Petroco Service Station wants to forecast the demand for unleaded gasoline next month so that the proper number of gallons can be ordered from the distributor. The owner has accumulated the following data on demand for unleaded gasoline from sales during the past 10 months. Compute an exponentially smoothed forecast with an a value of .30. According to the result from Excel and/or POM-QM, the forecast for the month of January would be (type number only, two decimals) Month October November December January February March April May June July 733.25 Gasoline Demanded (gal.) 800 725 630 500 645 690 730 810 1,200 980
Amazon finds that sales in July are much greater relative to other months because of the Amazon Prime days in that month. Assuming that an exponential smoothing model is used for forecasting sales, what should the company best do to make the forecast for the next month (Aug) more reflective of reality? Please pick from the provided options. F t+1 = αDt + (1-α) Ft increase value of alpha decrease value of alpha stay with the same alpha decrease the expected forecast for the current month (Ft) On hearing our forecast, our clients probe - how sure are we about the forecast? Which measure of errror (among those stated below) should we best use to respond? a. Root MSE (RMSE) b. Mean absolute percentage error (MAPE) c. Mean forecast error (Avg. error) d. Cumulative forecast error (CFE)
Please do not give solution in image formate thanku.
Generate forecasts for data with diff erent patterns, such as level, trend, and seasonality and cycles.
In a retail store, the actual sales of a particular product (in thousands of units) over the past few months are as follows: Month Sales 1 16 2 22 3 18 4 20 5 23 Using exponential smoothing method with α (smoothing constant) of 0.75 and the given forecast for month 1 equal to 10, what is the forecast for month 6?
Medium-term forecasts are used for making medium-term decisions related to planning for new products, capital expenditures, facility location or expansion, and research and development. True False
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
b. Compute 2s control limits for each forecast. (Do not round your intermediate calculations. Round your answers to 2 decimal places.) Forecast Method 1 Method 2 Control Limits
If the forecast and the actual demand in the year 2021 was 600 and 700 respectively, what is the forecast for the year 2022 according to the naive forecasting method? 600 700 650 800
A company wants to generate a forecast for unit demand for year 2017 using exponential smoothing. The actual demand in year 2016 was 120. The forecast demand in year 2016 was 110. Using this data and a smoothing constant alpha of 0.1, which of the following is the resulting year 2017 forecast value?
Harlen Industries has a simple forecasting model: Take the actual demand for the same month last year and divide that by the number of fractional weeks in that month. This gives the average weekly demand for that month. This weekly average is used as the weekly forecast for the same month this year. This technique was used to forecast eight weeks for this year, which are shown in the following tables along with the actual demand that occurred. The following eight weeks show the forecast (based on last year) and the demand that actually occurred (picture attached): Calculate the MAD and tracking signal for each week.
The manager of the Carpet City outlet needs to make an accurate forecast of the demand for Soft Shag carpet (its biggest seller). If the manager does not order enough carpet from the carpet mill, customers will buy their carpet from one of Carpet City's many competitors. The manager has collected the following demand data for the past 8 months: Demand for Soft Shag Month Carpet (1,000 yd.) 1 8 2 12 3 7 4 9 5 15 6 11 7 10 8 12 Compute the exponentially smoothed forecast (a = .20) for the given data. Compute an adjusted exponentially smoothed forecast (with a = .20 and β = .20) for the given data

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