E.loving Average, Welghted Moving Average andExponential Smoothing, this includes: MAD, MSE and MAPE2. Usinga=0.4, determinetheforecastforthenextperiodifthevalue forecasted forthe pastperiod was 41,758 and the actual demand turned out to be 42,555.mond fr joxNjE1/a/NTE1MD92MZK5MDY1/detailsOpen with Google Docs1. National Mixer, inc. sells can openers. Monthly sales for a seven-month period were asfollows:SalesMonth (000units)Feb19Mar18AprMayJune152018JulyAug2220Forecast September sales using each of the following:A The Naive ApproachB. Three month moving averageC.A weighted moving average using 0.60 for the recent month, 0.30 for two months ago,and 0.10 for three months agoD. Exponential smoothing with a smoothing constantof 0.20E Calculate the forecast errors for Moving Average, Weighted Moving Average andExponential Smoothing, this includes: MAD, MSE and MAPEPage2 1 3

Forecasting techniques are used to predict future events. Forecasting is the process of estimating…

Answered: A. The Naive Approach B. Three month…

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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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
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.
Given the table below, complete the missing cell values applying the Exponential Smoothing method of forecasting and Mean Absolute Deviation. Answer also the other 2 related questions below the table. Numbers with decimal should take 2 decimal places. Actual Quarter Tonnage Unloaded 1 2 3 4 5 6 7 8 175 160 170 160 160 170 180 200 Forecast for a=3 175 175.0 170.5 167.2 165.1 166.6 170.6 Sum of absolute deviation = Absolute Deviation for a = .3 Other questions: (1) What is the MAD for a = .3? (2) Which smoothing constant would you prefer? 0.00 15.00 0.50 10.35 4.93 13.45 29.41 80.89 Forecast for a = .6 175 166.0 168.4 163.4 161.3 166.5 174.6 Absolute Deviation for a = .6 0.00 15.00 4.00 8.40 3.36 8.66 13.46 25.38
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)
Which time-series forecasting method works best if the company assumes that product demand will decrease over time? A. Weighted moving average B. Linear trend C. Moving average D. Exponential smoothing
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: Year Year Forecast (000) 1 2 4.00 7.00 1 5.00 3 5.00 Registrations (000) a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a smoothing constant (a) of 0.40 and a starting forecast of 5.00 for year 1 (round your responses to one decimal place): 2 3 4.6 5.56 4 4.00 4 5.34 11 9 10 7 8 6 5 9.00 9.00 6.00 10.00 13.00 14.00 12.00 5 4.80 6 7 6.48 7.49 8 6.89 9 8.14 10 10.08 11 11.64 12 11.79 b) Mean absolute deviation based on the forecast developed using the exponential smoothing method (with a smoothing constant (a) = 0.40 and a starting forecast of F₁ = 5.00) is response to one decimal place). registrations (round your
Forecasting time horizons include:a) long range. b) medium range.c) short range. d) all of the choices.
A security company had to deploy guards for emergencies multiple times in the last four evenings. The numbers of emergencies for Monday, Tuesday, Wednesday, and Thursday were 7, 4, 8, and 11, respectively. What would be the security company's forecast for the number of emergencies on Friday using an exponential smoothing forecasting approach? (Use \alpha= 0.2 and a forecast for Monday of 10 emergencies)
Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two forecasting methods to see which method was better over this period. MONTH ACTUAL January 120 February 145 March 146 April 171 May 154 June 182 July 138 August 135 September 146 a. Forecast April through September using a three-month moving average. b. Use simple exponential smoothing with an alpha of 0.20 to estimate April through September, using the average of January through March as the initial forecast for April. c-1. Calculate MAD for Three-month moving average and Exponential smoothing. c-2. Use MAD to decide which method produced the better forecast over the six-month period.
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Give typed explanation Part 2: Using exponential smoothing, the forecasted demand for period 5 using the smoothing constant determined in image= ?
ontrast the reactive and proactive approaches to forecasting. Give several examples of types of organizations or situations in which each type is used.

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