WeekForecastActualDemand524842463565244547true or falseAssume that the actual demand is representative of a repeating pattern over 4 weeks. The cyclicalindex for Week 1 is (approximately) 1.07The forecast of demand for Week 5 (F5) using a Simple Moving Average (SMA) with 3 weeks is 48.75.The forecast of demand for Week 5 (F5) using exponential smoothing with alpha = 0.3 is 46.4.

The table shows the calculation of forecast of demand using the simple moving average method with 3…

Answered: Week Actual Forecast Demand 1 52 48 2…

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 manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives areSR1 = .90, SR2 = .95, SR3 = 1.05, and SR4 = 1.10. The trend equation is: Ft= 10 + 5t. Over thepast nine quarters, demand has been as follows:Period, t 1 2 3 4 5 6 7 8 9Demand 14 20 24 31 31 37 43 48 52Is the forecast performing adequately? Explain.
National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a seven-month period is reported below: Sales (1000 units) Forecast Observation Month Yt Ft 1 February 19 2 March 18 3 April 15 4 May 20 5 June 18 6 July 22 7 August 20 8 September ? Use Excel to plot the data and forecast September sales using the following methods: The naïve forecast A three-month moving average Exponential smoothing with a smoothing coefficient of α = 0.2, assuming a February forecast of 19 A 3-month weighted moving average, with weights 0.60, 0.3, and 0.1. With 0.6 applied to the most recent past.
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
Use simple exponential smoothing with a -0.8 to forecast electric scooter sales at Guelph- Humber Inc. for July. Assume that the forecast for May was for 45 electric scooters. Round your answer to 1 decimal Electric Scooter Sales Month May 42 June 47 July 45 August 40 Weekly demand for medical masks for the last five weeks at Chopper Drug Store has been as follows: 92, 96, 100, 100 and 102 (listed from the oldest to most recent). Suppose a naive forecast was used to forecast demand. What would the MAD be for this situation? Enrollment in a particular Yoga class at Guelph Fitness Centre for the last five months has been 80, 86, 88, 88 and 90(listed from the oldest to most recent). Suppose a two-month mov average was used to forecast enrollment. What would the MSE be for this situation?
Please solve the attached question.
The following data are for calculator sales in units at an electronics store over the past nine weeks: Week Sales Week Sales 1 45 53 2 50 7 59 3 44 8. 59 4 51 9 64 5 57 Use trend projection with regression to forecast sales for weeks 10 - 13. What are the error measures (CFE, MSE, o, MAD, and MAPE) for this forecasting procedure? How about ? Obtain the trend projection with regression forecast for weeks 10 – 13. (Enter your responses rounded to two decimal places.) Period Forecast, F, 10 64.81 11 67.06 12 69.31 13 71.56 Obtain the error measures. (Enter your responses rounded to two decimal places.) CFE MSE MAD МАРЕ
A forecast for the first six months of the year revealed a tendency to underpredict the actual demand for the revitalized Hubig’s Pies plant in the Marigny. Month Actual Forecast January 675 600 February 720 700 March 640 620 April 510 495 May 480 410 June 565 535 What is the mean squared error of this forecast? a. 1,694 b. 1,873 c. 2,075 d. 1,469
Use exponential smoothing with trend adjustment to forecast demand for period 11. Let α = 0.5, � = 0.3, and let the initial trend value be 12 and the initial forecast be 200
Demand for oil changes at Garcia's Garage has been as follows: Number of Oil Changes January 44 February 49 March 66 IT April 59 May 53 June 58 59 63 Month July August a. Use simple linear regression analysis to develop a forecasting model for monthly demand. In this application, the dependent variable, Y, is monthly demand and the independent variable, X, is the month. For Janu The forecasting model is given by the equation Y=+x. (Enter your responses rounded to two decimal places) J Show Transcribed Text >. Use the model to forecast demand for September, October, and November. Here, X=9, 10, and 11, respectively. (Enter your responses rounded to two decimal places.) Forecast for the number of Oil Changes Show Transcribed Text Month September October November can you do all the parts please corrrect
The actual number of patients at Providence Emergency Medical Clinic for the first six weeks of this year follows: The value of the forecast is Week Actual No. of Patients 45 49 IT 56 40 44 55 Clinic administrator Dana Schniederjans wants you to forecast patient numbers at the clinic for week 7 by using this data. You decide to use a weighted moving average method to find this forecast. Your method uses four actual demand levels, with weights of 0.333 on the present period, 0.250 one period ago, 0.250 two periods ago, and 0.167 three periods ago. a) What is the value of your forecast? patients (round your response to two decimal places). 123456
The following table shows predicted product demand using your particular forecasting method along with the actual demand that occurred: FORECAST ACTUAL 1,480 1,530 1,380 1,480 1,680 1,580 1,730 1,780 1,630 1,680 Compute the tracking signal using the mean absolute deviation and running sum of forecast errors. Note: Negative values should be indicated by a minus sign. Round your "Mean Absolute Deviation", "Tracking Signal" to 2 decimal places and all other answers to the nearest whole number. Period Forecast Actual Deviation RSFE Absolute Deviation Sum of Absolute MAD TS Deviation 1 1,480 1,530 -50 -50 50 50 50.00 -1.00 2 1,380 1,480 -100 -150 100 150 75.00 -2.00 3 1,680 1,580 100 -50 100 250 83.33 -0.60 4 1,730 1,630 100 50 100 350 87.50 0.57 5 1,780 1,680 100 150 100 450 90.00 1.67
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

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