Prepare a graph of the monthly forecasts and average forecast demand for Chicago Paint Corp., a manufacturer of specialized paint for artists.Compute the demand per day for each month (round your responses to one decimal place).MonthJanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecemberChoose the correct graph of the forecast demands below.OAProduction Days2222222222231920212023212019Demand Forecast9501,0501,2501,3501,3001,3001,2501,1501,0501,0001,000950Demand per Day325

Find the Given details below:Given details:MonthProduction DaysDemand…

Answered: Prepare a graph of the monthly…

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 a fabric company needs to accurately forecast the demand for fabric. If the customers do not order enough fabric (in 10,000 yards), they will buy their fabric from one of the company’s major competitors. The company has collected the following demand data for the past 10 months. Compute a weighted three-month moving average forecast using weights of (a) 10%, 30%, 60%, and (b) 25% 30% 45% for the most distant data, next recent, and the most recent respectively. Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Demand 37 45 47 50 52 54 58 60 63 65 Forecast Table: Month Actual WMA (10%, 30%, 60%) WMA (25%, 30%, 45%) January February March April May June July August September October
Below is a table containing data on product demand for the most recent five months along with the forecasts that had been made for those 5 previous months. Use the 3-period simple moving average method to forecast the number of sales to expect next month. Month Demand Forecast 1 308 341 388 343.3 3 344 364.7 4 400 346.7 341 377.3
Two different forecasting models were used to forecastsales of a popular soda on a college campus. Actual demand andthe two sets of forecasts are shown. Use MAD to explain whichmethod provided a better forecast.
Explain the function of demand forecasting in the logistics system and supply chain of a company! Then determine the demand forecasting value for the next 12 months based on the following historical data using several quantitative methods such as linear regression, exponential smoothing, and moving average! Note: The moving average period is 3 months, while the alpha for exponential smoothing is 0.53
The following table shows the actual demand observed over the last 11 years: Year 1 2 3 4 5 6 7 8 9 10 11 Demand 8 8 4 9 12 7 11 14 9 13 8 Part 2 Using exponential smoothing with α = 0.50 and a forecast for year 1 of 7.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). Year 1 2 3 4 5 6 7 8 9 10 11 12 Forecast 7.0 enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here enter your response here
please do ii. and explain and breakdown workings.
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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.
The following table shows the actual demand observed over the last 4 years: 1 Year Demand 8 Year Forecast (ES) 1 7.0 Using exponential smoothing with a = 0.30 and a forecast for year 1 of 7.0, provide the forecast from periods 2 through 5 (round your responses to one decimal place). 3 5 Provide the forecast from periods 2 through 5 using the naive approach (enter your responses as whole numbers). Year Forecast (NA) 2 10 2 2 3 4 3 4 4 9 4 5
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?
Historical demand for a product is DEMAND January 12 February 11 March 15 April 12 May 16 June 15 Using simple linear regression analysis, calculate the regression equation for the preceding demand data. Note: Round your intercept value to 1 decimal place and slope value to 2 decimal places. Using the regression equation in d, calculate the forecast for July. Note: Round your answer to 1 decimal place.
The following table shows the actual demand observed over the last 11 years: Year Demand 1 7 Year Forecast 2 8 2 3 4 3 4 10 4 Using exponential smoothing with a = 0.30 and a forecast for year 1 of 6.0, provide the forecast from periods 2 through 12 (round your responses to one decimal place). 3 2 4 5 6 T 8 9 Year 1 Forecast 6.0 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers) 5 12 5 6 7 6 7 8 11 14 7 8 9 10 9 10 10 10 13 11 11 11 8 12 12

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