Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table.4 5 6 7 8 9 10 114 9 9 8 11 11 14 17YearOA A3-year weighted moving average is significantly better.B. A 3-year moving average is significantly better.OC The forecasts are about the same.1Registrations (000) 42735This exercise contains only part cc) The graph to the right shows the actual registrations, registrations forecasted using a 3-year moving average, and registrations forecasted using a 3-year weighted moving average. Whichmethod seems to be able to forecast better? (Refer to the legend or hover your mouse over any plot)1812-161514-13-12-1110-BIB75-4-342-Demand235Year9 1611 12Blue Line = Actual RegistrationsRed Line = 3-year Moving AveragePink Line = 3-year Weighted Moving Average

Forecasting includes predicting the sales or demand of the future. There are various methods of…

Answered: c) The graph to the right shows the…

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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9) Gasoline sales Times Series week sales (1000s of gallons 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 With the above gasoline time series data, show the exponential smoothing forecast using alpha = 0.1 i)Applying the MSE measure of forecast accuracy, would you prefer a smoothing constant of Alpha= 0.1 or alpha=0.2 for the gasoline sales time series? ii)Are the results the same if you apply MAE as the measure of accuracy? iii)What are the results if MAPE is used?
(4) Exponential smoothing with a smoothing constant equal to 0.15, assuming a March forecast of 15(000). (Round your intermediate forecast values and final answer to 2 decimal places.) Forecast thousands (5) A linear trend equation. (Round your intermediate calculations and final answer to 2 decimal places.) Yt thousands
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.
a. What is the mean square error for time periods 2 through 4 using the average forecasting method? b. What is the mean absolute error for time periods 2 through 4 using the average forecasting method? c. What is the mean absolute percentage error for time period 2 through 4 using the average forecasting method? Round all answers to two decimal places. Time Period 1 2 3 4 Mean absolute error (MAE) Mean squared error (MSE) Mean absolute percentage error (MAPE) Electric Bill 510 315 420 480 Average Forecast Forecast Error
a) Forecast the demand for the week of October 12 using a 3-week moving average. b) Use a 3-week weighted moving average, with weights of .1, .3, and .6, using .6 for the most recent week. Forecast demand for the week of October 12. c) compute the forecast for the week of Oct 12 using exponential smoothing with a forecast for august 31 of 360 and alpha 0.2
January February March April May June a. Calculate forecasts for the remaining five months using simple exponential smoothing with a = 0.4. February March April May June ACTUAL FORECAST 100 85 96 103 82 66 90 MAD Forecasts 91 93 97 91 81 b. Calculate the MAD for all the forecasts, including January's. (Round your answer to 1 decimal place.)
The Toro Cutlery Company has collected monthly sales information below: MONTH January February March April The company is examining two forecasting methods, moving average and exponential smoothing for forecasting sales. a. What will the forecast be for January the following year using a three-, four-, and five-month moving averages? Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast (January, 3-month MA): 87667 Forecast (January, 4-month MA): 72500 Forecast (January, 5-month MA): 69600 b. What will the forecast be for January the following year using exponential smoothing with a = 0.6? Assume the forecast for February this year is 25,000. Do not round intermediate calculations. Round your answer to the nearest whole number. SALES 25,000 18,000 43,000 110,000 MONTH May June July August SALES MONTH 84,000 September 28,000 October 97,000 November 58,000 December SALES 27,000 105,000 82,000 76,000
41) A medium-term forecast is considered to cover what length of time? A) 2-4 weeks B) 1 month to 1 year C) 2-4 years D) 5-10 years E) 20 years 42) When is the exponential smoothing model equivalent to the naÃ¯ve forecasting model? A) ? = 0 B) ? = 0.5 C) ? = 1 D) during the first period in which it is used E) never 43) Enrollment in a particular class for the last four semesters has been 120, 126, 110, and 130. Suppose a one-semester moving average was used to forecast enrollment (this is sometimes referred to as a naÃ¯ve forecast). Thus, the forecast for the second semester would be 120, for the third semester it would be 126, and for the last semester it would be 110. What would the MSE be for this situation? A) 196.00 B) 230.67 C) 100.00 D) 42.00 E) None of the above 44) Which of the following methods tells whether the forecast tends to be too high or too low? A) MAD B) MSE C) MAPE D) decomposition E) bias 45) Assume that you have tried three different…
Tools View Week 3 Bonus Activity- DEMAND FORECASTING CASE STUDY After reviewing the forecasting demonstration and looking over the slides, complete the following case activity and transfer your answers to the appropriate questions in the Canvas activity quiz. You have been hired as a demand planning intern for Hawaiian Island Creations (HIC). They want you to de- velop a forecast for their HIC Papanui style of sun- glasses. The goal is to determine how many pair they will produce to meet retailer demand in July 2021. During your first meeting, you were handed some data to work with and the product team talked about the company's upcoming promotional blitz to support Summer Break '21 in major vacation destinations. Month Forecast Demand January 2021 4.000 3,300 February 2021 4,200 3,900 March 2021 4,500 4,300 April 2021 4.800 4,200 May 2021 5 000 5.400 of 4 P Type here to search 立
a. Using POM for Windows' least squares-linear regression module, develop a relationship to forecast production ratings from test scores. (Round your responses to three decis and include a minus sign if necessary.) Y= - 23 + .945 x where Y = Production rating and X = Test score. b. If a worker's test score was 54, what would be your forecast of the worker's production rating? 51. (Enter your response as an integer.) c. Comment on the strength of the relationship between the test scores and production ratings. The coefficient of correlation for the least-squares regression model is and the coefficient of determination is (Enter your responses rounded to three decimal places.) More info Test Score Production Rating Production Test Worker Worker Rating Score A 55 43 K 58 57 B 38 43 75 75 93 87 67 48 D 86 77 31 26 E 88 82 62 49 F 66 68 24 25 G 55 47 Q 78 84 Clear all Check 50 46 34 32 41 41 51 58 J 69 74 T 39 30 Print Done LLMN OPoRS
Centerville Bikes and Stuff (CBS) sells motorcycles and accessories. The number of helmets sold by CBS per week for the past six weeks follows. Week 1 2 3 Value 18 13 (a) Construct a time series plot. 20T 18 16- 14- Time Series Value O Week 1 2 3 4 5 6 What type of pattern exists in the data? O The data appear to follow a cyclical pattern. O The data appear to follow a trend pattern. 8 6 O The data appear to follow a seasonal pattern. O The data appear to follow a horizontal pattern. Week 1 2 0 1 3 4 5 6 18 13 15 12 (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Time Series Value 16 14 18 + 2 13 15 4 5 6 15 12 16 3 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? 12 16 4 14 Week (c) Use a = 0.2 to compute the exponential smoothing values for the time series. Time Series Value 5 14 Forecast 6 Forecast 7 20 18 16 14 12 WE 10 2 + 7 @o 20 18 0 1 2 3 4 Week 5 6 00 0 1 2 3 4 5 Week 6 7…
Bradley's Copiers sells and repairs photocopy machines. The manager needs weekly forecasts of service calls so that he can schedule service personnel. Use the actual demand in the first period for the forecast for the first week so error measurement begins in the second week. The manager uses exponential smoothing with a = 0.4. Forecast the number of calls for week 6, which is next week. Week Actual Service Calls 26 2 34 38 4 27 5 35 The forecast for week 6 is service calls. (Enter your response rounded to two decimal places.)

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