Sales of tablet computers at Marika Gonzalez's electronics store in Washington, D.C., over the past 10 weeks areshown in the table below:Week231Demand 19 23 2943656789 1026 28 35 24 24 30a) The forecast for weeks 2 through 10 using exponential smoothing with a = 0.60 and a week 1 initial forecast of19.0 are (round your responses to two decimal places):Week1 2 3 4Demand 19 23 29 36Forecast 19.05 6 726 28 358 9 1024 3024b) For the forecast developed using exponential smoothing (a=0.60 and initial forecast 19.0), the MAD = sales(round your response to two decimal places).c) For the forecast developed using exponential smoothing (x=0.60 and initial forecast 19,0), the tracking signal =(round your response to two decimal places).

It is a forecasting tool and it is mainly useful for time series data that exhibits a trend or…

Answered: of tablet computers at Marika…

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?
Consider the following time series data. Choose the correct time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. Round your answers to two decimal places. = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 7. Round your answers to two decimal places. Compare the three-week moving average forecast with the exponential smoothing forecast using Use trial and error to find a value of the exponential smoothing coefficient that results in a smaller MSE than what you calculated for = 0.2. Find a value of for the smallest MSE. Round your answer to three decimal places.
I The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 Pints Used 345 389 412 383 366 371 a) The forecasted demand for the week of October 12 using a 3-week moving average = 373.33 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.10, 0.35, and 0.55, using 0.55 for the most recent week, the forecasted demand for the week of October 12 = pints (round your response to two decimal places and remember to use the weights in appropriate order recent period and smallest weight applies to oldest period.) the largest weight applies to most
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.
The following data are for calculator sales in units at an electronics store over the past nine weeks: Week Sales Week Sales 1 45 6. 53 2 50 7 59 3 44 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, G. 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 11 12 13
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 6 8 4 7 11 7 13 12 10 13 8 This exercise contains only parts b, c, and d. Part 2 b) Using the 3-year moving average, provide the forecast from periods 4 through 12 (round your responses to one decimal place). Part 3 c) Using the 3-year weighted moving average with weights 0.10, 0.30, and 0.60, using 0.60 for the most recent period, provide the forecast from periods 4 through 12 (round your responses to two decimal places). Part 4 d) Mean absolute deviation for the forecast developed…
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 7 9 6 10 12 7 12 12 9 9 8 Part 2 Using exponential smoothing with α = 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). Part 3 Provide the forecast from periods 2 through 12 using the naive approach (enter your responses as whole numbers).
The following table gives the number of pints of type A blood used at Woodlawn Hospital in the past 6 weeks: Week Of August 31 September 7 September 14 September 21 September 28 October 5 - a) The forecasted demand for the week of October 12 using a 3-week moving average = pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.10, 0.30, and 0.60, using 0.60 for the most recent week, the forecasted demand for the week of October 12 = pints (round your response to two decimal places and remember to use the weights in appropriate order the largest weight applies to most recent period and smallest weight applies to oldest period.) Week Of c) If the forecasted demand for the week of August 31 is 360 and a = 0.20, using exponential smoothing, develop the forecast for each of the weeks with the known demand and the forecast for the week of October 12 (round your responses to two decimal places). August 31 September 7 September 14…
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
Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table: 3 8 9 6 7 6 3 7 10 11 Year Year Forecast (000) 1 5 1 5 2 5 4 4 4 5 11 Registrations (000) Use exponential smoothing with a smoothing constant of 0.4 to forecast the registrations at the seminar for years 2 through 12. To begin the procedure, assume that the forecast for year 1 was 5,000 people signing up (round your responses to one decimal place): 2 3 5 6 7 8 10 16 9 11 12 10 D 11 12 a) What is the MAD? Mean absolute deviation based on the forecast developed using the exponential smoothing method (with a smoothing constant (x) = 0.4 and a starting forecast of F₁ = 5) is thousand registrations (round your response to one decimal place). b) What is the MSE? The mean squared error based on the forecast developed using the exponential smoothing method (with a smoothing constant (x) = 0.4 and a starting forecast of F₁ = 5) is (round your response to two decimal…
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
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…

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