a) Using a 3-year moving average, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to onedecimal place):YearForecast4YearForecast5465768b) Using a 3-year weighted moving average in which the registrations in the most recent year are given a weight of 2, and registrations in theother 2 years are each given a weight of 1, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses toone decimal place):7981091110121112 Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table:Year14.0YearForecast26.043 44.0 5.05Registrations (000)This exercise contains only parts a and b.a) Using a 3-year moving average, the forecasted registrations (in thousands) for years 4 through 12 are (round your responses to onedecimal place):6105 6 7 8 910.0 8.0 7.0 9.0 12.0 14.078910111115.012Db) Using a 3-year weighted moving average in which the registrations in the most recent year are given a weight of 2, and registrations in thenther 2 veare are each niven a weight of 1 the forecasted registratione (in thousande) for voare 4 through 12 are fround your roenoncos fo

Forecasting is a technique used to predict future outcomes on the basis of past data. In businesses…

Answered: a) Using a 3-year moving average, 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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Compute the forecast sale using α = 0.20 and α = 0.35 respectively. (Note: express all answers using 4 decimal places)
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9
d) Using exponential smoothing with α = 0.40 and the forecast for year 1 being 3,000, the forecast for year 6 = ? miles (round your response to the nearest whole number).
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.)
In a retail store, the actual sales of a particular product (in thousands of units) over the past few months are as follows: Month Sales 1 16 2 22 3 18 4 20 5 23 Using exponential smoothing method with α (smoothing constant) of 0.75 and the given forecast for month 1 equal to 10, what is the forecast for month 6?
Given the following original forecast and actual data: Month Actual Forecast Jan Feb Mar Apr May Jun Jul 600 475 550 575 688 649 ??? 400 —— 1 ??? Using exponential smoothing with a - = 0.64, what is the forecast for July. Round your answer to 2 decimal places.
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…
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…
Let's say you are playing the stock market and below period 2020 data was provided. For "stock A" you use a 2 month moving average. For "stock B" you use exponential smoothing with (a = 0.3). What is the Forecast in Stock B for January 2021? Stock A Stock B ... Jan 0.11 Jan 14 Feb 0.20 Feb 11 Mar 0.03 Mar Apr May 1.20 Apr May 6. 0.50 9 Jun 0.03 Jun 12 Jul 0.10 Jul 16 Aug 0.11 Aug Sep 14 Sep 0.56 8 Oct 0.78 Oct Nov 0.44 Nov 4 Dec 0.10 Dec
Y9
3)The errors in a particular forecast are as follows: 3, -3, 4, 0, -2. What is the tracking signal for each period of the forecast? (use excel to show formulas )

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