Additional Algo TAESActual demand for the past 16 periods is shown below. Prepare a trend adjusted exponential smoothing forecast using the followingparameters: a = 3, 3-1, TAF5-755.00, and T5-200. (Round all your answers to two decimal points.)Penod12345678910111213141151617HIActual748750751754752755761767768760771774778780784791TAF단5

Given parameters: α = 0.3β = 0.1TAF5 = 755T5 = 2.00

Answered: Additional Algo TAES Actual demand for…

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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Q3. Find forecasted value for 2017 using a = 0.5 and a = 0.7 using exponential smoothing method. Which a is better (10 Years Sales Forecasted sale 2012 25 2013 17 2014 2015 30 2016 27 2017 21
Rosa's Italian restaurant wants to develop forecasts of daily demand for the next week. The restaurant is closed on Mondays and experiences a seasonal pattern for the other six days of the week. Mario, the manager, has collected information on the number of customers served each day for the past two weeks. If Mario expects total demand for next week to be around 336, what is the forecast for each day of nvext week? (Round intermediate colculations to 4 decimal places, eg. 1.2645 and final answers to 1 decimal place, es 15.2) Number of custooers Day Week 1 Week 2 Tuesdav 45 47 Wednesday 34 28 Thursday 44 31 Friday 92 107 Saturday 104 94 Sunday 55 79 Forecast Day Tuesday
Sales of Bluetooth Headphones at the Abdulla Electronics Enterprises in Model Town, India, over the past 4 months have been 100, 110, 120, and 130 units (with 130 being the most recent sales). Develop a moving-average forecast for next month, using following techniques: a) 3-month moving average. b) 4-month moving average. c) Weighted 4-month moving average with the most recent month weighted 4, the preceding month 3, then 2, and the oldest month weighted 1. d) If next month’s sales turn out to be 140 units, forecast the following month’s sales (months) using a 4-month moving average.
Asvnch Problem - Statistical Forecasting Data Set – Eunice BC Fashion Monthly Sales, in million units. Year Total Sales Year Total Sales 2010 38 2016 43 2011 41 2017 40 2012 40 2018 45 2013 45 2019 47 2014 50 2020 42 2015 42 2021 48 Questions: a. Find the naïve forecast. b. Use the 3 years moving average forecast. c. Have a 5 years weighted moving average. d. Develop forecast using exponential smoothing with a = 0.2. e. Determine the trend line equation and present the forecast. f. Find the best forecast for year 2022. Note: Use the first 5 years as the training samples and the last 5 years as the forecasting samples. Solve it in Excel Sheet/Sheet with Equations as possible.
please answer in excel Jean’s Copiers sells and repairs photocopy machines. The manager needs weekly forecasts of service calls so that she can schedule the personnel. The manager uses α = 0.3 for exponential smoothing, and the forecast for the first week was 24 calls. The manager also uses 3 weekly moving averages technique. a) Using 3 period moving averages, forecast the number of calls for week 7. b) Using exponential smoothing, forecast the number of calls for week 7. c) Compare these two forecasting techniques using Mean Squared Errors (MSE) measure. Which one is better?
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Given the actual demand of 300, the previous forecast of 300, and an alpha of 0.048 , which one of the following is closest to the forecast for the next period be using simple exponential smoothing? Select one: a. 330 b. 300 c. 420 d. 150
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…
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Assume today's date is 12/31/2023. Actual sales and forecast for 2023 are given below. Actual Forecast 2023 72.4 66.9 59.5 61.2 260 2023 69 67 Q3 61 Q4 59 Total 256 Obtain the MAD Q1 Q2 7.2 1.8 -1
Problem 5 You are trying to determine what forecast method to use. Based upon the following historical data, calculate the following forecast and specify what procedure you would utilize. MAY JUNE MONTH JANUARY FEBRUARY MARCH APRIL DEMAND 62 65 67 68 71 73 MONTH JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER DEMAND 76 78 78 80 84 85 a. Calculate the simple three-month moving average for periods 4 to 12. b. Calculate the weighted three-month moving average for periods 4 to 12. Use weights of 0.50, 0.30, and 0.20 for the most recent, second most recent, and third most recent periods, respectively. c. Calculate the single exponential smoothing forecast for periods 2 to 12 using an initial forecast (F₁) of 61 and a of 0.30. d. Calculate the exponential smoothing with trend component forecast for periods 2 to 12 using an initial trend forecast (T₁) of 1.8, and initial exponential smoothing forecast (F₁) of 60, an a of 0.30 and ō of 0.30. e. Calculate the MAD for the forecasts made by each…
Passenger miles flown on Northeast Airlines, a commuter firm serving the Boston hub, are shown for the past 12 weeks: 2 3 21 19 Week 1 Actual Passenger Miles (in thousands) 17 Week Forecasted Passenger Miles (in thousands) a) Assuming an initial forecast for week 1 of 17,000 miles, use exponential smoothing to compute miles for weeks 2 through 12. Use α = 0.2 (round your responses to two decimal places). 10 11 4 5 6 7 8 9 23 18 16 20 18 22 20 15 2 1 3 4 6 7 17.00 17.00 17.80 18.04 19.03 18.83 18.26 5 8 18.61 9 18.49 19.19 10 12 22 11 12

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