The following table contains the demand from the last 10 months:MONTH ACTUAL DEMAND1267103456789a. Calculate the single exponential smoothing forecast for these data using an a of 30 and an initial forecast (F of 31. (Round youranswers to 2 decimal places)Month50Month314567b. Calculate the exponential smoothing with trend forecast for these data using and of 0:30, a 5 of 0.30, an initial trend forecast (Tof1, and an initial exponentially smoothed forecast (F3 of 30. (Round your answers to 2 decimal places)B9ExponentialSmoothing1031343335FITI373638404041e-2. Which is best?c-1. Calculate the mean absolute deviation (MAD) for the last nine months of forecasts (Round your answers to 2 decimal places)MADSingle exponential smoothing forecastExponential amoothing with trend forecastSingle exponential smoothing forecastO Exponential smoothing with trend forecast

Single exponential smoothing-Ft+1= Ft+α (At-Ft)Here, α = Smoothing Constant = 0.30At = Actual demand…

Answered: The following table contains the demand…

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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Considering the fact that the number of students is relatively constant throughout the academic year, the college's cafeteria is planning for the second semester based of the actual sales the first semester. Month Actual Sales of Fall 2016 Forecast of Spring 2017 September 250 October 300 November 280 December 200 With the given information, can the forecast of November be obtained using a 3-month weighted moving average? Explain you answer.
The demand for a product of a company in each of the last twelve months is shown in the table below; Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Demand 37 40 41 37 45 50 43 47 56 52 55 54 Use the table to compute the following forecast demand for the company; a. Four months simple moving average b. Four months weighted moving average using the weight of 40%, 30% and 20% and 10%respectively.
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Consider the following yearly demand values for a particular product. Year Demand 1 360 389 3 410 4 381 368 374 (a) Produce forecast for year 4,5,6, and 7 by using 3-week moving average. (b) Produce forecast for year 4,5,6, and 7 by using 3-week weighted moving average where weights are as follows; wt–3 = .1, wt-2 = .3, and wt-1 = .6. (c) Produce forecast for year 4,5,6, and 7 by using exponential smoothing with a = .2. Please assume that the forecast for the first year is 360.
A recently introduced product has a positive trend in sales. The product’s sales have increased in each of its first eight weeks on the market. The forecast for week 6 was 1,325 (F6 = 1,325), with A6 = 1,283 and T6 = 42. Using smoothing components α = 0.20 and β = 0.30, develop forecasts for weeks 7 and 8.
Data collected on the yearly demand for 50-pound bags of fertilizer at Wallace Garden Supply are shown in the following table: YEAR DEMAND FOR FERTILIZER (1,000S OF BAGS) 1 4 2 6 3 4 4 5 5 10 6 8 7 7 8 9 9 12 10 14 11 15 a) Develop a 3-year moving average to forecast demand?
6. Consider the following data table. (12 Points) a) Forecast demand using exponential smoothing with an apha of 0.25, and an initial forecast of 128.0 for period 1. b) Calculate the MAD and MSE. Period Real demand 130 138 129 140 3 4 5 133
Here are the actual tabulated demands for an item for a nine-month period (January through September). Your supervisor wants to test two moving average forecasting methods to see which one was better over this period. Month Actual Demand Jan 120 Feb 140 March 160 April 180 May 170 June 190 July 150 August 160 September 170 a. Forecast April through September using a three-month moving average and calculate MAD for the forecasts. b. Forecast May through September using a four-month moving average and calculate MAD for the forecasts.
Use simple exponential smoothing with a=0.6 to forecast chargers sales for February through May. Assume that the forecast for January was 24 chargers. *** Month January Charger Sales 42 February 33 March 28 April 59 May ? a) What will be the forecast for May? b) Calculate the MSE.
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.
The following data shows sales forecast of Axis Dealer for motorbikes. Month Demand 1 650 700 3 810 4 800 5 900 6. 700 7 i. What are the 3-months moving average forecasts for months 4, 5, 6 & 7? ii. What are the 3-month Wt. Moving Average (weights: 0.2, 0.3, 0.5) for months 4, 5, 6 & 7? iii. Calculate an exponential smoothing forecast for the given data with an alpha of 0.1 for months 2, 3, 4, 5, 6 & 7. Assume a forecast of 650 for month 1. Show the formula and working method.

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