Consider the following data:MonthJan-14Feb-14Profit ($) 16,113 16,263Monthly Profit of an Auto Repair ShopMar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14Sep-1415,05517,117 18,763 17,210 19,141 18,468 20,254Step 3 of 4: Determine the exponential smoothing forecast for the next time period using a smoothing constant of 0.35. If necessary, round your answer to onedecimal place.

It is required to find the exponential smoothing forecast for the next time period, using the…

Answered: Consider the following data: Monthly…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The Agri-Food Company has been in business for five years. Brian, the firm's owner, wants to develop a forecast of olive oil sales for the coming year (i.e., 2025) based on the following historical data: Year 2020 2021 2022 2023 2024 Sales 10 20 40 55 75 1. Forecast sales for 2025 using the 3-year moving average method. 2. Forecast sales for 2025 using the simple exponential smoothing method with a smoothing constant of a=0.6. 3. Forecast sales for 2025 using the simple linear trend method.
Interpret the partial slope of work fulfillment in a sentence.
Find forecasted value for 2017using α = 0.5 and α = 0.7 using exponential smoothing method.Which α is better Years Sales Forecasted sale 2012 25 ……. 2013 17 2014 21 2015 30 2016 27 2017 ?
the table shows the percent of households with internet access for selected years from 2009 and projected through 2015. Year Percent of households 2009 67 2010 70 2011 72.5 2012 75 2013 76.5 2014 77.2 2015 78 Use the model to predict the percent of households with internet access in 2022.
The following table gives the personal savings (in billions of dollars) in the United States for selected years. Year 2005 2010 2011 2012 2013 2014 2015 2016 Personal Savings (billions) $153.8 189.3 187.5 142.0 155.7 152.1 175.6 199.6 5. Find the average rate of change between the years 2010 and 2012. 6. Interpret questions 4 and 5 on the graph. 7. Find the point of inflection of the regression equation and interpret what it means.
A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were Day: Number sold: 2 8. 37 40 45 44 48 49 47 46 50 10 11 12 13 14 15 Day: Number sold: 54 52 53 57 49 53 a. Assume the data refer to demand rather than sales. Using trend-adjusted exponential smoothing with an initial forecast of 42 for Day 8, an initial trend estimate of 2, and a = ß = .3, develop demand forecasts for Days 9 through 16. Then compute the resultant MSE using the error values from Days 8 through 15. (Round your intermediate period-by-period forecast and error values to 3 decimal places. Round your final MSE answer to 3 decimal places.)
Here's a table with average monthly price of a stock from Jan 2021-July 2021. Month Price Jan 29000 Feb 27000 Mar 31000 Apr 30000 May 32000 June 28000 July 29000 Using a 3-period weighted moving average with weights (wt, wt-1, W-2) = (0.6, 0.2, 0.2), the predicted price August is Using an exponential smoothing model with = 0.4, and with the initial predicted price for Jan the same as the observed price for January, the predicted price for August is % Now, let's suppose that we finally observe that the price for August is 30000. The absolute percent error (APE) of your prediction for August is using the weighted moving average method and % using the exponential smoothing model. (Note: Round your answer to the nearest 2 decimal places. For your APE answer for example let's say you get 0.06786 from Excel, then you should type-in 6.79 as your answer here since it is represented as percentage. Do not enter any symbols other than integers and decimal.)
Below is a table containing data on product demand for the most recent five months along with the forecasts that had been made for those 5 previous months. Use the exponential smoothing method to forecast the number of sales to expect next month. Use the following value of alpha: 0.2. Month Demand Forecast 1 308 349.2 2 388 340.9 3 344 350.3 4 400 349.1 5 341 359.3
Describe three approaches to modeling seasonality in a regression forecast.
60% 12:18 PM + MathHW414b.. / Activinspire - Studio Untitied Untitied CLASSFLOW CONNECT DEVICES Page 430 of 1,040 B Which of the following functions has a greater slope and y-intercept? Function 1: Y = 11x - (-13) Function 2: 90 80 70 60 50 40 30 20 10 6. You're using this app in Workspace.

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