The following are historical demand data: ACTUAL YEAR SEASON DEMAND 2 years ago Spring 205 Summer 140 Fall 375 Winter 575 last year Spring 475 Summer 275 Fall 685 Winter 965 Use regression analysis and seasonal indexes to forecast this summer's demand. (Do not round intermediate calculations. Round your answer to the nearest whole number.) Forecast for this summer's demand

The following are historical demand data: ACTUAL YEAR SEASON DEMAND 2 years ago Spring 205 Summer 140 Fall 375 Winter 575 last year Spring 475 Summer 275 Fall 685 Winter 965 Use regression analysis and seasonal indexes to forecast this summer's demand. (Do not round intermediate calculations. Round your answer to the nearest whole number.) Forecast for this summer's demand

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 following are historical demand data: YEAR SEASON ACTUALDEMAND 2 years ago Spring 205 Summer 151 Fall 379 Winter 560 last year Spring 481 Summer 268 Fall 679 Winter 959 Use regression analysis on deseasonalized demand to forecast next summer’s demand. (Round your answer to the nearest whole number.)
The following are historical demand data: YEAR SEASON ACTUAL DEMAND 2 years ago Spring 205 Summer 140 Fall 375 Winter 575 last year Spring 475 Summer 275 Fall 685 Winter 965 Use regression analysis and seasonal indexes to forecast this summer’s demand. Note: Do not round intermediate calculations. Round your answer to the nearest whole number.
Apply the 3-years moving average method to forecast the required demand for the year 2021from the following historical data.Years 2012 2013 2014 2015 2016 2017 2018 2019 2020Demand 245 325 300 350 295 400 450 380 500
Consider the following data:Monthly Profit of a Gym: Month & Profit: Jan-12: 5700 Feb-12: 5453 March-12: 5034 April-12: 4717 May-12: 5185 June-12: 5638 July-12: 6519 Aug-12: 6182 Sept-12: 5913 What are the MAD, MSE and MAPE scores for the three-period weighted moving average forecast? Round any intermediate calculations, if necessary, to no less than six decimal places, and round your final answer to one decimal place. MAD: MSE: MAPE as %: link to excel sheet for forumla to assist: http://www.livebinders.com/play/play?id=2368073
A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were Day: 1 2 3 4 5 6 7 8 9 Number sold: 34 37 40 39 45 43 47 49 48 Day: 10 11 12 13 14 15 Number sold: 52 53 47 53 47 49 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 α = β = .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.) MSE
The sales records of a major auto manufacturer over the past years from 2005 to 2019 are shown below. Number of Cars Sold Year (In thousands of Units) 2005 195 2006 200 2007 250 2008 270 2009 320 2010 380 2011 440 2012 460 2013 500 2014 500 2015 550 2016 570 2017 600 2018 650 2019 700 Develop moving average with k=4 and compute its MSE Develop exponential model with α = 0.4 and compute its MSE Develop a linear trend model and compute its MSE Based on the MSE computed fore ach model , which model fits well to the data Based on the answer of question (4) forecast the number of cars sold for year 2020.
The customer demand for a particular smart phone during Year 0 to Year 5 is given as 1,056,000, 1,032,000, 1,093,000, 1,024,000, 1,066,000, and 1,072,000. Using the Holt forecasting model with trend, what is the forecasted demand in year 10, where w = 0.4 and v = 0.5?a) 1,071,874b) 1,075,573c) 1,077,488d) 1,083,816
The problem is based on the following data given. Observations of the demand for a certain part stocked at a parts supply depot during the calendar year 2013 were ( as shown ). Using a four-month moving average, determine the two-step-ahead forecast for July through December 2013. (Hint: The two-step-ahead forecast for July is based on the observed demands in February through May.)
Movieflix, an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs.Year 2013 2014 2015 2016 2017 2018 2019 2020 2021Membership (000s)17 16 16 21 20 20 23 25 24 (i) Use the following time series data, to develop a regression equation relating memberships to time.
The Badrutt’s Palace Hotel St. Moritz which is one of the best Alpine hotels in Switzerland has provided you with their quarterly bookings data over the last 6 years as follows: Year Quarter-1 (Demand in units) Quarter-2 (Demand in units) Quarter-3 (Demand in units) Quarter-4 (Demand in units) 2018 45,000 22,000 64,000 33,000 2019 48,000 27,000 74,000 41,000 2020 52,000 32,000 83,000 46,000 2021 57,000 35,000 94,000 52,000 2022 61,000 42,000 104,000 56,000 2023 67,000 49,000 120,000 61,000 Required: i) Calculate the seasonal indices for each season using multiplicative index ii) Forecast the demand for each season of the year 2024 given that the annual demand forecast is 324,000 units. iii) Deseasonalize the actual demand data (2018-2023) above using the seasonal indices obtained in (a) above. iv) Generate OLS equation using the Deseasonalized data in (iii) above (in thousand units)
Table 1 HPF Demand in the last 12 periods Period Month Demand in '000 Period Month Demand in '000 1 January 37 7 July 43 2 February 40 8 August 47 3 March 41 9 September 56 4 April 37 10 October 52 5 May 45 11 November 55 6 June 50 12 December 54 The manager of the company wants to be certain enough OFC01 are available to complete orders promptly and they have adequate inventory in stock. During the last meeting, a number of forecast techniques have been discussed: Simple moving average n = 4 Weighted moving average with n=4 with the following weights from most recent periods: 0.4, 0.3, 0.2, 0.1 Exponential Smoothing with alpha = 0.2 Linear trend The manager would like to ascertain the best tools that he and his team can effectively manage the production processes. Among the above forecasting methods, which method should be used to forecast the demand for this product? Why? The…
Given the following data for demand at the XYZ Company, calculate the monthly forecast for 2003 using a 3-month moving average. Calculate the Forecast, Error, MAD (mean absolute percentage error), Bias and the TS (tracking signal) .