The following are historical demand data: YEAR SEASON ACTUAL DEMAND 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 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.)

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.1: Logistic Functions

Problem 16E: Cable TV The following table shows the number C. in millions, of basic subscribers to cable TV in...

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Cable TV The following table shows the number C. in millions, of basic subscribers to cable TV in the indicated year These data are from the Statistical Abstract of the United States. Year 1975 1980 1985 1990 1995 2000 C 9.8 17.5 35.4 50.5 60.6 60.6 a. Use regression to find a logistic model for these data. b. By what annual percentage would you expect the number of cable subscribers to grow in the absence of limiting factors? c. The estimated number of subscribers in 2005 was 65.3million. What light does this shed on the model you found in part a?
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.
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
Consider the following data:Monthly Profit of an Auto Repair Shop Month Jan-14 Feb-14 Mar-14 Apr-14 May-14 Jun-14 Jul-14 Aug-14 Sep-14 Profit ($) 17,527 17,677 16,455 18,642 20,163 17,350 19,127 18,622 20,422 Step 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 one decimal place. I have been stuck on this for 2 days now. I do not understand exponential smoothing forecast at all and the textbook is not helpful. I have tried looking at the textbook, using the step-by-step learning tools, and youtube videos and it still isn't helping.
Monthly sales for a six month period are as follows: Month Sales Jan 18,000 Feb 22,000 Mar 16,000 Apr 18,000 May 20,000 June 24,000 Compute the sales forecast for July using the following approaches: (1) Four-month moving average; (2) Weighted three-month moving average using .50 for June, .30 for May and .20 for April; (3) Exponential smoothing with α (smoothing constant) equal to .40, assuming a February forecast of 18,000
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 demand for electric power supplied by Eskom over the period 2003 to 2009 is shown in the table below in megawatts. Nike wants you to forecast demand for 2010 by using the simple linear regression method and also draw a graph Year Time Demand 2003 1 74 2004 2 79 2005 3 80 2006 4 90 2007 5 105 2008 6 142 2009 7 122
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.
A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were: DAY 1 - 37 2 - 40 3 - 45 4 - 44 5 - 48 6 - 49 7 - 47 8 - 46 9 - 50 10 - 54 11 - 52 12 - 53 13 - 57 14 - 49 15 - 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 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.) This question was previously answered with 16.787. The McGraw-Hill website where you enter this answer says it's not correct. Can you please assist me??
For the Hawkins Company, the monthly percentages of all shipments received on time over the past 12 months are 80, 82, 84, 83, 83, 84, 85, 84, 82, 83, 84, and 83. a. Compute for a 3 month moving average forecast. b. Compute for the exponential smoothing forecast for a=0.2. c. Which provides the better forecast using MSE as the measure of model accuracy? d. What is the forecast for next month?
The table shows the national expenditures for health care in billions, in a country for the selected years from 1990 to 2020. Given the projection cost for the year 2002, identify the type of regression point. Year Exprenditures ($billions) 1991 1020 1994 1356 1998 1984 2004 2984 2009 3374 2016 4765 2020 5937 Interpolation Extrapolation Neither Both