The table below shows the quarterly sales of television set (in thousands) in an electrical appliance shop inyears 2017-2019.YearQuarter 1Quarter 2Quarter 3Quarter 420174.84.16.06.520185.85.26.87.420196.5.67,57.8(a) Describe the trend and seasonal variation of the sales of television setby referring to the following timeseries plot. (In a short paragraph of around 30 words.)Sales of Television Set (1000s)23589101112Time: (2017 Quarter 1 to 2019 Quarter 4)(b) Calculate the seasonal variation for Quarter 1, Quarter 2, Quarter 3, and Quarter 4 respectively by usingthe calculated 4-quarter moving average as below.YearQuarterSalesCentered Moving(1000)Average (1000)20175.475201746.55.7375201815.85.975201825.26.1875201836.86.32520187.46.42019166.5375201925.66.675TTTT"

Seasonal variation will be variation in a period series inside one year that is rehashed pretty much…

Answered: The table below shows the quarterly…

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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A large cement manufacturer uses exponential smoothing to forecast demand for a piece of pollution-control equipment. It appears that an increasing trend is present.Month At1 700 2 685 3 648 4 717 5 713 6 728 7 754 8 762 If the initial forecast for month 1 was 650 units and the trend over that period was 0 units, calculate FIT for the 9-month period. Use smoothing constants, Alpha = 0.1 andAlpha = 0.2.
The marketing manager of a company that manufactures and distributes farming equipment (such as combined harvesters, ploughs and tractors) recorded the number of farming units sold quarterly for the period 2016 to 2019. Using the four period moving average and sequential numbering system starting with x=1 in period 1. determine the following : a) centered moving average of period 5 b) centered moving average of period 10 c) seasonal ratio of period 7 d) seasonal ratio of period 14
The accompanying dataset provides data on the monthly usage of natural gas (in millions of cubic feet) for a certain region over two years. Implement the Holt-Winters multiplicative seasonality model with no trend to find the forecast for periods 13-26, where x = 0.5 and y = 0.8. Then find the MAD for periods 13-24. Click the icon to view the monthly use of natural gas data. Use the Holt-Winters multiplicative seasonality model with no trend to find the forecast for periods 13-18, periods 19-24, and then for periods 25 and 26. (Type integers or decimals rounded to two decimal places as needed.) Forecast Period 13 14 15 16 17 18 Natural Gas Usage Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Period Gas Usage 1 2 8699 A WI 3 4 5 7 9 10 11 12 13 14 1516718192021 22 23 24 241 221 155 137 54 34 29 27 30 40 90 201 229 238 242 136 34 34 28 26 27 40 86 187
Find the five-month moving average of the sales of soaps for this year.
In a retail store, the actual sales of a particular product (in thousands of units) over the past few months are as follows: Month Sales 1 16 2 22 3 18 4 20 5 23 Using exponential smoothing method with α (smoothing constant) of 0.75 and the given forecast for month 1 equal to 10, what is the forecast for month 6?
You have the data on the application during the 8 consecutive year period below Wanted / Find the forecast demand for the year 2008 using the simple moving average method and on a 4-period basis the years 2000 2001 2002 2003 2004 2005 2006 2007 2008 Order quantity 24 48 50 68 60 66 70 90
A newly operated company producing household items would want to forecast its sales volume for the next month. It has been in operation for ten (10) months now. For the past ten (10) months, forecast and sales data for its top selling Item A are as follow: Time Period Forecasted Value Actual Sales (Quantity) 10th month 405 345 9th month 400 380 8th month 410 400 7th month 370 375 6th month 330 360 5th month 320 325 4th month 320 315 3rd month 305 300 2nd month 290 295 1st month 300 280 The operations manager observes the fluctuations on the sales quantity over the 10-month period that the company is in operation. To forecast for the 11th month, the team decided to evaluate options on what forecasting method to use. Their options are: To use the Moving Average Method using the sales data for the past 10 months, To use the Exponential Smoothing Average assigning a smoothing constant of .6 and To use the Trend-adjusted Exponential Smoothing assigning smoothing constants α =…
The following table shows the past two years of quarterly sales information. Assume that there are both trend and seasonal factors and that the seasonal cycle is one year. QUARTER 1 2 5678AWN 3 4 8 SALES 219 237 208 171 169 Quarter 9 10 11 12 192 157 132 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to the nearest whole number. Forecast
please answer in 30 minutes.
Based on the information in the following table, use the Exponential Smoothing Approach (a = 0.3) to forecast the demand for periods 4-13 %3D PERIOD MONTH Demand Forecast 1 Jan 222 Feb 192 222 3 Mar 212 213 Apr 202 May 220 Jun 200 7 Jul 113 Aug 175 6. Sep 277 10 Oct 211 11 Nov 249 12 Dec 144 13 Jan 6o 00
Apply the 3-years moving average method to forecast the required demand for the year 2021 from the following historical data. Years 2012 2013 2014 2015 2016 2017 2018 2019 2020 Demand 245 325 300 350 295 400 450 380 500
Following data on the demand for sewing machines manufactured by Taylor and Son Co. have been compiled for the past 10 years. Year 1971 1972 1973 1974 1975 78 1976 1977 1978 1979 99 1980 106 Demand 58 65 73 76 87 88 93 in (1000 units) Please estimate the value of demand for next 3 years using trend analysis.

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