The marketing manager of manufactures and distributes farming equipment (such a company that combined harvesters, ploughs and tractors) recorded the number of farming units sold quarterly for the period 2016 to 2019. Quarter 2016 2017 2018 2019 Summer 57 60 65 64 Autumn 51 56 60 62 Winter 50 53 58 58 Spring 56 61 68 70 Using the four period moving average and sequential numbering system starting with -, in period 1. X=1
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DETERMINE
I) the adjusted seasonal indexes ofautumn:
II) the de-seasonalised of period 1:
III) the de-seasonalised of period 16:
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- The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?The following table shows the three-period moving average and five-period moving average for monthly sales of Budget Furniture's during 2019. Moving averages of Budget Furniture's Time period Months Sales Three-period moving average (rounded off to Five-period moving average four decimals) R'millions 1 Jan 7 5.0000 6.2 February 5.6667 6.6 March 5 7.0000 B 4 April 8.3333 8.2 May 7 9.3333 8.4 June 8.3333 9.6 7 July 12 8.6667 9.6 August 4 A 9.2 September 10 10.6667 10 October 13 10.6667 11 November 9 12 December 10 The seasonal index for the month of February in 2019 is: LO1. Favors Distribution Company purchases small imported trinkets in bulk, packages them, and sells them to retail stores. They are conducting an inventory control study of all their items. The following data for the year 2006 are for one such item, which is not seasonal. [10 Points] Month Sales Jan Feb 18 19 Mar Apr May Jun 17 21 20 19 Jul 20 Aug 23 a. Use trend projection to estimate the relationship between time and sales (state the trend line equation in this problem). b. Calculate forecasts for February 2007, April 2007, and February 2008
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- ABC Inc. sells patio sets. Monthly sales for a seven-month period were as follows: Month Sales (000) Unites Feb 19 Mar 18 Apr 15 May 20 Jun 18 Jul 22 Aug 20 Forecast September sales volume using the naive approach.Given a forecast demand and an actual demand for a certain product, calculate the tracking signal and MAD parameter. Year Forecast Demand Actual demand 1 78 71 75 80 3 83 101 84 84 5 88 60 85 73Given the demand data, answer the following questions below. Year Sales 1 - 123 2 - 118 3 - 109 4 - 112 5 -100 6 -110 7 -124 8 - ? What will be the forecast demand in Year 8 using Naïve method?a.) 120b.) 110c.) 115d.) 124
- Year Sales 1) 123 2)118 3) 109 4) 112 5) 100 6) 110 7) 124 8)Determine the demand in Year 8 using a 3-month moving average using the sales table. Use weights of 0.40, 0.30 and 0.30The 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 SALES 1 215 2 240 3 205 4 190 5 160 6 195 7 150 8 140 Use regression and seasonal indexes to forecast quarterly sales for the next year. Note: Do not round intermediate calculations. Round your answers to 1 decimal place.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 =…