Considering the aggregated demand for coffee beans for the following months shown below, what would be the 3-month Simple Moving Average Forecast for the 8th Month? Actual Demand (in Period (Month) kg) 1 455,300 2 249,422 325,600 114,618 301,243 103,522 ? 4 3 4 5 6 7 O More than 500,000 kg O Cannot be determined O between 400,000 and 500,000 kg O Below 300,000 kg
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- 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) .Metropolitan Hospital has estimated its average monthly bed needs, N, as: N=460+9X�=460+9� where X = time period (months); (January 2002 = 0) Assume that no new hospital additions are expected in the area in the foreseeable future. The following monthly seasonal adjustment factors have been estimated, using data from the past five years: Forecast Metropolitan's bed demand for January, April, July, November, and December 2007. Month Adjustment Factor (%) Forecast January +5 April -15 July +4 November -5 December -25 Suppose the following actual and forecast values for June bed demands have been recorded. Year Forecast Actual 2007 1,045 1,139 2006 937 974 2005 829 895 2004 721 743 2003 613 656 2002 505 515 What seasonal adjustment factor would you recommend be used in making future June forecasts? 2.1% 5.5% 1.3%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.)
- Price information for selected foods for 2010 and 2018 is given in the table. Price Quantity Item 2010 2018 2010 2018 Cabbage (pound) $ 0.06 $ 0.05 2,000 1,500 Carrots (bunch) 0.10 0.12 200 200 Peas (quart) 0.20 0.18 400 500 Endive (bunch) 0.15 0.15 100 200 Compute a simple price index for each of the four items. Use 2010 as the base period. (Round your answers to 2 decimal places.)Given the following demand for ten-period time frame as shown in the table below. Compute the three-period and five-period moving average forecasts. Plot the actual demand and the forecasts on the same graph. Period 1 2 3 4 5 6 7 8 9 10 Demand (in units) 24 25 28 32 35 38 41 46 49 53 Forecast Table: Period Actual 3-Moving Averages 5-Moving Averages 1 24 2 25 3 28 4 32 5 35 6 38 7 41 8 46 9 49 10 53 11Given the following data and seasonal index: Month Sales Year 1 Year 2 Jan 8 8 Feb 7 9 Mar 5 6 Apr 10 11 May 9 12 June 12 16 July 15 20 Aug 20 25 Sept 4 4 Oct 3 2 Nov 8 7 Dec 9 9 (a) Compute the seasonal index using only year 1 data. (b) Determine the deseasonalized demand values using year 2 data and year 1's seasonal indices.
- The accompanying dataset provides data on monthly unemployment rates for a certain region over four years. Compare 3- and 12-month moving average forecasts using the MAD criterion. Which of the two models yields better results? Explain. Find the MAD for the 3-month moving average forecast. MAD=? (Type an integer or decimal rounded to three decimal places as needed.) Year Month Rate(%) 2010 Jan 7.8 2010 Feb 8.2 2010 Mar 8.8 2010 Apr 9.1 2010 May 9.5 2010 Jun 9.3 2010 Jul 9.7 2010 Aug 9.6 2010 Sep 9.8 2010 Oct 10.1 2010 Nov 9.7 2010 Dec 9.8 2011 Jan 9.7 2011 Feb 9.9 2011 Mar 9.8 2011 Apr 9.9 2011 May 9.7 2011 Jun 9.4 2011 Jul 9.4 2011 Aug 9.3 2011 Sep 9.7 2011 Oct 9.3 2011 Nov 9.9 2011 Dec 9.5 2012 Jan 9.3 2012 Feb 8.8 2012 Mar 8.7 2012 Apr 9.1 2012 May 9.2 2012 Jun 9.2 2012 Jul 9.1 2012 Aug 9.1 2012 Sep 9.1 2012 Oct 8.9 2012 Nov 8.4 2012 Dec 8.3 2013 Jan 8.4 2013 Feb 8.1 2013 Mar 8.4 2013 Apr…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) 1,083,816A shop is planning an order for a popular Christmas festive season product. Demand for the product usually starts from first week of December till first week of January and reduces sharply thereafter. For this reason, and to stimulate sales for leftovers, the product is sold at a significantly reduced price from the second week of January to the fourth week of January. Any leftover after the fourth week of January goes waste. The table below gives past data on total demand for the period from first week of December to first week of January, and from second week of January to fourth week of January, together with their respective chances of occurrence. The product can be purchased at a wholesale price of GHS60 per unit for a pack containing 600 products, GHS57 per unit for a pack containing 800 products, and GHS52 per unit for a pack containing 1000 products. The shop plans to sell the product for GHS80 per unit from first week of December to first week of January, and at a reduced…
- A shop is planning an order for a popular Christmas festive season product. Demand for the product usually starts from first week of December till first week of January and reduces sharply thereafter. For this reason, and to stimulate sales for leftovers, the product is sold at a significantly reduced price from the second week of January to the fourth week of January. Any leftover after the fourth week of January goes waste. The table below gives past data on total demand for the period from first week of December to first week of January, and from second week of January to fourth week of January, together with their respective chances of occurrence. The product can be purchased at a wholesale price of GHS60 per unit for a pack containing 600 products, GHS57 per unit for a pack containing 800 products, and GHS52 per unit for a pack containing 1000 products. The shop plans to sell the product for GHS80 per unit from first week of December to first week of January, and at a reduced…A shop is planning an order for a popular Christmas festive season product. Demand for the product usually starts from first week of December till first week of January and reduces sharply thereafter. For this reason, and to stimulate sales for leftovers, the product is sold at a significantly reduced price from the second week of January to the fourth week of January. Any leftover after the fourth week of January goes waste. The table below gives past data on total demand for the period from first week of December to first week of January, and from second week of January to fourth week of January, together with their respective chances of occurrence. The product can be purchased at a wholesale price of GHS60 per unit for a pack containing 600 products, GHS57 per unit for a pack containing 800 products, and GHS52 per unit for a pack containing 1000 products. The shop plans to sell the product for GHS80 per unit from first week of December to first week of January, and at a reduced…The prices and the numbers of various items produced by a small machine and stamping plant are reported below. Use 2010 as the base. 2010 2018 Item Price (in $) Quantity Price (in $) Quantity Washer 0.07 17,000 0.10 20,000 Cotter pin 0.04 125,000 0.03 130,000 Stove bolt 0.15 40,000 0.15 42,000 Hex nut 0.08 62,000 0.10 65,000 a. Determine the Laspeyres price index. (Round your answer to 2 decimal places.) b. Determine the Paasche price index. (Round your answer to 2 decimal places.)