months show the 3-month Simple Moving Average Forecast for the 8th Month? Actual Demand Month) (in kg) 455.300 249.422 325,600 114,618 301.243 103,522 ? be determined m 400,000 and 500.000 kg 00.000 kg an 500.000 kg
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- Use the table of values you made in part 4 of the example to find the limiting value of the average rate of change in velocity.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) .Below is a table containing data on product demand for the most recent five months along with the forecasts that had been made for those 5 previous months. Use the exponential smoothing method to forecast the number of sales to expect next month. Use the following value of alpha: 0.2. Month Demand Forecast 1 308 349.2 2 388 340.9 3 344 350.3 4 400 349.1 5 341 359.3
- The table shows the sales revenue from the past 8 quarters. What is the 4-period moving average forecast of the next quarter? Year 1 Year 2 Year 3 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 11 10 9 12 10 7 7 11 ?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 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 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.)The forecast for year 6 using a weighted 2-year moving average with weights of 0.350.35 and 0.650.65 (the weight of 0.650.65 is for the most recent period) is what?The demand and forecast information for the XYZ Company over a twelve-month period has been collected in the Microsoft Excel Online file below. Use the Microsoft Excel Online file below to develop forecast accuracy and answer the following questions. Forecast Accuracy Measures Period Actual Demand Forecast Error Absolute Error Error^2 Abs. % Error 1 1,300 1,378 2 2,000 1,676 3 1,800 1,974 4 1,700 2,272 5 2,300 2,570 6 3,800 2,868 7 3,200 3,166 8 3,100 3,464 9 3,900 3,761 10 4,600 4,059 11 4,200 4,357 12 4,300 4,655 Total Average RSFE MAD MSE MAPE Tracking Signal 1. What can be concluded about the quality of the forecasts? Assume that the control limit for the tracking signal is ±3. The results indicate (bias or no bias) in the…
- John Kittle, an independent insurance agent, uses a five-year moving average to forecast the number of claims made in a single year for one of the large insurance companies he sells for. He has just discovered that a clerk in his employ incorrectly entered the number of claims made four years ago as 1,400 when it should have been 1,200.a. What adjustment should Mr. Kittle make in next year’s forecast to take into account the corrected value of the number of claims four years ago?b. Suppose that Mr. Kittle used simple exponential smoothing with a = .2instead of moving averages to determine his forecast. What adjustment is now required in next year’s forecast? (Note that you do not need to know the value of the forecast for next year in order to solve this problem.)Given the following average demand for each month, calculate the seasonal indicesfor each month.The following table gives the number of pints of type A blood used at Damascus Hospital in the past 6 weeks: Week Of Pints UsedAugust 31 360September 7 389September 14 410September 21 378September 28 368October 5 374 a) The forecasted demand for the week of October 12 using a 3-week moving average = 373.33 pints (round your response to two decimal places). b) Using a 3-week weighted moving average, with weights of 0.15, 0.25, and 0.60, using 0.60 for the most recent week, the forecasted demand for the week of October 12 = ? pints (round your response to two decimal places and remember to use the weights in appropriate order — the largest weight applies to most recent period and smallest weight applies to oldest period.)