forecast solved proplem +case - Confirming Pages 114 Chapter Three KEY TERMS associative model 80 bias 105 centered moving average 95 control chart 103

forecast solved proplem +case - Confirming Pages 114...

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114 Chapter Three Forecastingassociative model, 80 bias, 105 centered moving average, 95 control chart, 103 correlation, 101 cycle, 82 Delphi method, 81 error, 78 exponential smoothing, 87 forecast, 74 irregular variation, 82 judgmental forecasts, 80 least squares line, 98 linear trend equation, 90 mean absolute deviation (MAD), 78 mean absolute percent error (MAPE), 79 mean squared error (MSE), 78 moving average, 84 naive forecast, 82 predictor variables, 98 random variations, 82 regression, 98 seasonal relative, 94 seasonal variations, 93 seasonality, 82 standard error of estimate, 100 time series, 82 time-series forecasts, 80 tracking signal, 105 trend, 82 trend-adjusted exponential smoothing, 92 weighted average, 86 KEY TERMS SOLVED PROBLEMS a. Plot the data to see if there is a pattern. Variations around an average (i.e., no trend or cycles). Therefore, the most recent value of the series becomes the next forecast: 64. b. Use the latest values. MA3555864359c. F.20(55) .30(58) .50(64) 60.4 d. Start with period 2. Use the data in period 1 as the forecast for period 2, and then use exponential smoothing for successive forecasts.PeriodNumber of ComplaintsForecastCalculations160[The previous value of the series is used 26560as the starting forecast.]3556260 .40(65 60) 6245859.262 .40(55 62) 59.256458.7259.2 .40(58 59.2) 58.72660.8358.72 .40(64 58.72) 60.83SolutionStep by step Forecasts based on averages.Given the following data:PeriodNumber of Complaints160265355458564Prepare a forecast for period 6 using each of these approaches:a. The appropriate naive approach. b. A three-period moving average. c. A weighted average using weights of .50 (most recent), .30, and .20. d. Exponential smoothing with a smoothing constant of .40. Problem 1
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Chapter Three Forecasting115You also can obtain the forecasts and a plot using an Excel template, as shown: ecelxecelxProblem 2 Using seasonal relatives.Apple’s Citrus Fruit Farm ships boxed fruit anywhere in the world. Using the following information, a manager wants to forecast shipments for the first four months of next year. MonthSeasonal RelativeMonthSeasonal RelativeJan. 1.2Jul. 0.8Feb. 1.3Aug. 0.6Mar. 1.3Sep. 0.7Apr. 1.1Oct. 1.0May. 0.8Nov. 1.1Jun. 0.7Dec. 1.4The monthly forecast equation being used is:Ftt4023where t0January of lastyear FtForecast of shipments for month tJanFebMar4023 244744023 2547740()()23 264804023 27483()()FAprMonthSeasonal RelativeForecastJan. 1.2474(1.2) 568.8Feb. 1.3477(1.3) 620.1Mar. 1.3480(1.3) 624.0Apr. 1.1483(1.1) 531.3ecelxecelxSolutionSolution
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116 Chapter Three ForecastingLinear trend line.Plot the data on a graph, and verify visually that a linear trend line is appropriate. Develop a linear trend equation for the following data. Then use the equation to predict the next two values of the series.
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