1-2. Short Questions in addition to Multiple Choices 1. Given an actual dem

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1-2. Short Questions in addition to Multiple Choices 1. Given an actual dem

Concordia College, St. Paul, US has reference to this Academic Journal, 1-2. Short Questions in addition to Multiple Choices 1. Given an actual demand of 60 in consideration of a period when forecast of 70 was anticipated, in addition to an alpha of 0.3, what would the forecast in consideration of the next period be using simple exponential smoothing? F = (1-0.3)(70)+0.3(60) = 67 2. Suppose you have been asked so that generate a demand forecast in consideration of a product in consideration of year 2012 using an exponential smoothing method. The forecast demand in 2011 was 910. The actual demand in 2011 was 850. Using this data in addition to a smoothing constant of 0.3, which of the following is the demand forecast in consideration of year 2012?A) 850B) 885C) 892D) 925E) 930ÿF = (1-0.3)(910)+0.3(850) = 892 3. Short Questions in addition to Multiple Choices The president of State University wants so that forecast student enrollments in consideration of this academic year based on the following historical data: 5 years ago ; 15,000, 4 years ago ; 16,000, 3 years ago; 18,000, 2 years ago; 20,000, Last year; 21,000. What is the forecast in consideration of this year using exponential smoothing alongside ? = 0.4, if the forecast in consideration of two years ago was 16,000? t 1 2 3 4 5At 15000 16000 18000 20000 21000Ft 16000 17600Forecast in consideration of last yearF5 = (1-?)F4+ ?(A4) F5 = 0.6(16000)+0.4(20000)=17600Forecast in consideration of this yearF6 = (1-?)F5+ ?(A5) F6 = 0.6(17600)+0.4(21000)=18960 Given the following demandSuppose the forecast in consideration of period 2 is equal so that the actual in consideration of period 1. What is your forecast in consideration of period 4 using exponential smoothing in addition to ?=0.5?A) 300B) 400C) 500D) 550E) none of the aboveFt+1 = (1-?)Ft+ ?(At)Ft+1 = (1-0.5)Ft+ 0.5(At)Ft+1 = (1/2) Ft+ (1/2) (At)Ft+1 = (Ft+At)/2F3 = (F2+A2)/2F3 = (300+500)/2= 400F4 = (F3+A3)/2 = (400+600)/2 = 500 4.Short Questions in addition to Multiple Choices

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5-6. Short Questions in addition to Multiple Choices 5. Use exponential smoothing so that forecast this period?s demand if ? = 0.2, previous actual demand was 30, in addition to previous forecast was 35. A) 29B) 31C) 34D) 36E) 37F(t+1) = Ft + ? (At-Ft)6. Exponential smoothing is being used so that forecast demand. The previous forecast of 66 turned out so that be 5 units larger than actual demand. The next forecast is 65. Compute ??65 = 66 + ? (-5)66+565- 55 ? = 1? = 0.2F = (1-0.2)(35)+0.2(30) = 347-8. Short Questions in addition to Multiple Choices 7. For what value of ?, exponential smoothing becomes na?ve method? A) ? =0B) ? =0.25C) ? =0.5D) ? =0.75E) ? =18. For what value of ?, exponential smoothing becomes a straight line? A) ? =0B) ? =0.25C) ? =0.5D) ? =0.75E) ? =1Ft+1 = (1-?)Ft+ ?(At) Ft+1 = (At) Ft+1 = (1-1)Ft+ 1(At) Ft+1 = (1-?)Ft+ ?(At) Ft+1 = Ft Ft+1 = (1-0)Ft+ 0(At) 9-10. Short Questions in addition to Multiple Choices 9. A forecast based on the previous forecast plus a percentage of the forecast error is: A) a naive forecast B) a simple moving average forecastC) a centered moving average forecastD) an exponentially smoothed forecastE) an associative forecastÿ10. In exponential smoothing forecasting, using large values of the smoothing coefficient ? generates forecasts that are more:A) accurateB) responsiveC) randomD) stableE) levelFt+1 = (1-?)Ft+ ?(At) Ft+1 = Ft+ ?(At-Ft ) Ft+1 = (1-?)Ft+ ?(At)

12. It can be mathematically proved that the Age of data in exponential smoothing is 1/? . The larger the ?, the larger the number of periods in the moving average. True or false? Why?11. For what value of ? the forecast in consideration of the next period is equal so that 90% of the actual of this period.A) 0.9B) 0.1C) 0.5D) all of the aboveE) we do not know11-12. Short Questions in addition to Multiple Choices False? = 0.5 ? age of data is 2 periods.? = 0.2 ? age of data is 5 periods.? = 0.1 ? age of data is 10 periods. 13. Given a forecast using a 6 period moving average. What is the average age of data? The last piece (newest piece) of data is only 1 period old.The first piece (oldest piece) of data in a 6 period moving average is 6 periods old.The average age of data is (1+6)/2 = 3.5ÿ14. If the age of data in exponential smoothing is 1/ ?, in consideration of what value of ?, exponential smoothing performs close so that a six period moving average?The age of data in a 6 period moving average is 3.5. The age of data in exponential smoothing is 1/ ?.1/ ? = 3.5? = 1/3.5? = 0.29Short Questions in addition to Multiple Choices Problem 1 Given the following demand dataMonth Feb Mar Apr May Jun Jul AugDemand 19 18 15 20 18 22 20Graph the data.What are your forecasts using 5-period moving average.Forecast in consideration of September using Exponential smoothing. Alpha is 0.2 in addition to forecast in consideration of march was 19.Forecast in consideration of September using Na‹ve methodCompute MAD in consideration of Na‹ve Method in addition to Exponential Smoothing. Which one is preferred? Na‹ve Method in addition to Exponential Smoothing?Forecast in consideration of September using Linear Regression

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(a) Plot the Data ( b) Forecast in consideration of Sep Using 5 Period Moving AverageF8 =MA7= (A7+A6+A5+A4+A3)/5 = (20+22+18+20+15)/5 F8 =MA7= 19 (b) Forecast Using 5 Period Moving Average in consideration of All Periods

(c)Forecast in consideration of Sep Using Exponential Smoothing ? =0.2 in addition to F(Mar) = 19March is period 2 F3 = (1-?)F2 + ? A2 F3 = (0.8)19+ 0.2(18) F3 = 18.8 (c) Forecast in consideration of Sep Using ? =.2 in addition to F(Mar) = 19Using the same formula, we compute F4, F5, F6, F7, in addition to finally F8 which is the demand in consideration of Sep. (d) Forecast in consideration of Sep Using Na‹ve Method F(t +1) =AtF8 =A7F8 = 20Forecast in consideration of all periods using Na‹ve Method

(e) Which Technique ? When comparing several methods, we need so that use the same time horizon in consideration of all methods. We need so that have actual as well as forecasts in consideration of all methods in consideration of all periods of MAD computationsHere we have Actual in consideration of periods 1 so that 7; that is 7 periods.Regression can provide us alongside forecast in consideration of periods 1 so that ?Five period moving average can only provide forecast in consideration of periods 6 in addition to 7; that is 2 periodsTherefore, so that compare all these methods, we can compute MAD only over 2 periods. But two period is not enough.Na‹ve Method or Exponential Smoothing ? Na‹ve method forecasts in consideration of periods 2 so that 7; That is 6 periodsExponential Smoothing in consideration of periods 2 so that 7; That is 6 periodsWe can compare NM in addition to ES over 6 periods. (e) Na‹ve Method or Exponential Smoothing ? BetterHowever, we need so that keep all methods, because we need more actual data. A MAD computed just 6 periods is not a reliable measure.It is better so that have all methods in consideration of say 10-20 more periods, in addition to then identify the best method

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