Appendix 1 < Passenger Forecasts> Passenger Forecasts for the New Gate Area at Newark (To be used for facility and manpower planning) Mon Tue Wed Thu Fri Sat Sun 800 600 500 600 700 200 400 Total between 2 PM and 10 PM 700 400 500 700 900 300 700 175 150 150 150 200 100 Description Total between 6 AM and 2 PM Peak hour Traffic 175
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- What are the disadvantages and advantages of moving average technique and simple exponential smoothing?If the forecasted value of the time series variable for one period is 28.5 and the actual value observed for the same period is 32, what is the forecast error for that period? Question 19 options: 3.5 2 -3.5 4Time period Actual sales 1 18 2 22 If the forecasting value of period 3 is 19.6 using exponential smoothing, the smoothing constant is what?
- please answer in excel Jean’s Copiers sells and repairs photocopy machines. The manager needs weekly forecasts of service calls so that she can schedule the personnel. The manager uses α = 0.3 for exponential smoothing, and the forecast for the first week was 24 calls. The manager also uses 3 weekly moving averages technique. a) Using 3 period moving averages, forecast the number of calls for week 7. b) Using exponential smoothing, forecast the number of calls for week 7. c) Compare these two forecasting techniques using Mean Squared Errors (MSE) measure. Which one is better?php?attempt=104149&cmid%330865 aline Services v OS Ticket system My Dispense Academic Calendar N My courses 3) v Q b) Calculate the weighted moving average for periods 7 through 10 using weights of 0.6, 0.3, and 0.1. n Lo S : Cha Weighted moving Period Actual average 1 64 2 84 3 91 4 97 115 6. 135 7. 137 8. 144 6. 153 10 171 beriods 7 through 10. Use 5.Part C Exponential Exponential Gasoline Demand Gasoline Month smoothed forecast smoothed forecast Exponential smoothed forecast (a = 0.25) Demand (a = 0.25) (a = 0.45) Exponential smoothed forecast (a = 0.45) Mar 900 920 920 1200 Apr May 755 915.00 911.00 1100 1000 650 875.00 840.80 g20 915.00 846 80 755 818.75 754.94 904.76 835.12 Jun 550 818.75 754.94 800 320 751.56 66272 645.74 746.83 Jul 625 751.56 662.72 650 600 550 Aug Sep 730 719.92 645.74 820 722.44 683.66 400 D Oct 1100 746.83 745.01 200 1 Nov 835.12 904.76 Mar Apr May Jun Jul Aug Sep Oct Nov 1. Make a comparative analysis out of your answers in the plotted data. (3-5 5 sentences)
- •• 4.31 North Carolina, for the past 24 weeks are shown in the following table: Emergency calls to the 911 system of Durham, WEEK 1 2 3 4 5 6 7 8 9 10 11 12 CALLS 50 35 25 40 45 35 20 30 35 20 15 40 WEEK 13 14 15 16 17 18 19 20 21 22 23 24 CALLS 55 35 25 55 55 40 35 60 75 50 40 65 a) Compute the exponentially smoothed forecast of calls for each week. Assume an initial forecast of 50 calls in the first week, and use a = .2. What is the forecast for week 25? b) Reforecast each period using a = .6. c) Actual calls during week 25 were 85. Which smoothing con- stant provides a superior forecast? Explain and justify the measure of error you used. Px2. Calculate the exponential smoothing forecast for week eight using a=0.2. Week Sales Forecast 1 39 2 44 3 40 4 45 5 38 6 43 7 39 a. 41.63 b. 39.98 c. 40.54 d. 40.03 Instruction: This is consists of one (1) multiple choice question. The question requires deep analysis. Choose the appropriate response for the question. A detailed working out should accompany the responses.Question 3: Jane is trying to forecast demand for her store, using moving average with n=2, Fill in the missing cells with correct values and find average error for first quarter and second quarter of year 2000 E Enroll- Year Quarter ment Forecast Error Abs Error 1997 313 3. 2 285 4 3 312 5. 4 339 6. 1998 1 359 7 320 356 385 6. 10 1999 396 367 11 397 12 423 13 14 2000 1 15 2000 3412M4
- Forecast is calculating estimates of future cycle/s based on data of past cycles -- there is no?Explain how is the moving avarages l approach equivalent to exponential smoothing ?Question 1 ABC Restaurant has made a forecast for last week's operations vs Actual result of the forecast last week. Period Monday Tuesday Actual 112 110 113 120 140 Forecast 115 104 Wednesday 110 Thursday 115 Friday 135 Using this table above, solve for Mean Absolute Deviation (MAD) Note: Round up to the last 2 decimals example 9.6568->9.66