3. The following tabulations are actual sales of units for 6 months and a starting forecast in January.a. Calculate forecasts for the remaining 5 months using simple exponential smoothing with a = 0.2.b. Calculate MAD for the forecasts.JanuaryFebruaryMarchAprilMayJuneActual10094106806894Forecast80

Answered: The following tabulations are actual…

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter2: Introduction To Spreadsheet Modeling

Section: Chapter Questions

Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...

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4. What is the difference between trend and seasonality in time series data? 5. Here are the errors associated with a particular forecast over the past 5 months, in chronological order: 5, 10, -15, 0, 8. In which month was the forecast perfectly accurate? In which month was the forecast the least accurate? In which month or months was the forecast too high? (Noteshaper Ramp Up # 23) 6. Tutoring Center needs to allocate tutors this week for office appointments, so it needs to forecast the number of students who will seek appointments. The director has gathered the following time series data recently: Time Period Code Student Appointments Jan 6 - 10 95 Jan 13 - 17 80 Jan 20 - 24 65 Jan 27 – 31 4 50 a) What is the naïve forecast for the number of student appointments for Time Period 5 (Feb 3– 7)? b) What is the 2 week moving average for Time Period 5? c) What is the 3 week moving average for Time Period 5? d) What is the forecast for Time Period 5 using exponential smoothing with alpha =…
A forecast for the first six months of the year revealed a tendency to underpredict the actual demand for the revitalized Hubig’s Pies plant in the Marigny. Month Actual Forecast January 675 600 February 720 700 March 640 620 April 510 495 May 480 410 June 565 535 What is the mean squared error of this forecast? a. 1,694 b. 1,873 c. 2,075 d. 1,469
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8.6 Using exponential smoothing, calculate the forecasts for months 2, 3, 4, 5, and 6. The smoothing constant is 0.2, and the old forecast for month 1 is 245. Month 1 2 3 4 5 6 LO Actual Demand 260 230 225 245 250 Forecast Demand
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6. Consider the following data table. (12 Points) a) Forecast demand using exponential smoothing with an apha of 0.25, and an initial forecast of 128.0 for period 1. b) Calculate the MAD and MSE. Period Real demand 130 138 129 140 3 4 5 133
Use simple exponential smoothing with a=0.6 to forecast chargers sales for February through May. Assume that the forecast for January was 24 chargers. *** Month January Charger Sales 42 February 33 March 28 April 59 May ? a) What will be the forecast for May? b) Calculate the MSE.
Amazon finds that sales in July are much greater relative to other months because of the Amazon Prime days in that month. Assuming that an exponential smoothing model is used for forecasting sales, what should the company best do to make the forecast for the next month (Aug) more reflective of reality? Please pick from the provided options. F t+1 = αDt + (1-α) Ft increase value of alpha decrease value of alpha stay with the same alpha decrease the expected forecast for the current month (Ft) On hearing our forecast, our clients probe - how sure are we about the forecast? Which measure of errror (among those stated below) should we best use to respond? a. Root MSE (RMSE) b. Mean absolute percentage error (MAPE) c. Mean forecast error (Avg. error) d. Cumulative forecast error (CFE)
Given the following historical data, what is the simple three-period moving average forecast for period 6? Period 1 2 3 4 5 67.67 68.2 67.3 68.4 Value 73 66 64 73 66
Respond to each of the items using the following time series data. Period Demand 144 2 172 3 157 4 160 144 181 7 160 8 176 9. 149 10 183 11 182 12 149 13 153 14 164 15 153 16 104 Click here for the Excel Data File b. Compute all possible forecasts using a five-period moving average. (Round your answers to 1 decimal place.) Absolute Period Demand 5-period SMA Errors 1 144 172 3 157 4. 160 5 144 181 7 160 8 176 9 149 10 183 11 182 12 149 13 153 14 164 LO
January February March April May June a. Calculate forecasts for the remaining five months using simple exponential smoothing with a = 0.4. February March April May June ACTUAL FORECAST 100 85 96 103 82 66 90 MAD Forecasts 91 93 97 91 81 b. Calculate the MAD for all the forecasts, including January's. (Round your answer to 1 decimal place.)
Given the following original forecast and actual data: Month Actual Forecast Jan Feb Mar Apr May Jun Jul 600 475 550 575 688 649 ??? 400 —— 1 ??? Using exponential smoothing with a - = 0.64, what is the forecast for July. Round your answer to 2 decimal places.

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