The problem below asks you to compare 4 different forecasting methodologies to determine which forecasting model results in the most accurate forecasts. Accuracy is determined by the lowest mean absolute deviation. Emergency calls to the 911 system of Greenville County for the past 24 weeks are shown below. Accurate forecasts are needed to determine the number of operators needed to staff the station. Week# of Calls150235325440545635720830935102011151240135514351525165517551840193520602175225023402465 1. EXPONENTIAL SMOOTHINGCompute the forecasts using α = .2. Calculate the MAD for weeks 4 through 24 only.Compute the forecasts using α = .6. Calculate the MAD for weeks 4 through 24 only. 2. SIMPLE LINEAR REGRESSIONUse all of the data, weeks 1 - 24, to calculate the regression equation for this data. Use the weeks (1-24) as the independent variable (x) and number of calls as the dependent variable (y). Once you have the equation, forecast weeks 4 through 24 (enter 4, 5, 6, etc. as the x value in the equation). Calculate the MAD for this forecasting model. Comment on the goodness of fit (R2) and significance of the model (F significance) to determine if this forecast model should be included in the consideration of the different approaches. (If the model is not significant, it cannot be considered, however, you must still make the forecasts and calculate the MAD). 3. CONCLUSIONSShow your work in a table like the one belowIndicate which model is best/most accurate (based on the lowest MAD). SMA AP=3 WMA ETCWeek# of CallsForecastAbsolute Deviation ForecastAbsolute Deviation 150 235

1. For α = 0.20 The exponential smoothing average for α = .2 and α = .6 has been carried out using…

Answered: The problem below asks you to compare 4…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The problem below asks you to compare 4 different forecasting methodologies to determine which forecasting model results in the most accurate forecasts. Accuracy is determined by the lowest mean absolute deviation.

Emergency calls to the 911 system of Greenville County for the past 24 weeks are shown below. Accurate forecasts are needed to determine the number of operators needed to staff the station.

Week	# of Calls
1	50
2	35
3	25
4	40
5	45
6	35
7	20
8	30
9	35
10	20
11	15
12	40
13	55
14	35
15	25
16	55
17	55
18	40
19	35
20	60
21	75
22	50
23	40
24	65

1. EXPONENTIAL SMOOTHING

Compute the forecasts using α = .2. Calculate the MAD for weeks 4 through 24 only.
Compute the forecasts using α = .6. Calculate the MAD for weeks 4 through 24 only.

2. SIMPLE LINEAR REGRESSION

Use all of the data, weeks 1 - 24, to calculate the regression equation for this data. Use the weeks (1-24) as the independent variable (x) and number of calls as the dependent variable (y). Once you have the equation, forecast weeks 4 through 24 (enter 4, 5, 6, etc. as the x value in the equation). Calculate the MAD for this forecasting model. Comment on the goodness of fit (R²) and significance of the model (F significance) to determine if this forecast model should be included in the consideration of the different approaches. (If the model is not significant, it cannot be considered, however, you must still make the forecasts and calculate the MAD).

3. CONCLUSIONS