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   SIMPLE MOVING AVERAGE Using an averaging period of 3, calculate the simple moving average for weeks 4 through 24.  Calculate the MAD for this forecasting model.

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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. SIMPLE MOVING AVERAGE
  • Using an averaging period of 3, calculate the simple moving average for weeks 4 through 24.  Calculate the MAD for this forecasting model.

 

  1. WEIGHTED MOVING AVERAGE
  • Using an averaging period of 3 with the most recent period weighted .5, the next most recent .4, and the oldest period weighted .1, forecast weeks 4 through 24.  Calculate the MAD for this forecasting model.

 

  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.

 

  1. 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).

 

  1. CONCLUSIONS
  • Show your work in a table like the one below
  • Indicate which model is best/most accurate (based on the lowest MAD).

 

 

 

SMA AP=3

 

WMA

 

ETC

Week

# of Calls

Forecast

Absolute Deviation

 

Forecast

Absolute Deviation

 

 

 

 

1

50

 

 

 

 

 

 

 

 

 

2

35

 

 

 

 

 

 

 

 

 

 

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