Consider the following time series data.
Month | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
Value | 24 | 13 | 18 | 12 | 18 | 23 | 15 |
b. Develop the three-month moving average forecasts for this time series. Compute MSE and a forecast for month 8
(to 2 decimals if necessary). Enter negative values as negative number.
Month |
Time Series Value | Forecast |
Forecast Error | Squared Forecast Error |
1 | 24 | |||
2 | 13 | |||
3 | 18 | |||
4 | 12 | ? | ? | ? |
5 | 18 | ? | ? | ? |
6 | 23 | ? | ? | ? |
7 | 15 | ? | ? | ? |
Totals | ? |
MSE = [ ? ]
The forecast for month 8 = [ ? ]
c. Use a=.02 to compute the exponential smoothing forecasts for the time series. Compute MSE and a forecast for month 8 (to 2 decimals). Enter negative values as negative number.
Month | Time Series Value | Forecast |
Forecast Error | Squared Forecast Error |
1 | 24 | |||
2 | 13 | ? | ? | ? |
3 | 18 | ? | ? | ? |
4 | 12 | ? | ? | ? |
5 | 18 | ? | ? | ? |
6 | 23 | ? | ? | ? |
7 | 15 | ? | ? | ? |
Totals | ? |
MSE = [ ? ]
The forecast for month 8 = [ ? ]
e. Use a smoothing constant of a=.04 to compute the MSE. (to 2 decimals).
[ ? ]
b)
squared | ||||
month | value | forecast | error | error |
1 | 24 | |||
2 | 13 | |||
3 | 18 | |||
4 | 12 | 18.33 | -6.33 | 40.11 |
5 | 18 | 14.33 | 3.67 | 13.44 |
6 | 23 | 16.00 | 7.00 | 49.00 |
7 | 15 | 17.67 | -2.67 | 7.11 |
total | 109.67 |
MSE= 27.42
forecast =18.67
c)
squared | ||||
month | value | forecast | error | error |
1 | 24 | |||
2 | 13 | 24.00 | -11.00 | 121.00 |
3 | 18 | 21.80 | -3.80 | 14.44 |
4 | 12 | 21.04 | -9.04 | 81.72 |
5 | 18 | 19.23 | -1.23 | 1.52 |
6 | 23 | 18.99 | 4.01 | 16.12 |
7 | 15 | 19.79 | -4.79 | 22.93 |
total | 257.72 |
MSE =42.95
forecast =18.83
e)
MSE =38.56
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