In: Statistics and Probability
Consider the following time series data.
| Week | 1 | 2 | 3 | 4 | 5 | 6 | 
|---|---|---|---|---|---|---|
| Value | 17 | 12 | 14 | 10 | 16 | 13 | 
(a) Construct a time series plot.
(b)Develop the three-week moving average forecasts for this time series. (Round your answers to two decimal places.)
| Week | Time Series Value  | 
Forecast | 
|---|---|---|
| 1 | 17 | |
| 2 | 12 | |
| 3 | 14 | |
| 4 | 10 | |
| 5 | 16 | |
| 6 | 13 | 
Compute MSE. (Round your answer to two decimal places.)
MSE =
What is the forecast for week 7?
(c) Use α = 0.2 to compute the exponential smoothing forecasts for the time series.
| Week | Time Series Value  | 
Forecast | 
|---|---|---|
| 1 | 17 | |
| 2 | 12 | |
| 3 | 14 | |
| 4 | 10 | |
| 5 | 16 | |
| 6 | 13 | 
Compute MSE. (Round your answer to two decimal places.)
MSE =
What is the forecast for week 7? (Round your answer to two decimal places.)
(d) Compare the three-week moving average approach with the exponential smoothing approach using α = 0.2.
Which appears to provide more accurate forecasts based on MSE? Explain.
The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach.
The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach.
The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller MSE than the three-week moving average approach.
The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach.
(e) Use a smoothing constant of α = 0.4 to compute the exponential smoothing forecasts.
| Week | Time Series Value  | 
Forecast | 
|---|---|---|
| 1 | 17 | |
| 2 | 12 | |
| 3 | 14 | |
| 4 | 10 | |
| 5 | 16 | |
| 6 | 13 | 
a)]

b)
| Time period | Actual Value(A) | Moving avg. Forecast(F) | Forecast error E=|A-F| | Squared Forecast Error | MAPE | 
| 1 | 17 | ||||
| 2 | 12 | ||||
| 3 | 14 | ||||
| 4 | 10 | 14.33 | 4.33 | 18.78 | 0.4333 | 
| 5 | 16 | 12.00 | 4.00 | 16.00 | 0.2500 | 
| 6 | 13 | 13.33 | 0.33 | 0.11 | 0.0256 | 
| Total | 8.67 | 34.89 | 0.2756 | ||
| Average | 2.89 | 11.63 | 13.78% | ||
| MAD | MSE | MAPE | |||
| MSE = | 11.63 | ||||
| forecast for week 7 = | 13.00 | ||||
c)
| for exponential smoothing: next period forecast =α*last period actual+(1-α)*last period forecast | 
| Time period | Actual Value(A) | Forecast(F) | 
| 1 | 17 | |
| 2 | 12 | 17.00 | 
| 3 | 14 | 16.00 | 
| 4 | 10 | 15.60 | 
| 5 | 16 | 14.48 | 
| 6 | 13 | 14.78 | 
| MSE = | 13.17 | ||
| forecast for week 7 = | 14.42 | ||
d)
The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach.
e)
| Time period | Actual Value(A) | Forecast(F) | 
| 1 | 17 | |
| 2 | 12 | 17.00 | 
| 3 | 14 | 15.00 | 
| 4 | 10 | 14.60 | 
| 5 | 16 | 12.76 | 
| 6 | 13 | 14.06 |