Question

Consider the following time series data. Week 1 2 3 4 5 6 Value 19 12 15 10 18 14 (a) Construct a time series plot. What type of pattern exists in the data? The data appear to follow a trend pattern. The data appear to follow a horizontal pattern. The data appear to follow a seasonal pattern. The data appear to follow a cyclical pattern. (b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.) Week Time Series Value Forecast 1 19 2 12 3 15 4 10 5 18 6 14 MSE = Compute MSE. (Round your answer to two decimal places.) What is the forecast for week 7? FORECAST = (c) Use α = 0.2 to compute the exponential smoothing values for the time series. Week Time Series Value Forecast 1 19 2 12 3 15 4 10 5 18 6 14 Compute MSE. (Round your answer to two decimal places.) MSE = What is the forecast for week 7? (Round your answer to two decimal places.) FORECAST = (d) Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Explain. The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach using α = 0.2. The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average 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 three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach using α = 0.2. (e) Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2. α =

          Consider the following time series data.

Week
1
2
3
4
5
6
Value
19
12
15
10
18
14

(a) Construct a time series plot. What type of pattern exists in the data?
The data appear to follow a trend pattern.
The data appear to follow a horizontal pattern.
The data appear to follow a seasonal pattern.
The data appear to follow a cyclical pattern.

(b) Develop the three-week moving average for this time series. (Round your answers to two decimal places.)

Week
Time Series Value
Forecast
1
19
2
12
3
15
4
10
5
18
6
14

MSE = Compute MSE. (Round your answer to two decimal places.)
What is the forecast for week 7?
FORECAST =

(c) Use α = 0.2 to compute the exponential smoothing values for the time series.

Week
Time Series Value
Forecast
1
19
2
12
3
15
4
10
5
18
6
14

Compute MSE. (Round your answer to two decimal places.)
MSE =
What is the forecast for week 7? (Round your answer to two decimal places.)
FORECAST =

(d) Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Explain.
The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach using α = 0.2.
The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average 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 three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach using α = 0.2.

(e) Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2.
α =

Added by Bradley T.

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