Question

Consider the following time series data. Week 1 2 3 4 5 6 Value 19 12 14 11 15 13 (a) Construct a time series plot. A B C D What type of pattern exists in the data? A The data appear to follow a trend pattern. B The data appear to follow a horizontal pattern. C The data appear to follow a cyclical pattern. D The data appear to follow a seasonal pattern. (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 19 2 12 3 14 4 11 5 15 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 19 2 12 3 14 4 11 5 15 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. A The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach. B The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach. C The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach. D The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller 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 19 2 12 3 14 4 11 5 15 6 13 Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. A The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.4. B The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.4. C The exponential smoothing using α = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.2. D The exponential smoothing using α = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.2.

Consider the following time series data.

Week
1
2
3
4
5
6
Value
19
12
14
11
15
13

(a)
Construct a time series plot.

A
B
C
D

What type of pattern exists in the data?

A The data appear to follow a trend pattern.
B The data appear to follow a horizontal pattern.
C The data appear to follow a cyclical pattern.
D The data appear to follow a seasonal pattern.

(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
19
2
12
3
14
4
11
5
15
6
13

Compute MSE. (Round your answer to two decimal places.)

MSE =

What is the forecast for week 7?

Week
Time Series Value
Forecast
1
19
2
12
3
14
4
11
5
15
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.

A The three-week moving average provides a better forecast since it has a smaller MSE than the smoothing approach.
B The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the three-week moving average approach.
C The three-week moving average provides a better forecast since it has a larger MSE than the smoothing approach.
D The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller 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
19
2
12
3
14
4
11
5
15
6
13

Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain.

A The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.4.
B The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.4.
C The exponential smoothing using α = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.2.
D The exponential smoothing using α = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.2.

Added by Trung B.

Question

Please give Ace some feedback