1. When is it appropriate to choose an additive decomposition model?

a. When the seasonal and cyclical influences increase or decrease proportionate to corresponding fluctuations in the level of the time series.

b. When the graphical plot of the dataset has seasonal and cyclical influences that are unrelated to the general level of the time series

c. When there are no seasonal or cyclical influences.

d. When there are no cyclical influences.

2. Which of the following best describes the objective/function of the Ratio-to-Moving-Average (RMA) method?

a. To forecast the time series at hand

b. To measure the degree of seasonality

c. To decompose a time series into individual components

d. To remove short-term fluctuations from the data

3. After decomposing a time series, which of the following can NOT be determined?

a. Long-term trend (CMAT) based on de-seasonalized data

b. CF, the ratio of CMA to CMAT, which represents the gradual wavelike movements in the series around the trend line.

c. SI's, the normalized averages of seasonal factors that are determined as the ratio of each period's actual value (Y) to the deseasonalized value (CMA)

d. All of these may be obtained via time series decomposition