1. Holt-Winters method for additive effects is a forecasting technique applicable when:

a. The time series exhibits an upward trend.

b. The time series exhibits a downward trend.

c. The time series exhibits seasonality.

d. All of the above conditions describe situations when Holt-Winters method is applicable.

2. The Holt-Winters method for multiplicative effects is a forecasting technique applicable when:

a. The time-series variance is constant.

b. The time series has the base level equal to zero.

c. The seasonal effects in the data may be becoming more pronounced over time.

d. There is a significant nonlinear trend in the time series.

3. In a time series linear trend model:

a. The independent variable is the time index, t.

b. There can be only one independent variable.

c. The independent variable is of power 1.

d. All options listed are characteristics of time series linear trend model.

4. In a time series quadratic trend model:

a. The slope of the linear term is statistically insignificant.

b. The Y-intercept is statistically insignificant.

c. A curved trend may be fitted.

d. All independent variables are of power 1.

5. Suppose you want to model monthly time series data using a regression model. How many binary variables are needed to model seasonality in this situation?

a. 11.

b. 4.

c. 2.

d. 8.