Exam 15: Forecasting

All quarterly time series contain seasonality.

Which of the following forecasting methods puts the least weight on the most recent time series value?

Quantitative forecasting methods can be used when past information about the variable being forecast is unavailable.

Exponential smoothing with $\alpha$ = .2 and a moving average with n = 5 put the same weight on the actual value for the current period.

All of the following are true about a stationary time series except

All of the following are true about a cyclical pattern except

Using exponential smoothing, the demand forecast for time period 10 equals the demand forecast for time period 9 plus

Trend in a time series must be linear.

The exponential smoothing forecast for any period is a weighted average of all the previous actual values for the time series.

All of the following are true about time series methods except

The forecasting method that is appropriate when the time series has no significant trend, cyclical, or seasonal pattern is

Smoothing methods are more appropriate for a stable time series than when significant trend or seasonal patterns are present.

If the random variability in a time series is great and exponential smoothing is being used to forecast, then a high alpha ( $\alpha$ ) value should be used.

Using a naive forecasting method, the forecast for next week's sales volume equals

Qualitative forecasting techniques should be applied in situations where time series data exists, but where conditions are expected to change.

The focus of smoothing methods is to smooth out

The trend pattern is easy to identify by using

A time series model with a seasonal pattern will always involve quarterly data.