Chapter 18: Forecasting

A group of observations measured at successive time intervals is known as
1. a trend component
2. a time series
3. a forecast
4. an additive time series model
A component of the time series model that results in the multi-period above-trend and below-trend behavior of a time series is
1. a trend component
2. a cyclical component
3. a seasonal component
4. an irregular component
The model which assumes that the actual time series value is the product of its components is the
1. forecast time series model
2. multiplicative time series model
3. additive time series model
4. none of the above
A time series model whereby a regression relationship based on past time series values is used to forecast future time series values is
1. an autoregressive model
2. the Delphi method
3. the linear trend
4. an intuitive approach
A method that uses a weighted average of past values for arriving at smoothed time series values is known as
1. the smoothing average
2. the moving average
3. the exponential average
4. exponential smoothing
In the linear trend equation T = b0 + b1t, b1 represents the
1. trend value in period t
2. intercept of the trend line
3. slope of the trend line
4. point in time
In the linear trend equation T = b0 + b1t, b0 represents the
1. time
2. slope of the trend line
3. trend value in period 1
4. the Y intercept
A parameter of the exponential smoothing model that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the
1. mean square error
2. mean absolute deviation
3. smoothing constant
4. none of the above
One measure of the accuracy of a forecasting model is
1. the smoothing constant
2. a deseasonalized time series
3. the mean square error
4. none of the above
A qualitative forecasting method that obtains forecasts through "group consensus" is known as the
1. autoregressive model
2. Delphi approach
3. mean absolute deviation
4. none of the above