Chapter 17

A time series model could include
1. Trend
2. Seasonal factors
3. Cyclical factors
4. All of the above
A trend is
1. copying past figures
2. a general direction in which the figures are moving
3. being the same as other current figures
4. the use of regression
the use of regression
1. A = T ÷ S ÷ C ÷ R
2. A = T – S + C + R
3. A = T + S + C + R
4. A = T × S × C × R
The additive model is given by
1. A = T ÷ S ÷ C ÷ R
2. A = T – S + C + R
3. A = T + S + C + R
4. A = T × S × C × R
The number of periods included in a moving average trend correspond to
1. always 4 , 5 or 6
2. the maximum possible
3. the minimum possible
4. none of these
The seasonal factor for the additive model is estimated using
1. A - T
2. T × S
3. T/A
4. A/T
Predictions are made by
1. averaging the trend and seasonal variation
2. extending the trend and adjusting for seasonal factor
3. giving the average seasonal variation
4. extending for the trend and adjusting for the residual
The exponentially weighted moving average
1. gives more weight to recent data
2. has a sum of weights which equals 1
3. is weighted exponentially
4. all of these