Question

If the span of a moving average is large – say, 12 months – then many observations go into each average, and extreme values have relatively large effect on the forecasts. True or False.

In an additive seasonal model, we add an appropriate seasonal index to a “base” forecast. These indexes, one for each season, typically average to 1. True or False.

The trend pattern is easy to identify by using

	a.	simple exponential smoothing
	b.	the Delphi approach
	c.	regression analysis
	d.	moving averages

One form of autocorrelation is negative autocorrelation, in which:

	a.	large observations tend to follow small observations and small observations tend to follow large observations
	b.	small observations tend to follow both large and small observations
	c.	large observations tend to follow both large and small observations
	d.	large observations tend to follow large observations and small observations tend to follow small observations

Answer 1

1) If the span of a moving average is large – say, 12 months – then many observations go into each average, and extreme values have relatively large effect on the forecasts. FALSE.

Actually extreme values have relatively little effect on the forecasts. If the span of a moving average is large.

2)

In an additive seasonal model, we add an appropriate seasonal index to a “base” forecast. These indexes, one for each season, typically average to 1. FALSE

additive seasonal model, . These indexes, one for each season, typically average to 0.

3) The trend pattern is easy to identify by using REGRESSION ANALYSIS.

4)

negative autocorrelation, = large observations tend to follow small observations and small observations tend to follow large observations