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To classify the quarter that has the greatest seasonality.

A contractor developed a multiplicative time series model to predict the number of contracts in future quarters, using quarterly data on number of contracts during the 3-year period from 1996 to 1998. The following is the resulting regression equation:

Y = 3.35 + .117Time - .083Q1 + 1.28Q2 + .617Q3

where Y is the number of contracts in a quarter; Time is a linear time trend measured in quarters from January 1996, Q1 is a dummy categorical variable equal to 1 in the first quarter and 0 otherwise (see pg. 206 for a discussion of categorical variables); Q2 is a dummy variable equal to 1 in the second quarter and 0 otherwise; and Q3 is a final dummy variable equal to 1 in the third quarter and 0 otherwise.

Which quarter exhibits the greatest seasonality?

a. Q1

b. Q2

c. Q3

d. Q4

What is the forecast for the first quarter (Q1) for 1999?

a. 5.477

b. 6.477

c. 4.788

d. 5.871

The number of contracts per quarter have a(n):

a. negative trend.

b. positive trend.

c. quadratic trend.

d. exponential trend.

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Statistics and Probability, Statistics

Category:- Statistics and Probability
Reference No.:- M9169435

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