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TABLE 16-12
A local store developed a multiplicative time-series model to forecast its revenues in future quarters, using quarterly data on its revenues during the 4-year period from 2005 to 2009. The following is the resulting regression equation:
log₁₀ = 6.102 + 0.012 X - 0.129 Q₁ - 0.054 Q₂ + 0.098 Q₃
where is the estimated number of contracts in a quarter.
X is the coded quarterly value with X = 0 in the first quarter of 2005.
Q₁ is a dummy variable equal to 1 in the first quarter of a year and 0 otherwise.
Q₂ is a dummy variable equal to 1 in the second quarter of a year and 0 otherwise.
Q₃ is a dummy variable equal to 1 in the third quarter of a year and 0 otherwise.
-Referring to Table 16-12, the best interpretation of the coefficient of X (0.012) in the regression equation is
Skyrockets
Rapid increase or sudden upward movement in prices, popularity, or other measurable factors.
Rank-Order Consistency
Comparing someone to the average person his or her age.
Variability
The degree to which data points differ from each other or the mean in a dataset, indicating the spread or dispersion of the dataset.
Maturation Of Personality
Growth in traits consistent with being more mature and grown-up, such as higher conscientiousness, higher agreeableness, and lower neuroticism.
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