Exhibit 15-6 Below you are given a partial Excel output based on a sample of 16 observations. ANOVA df SS MS F Regression 4,853 2,426.5 Residual 485.3 Coefficients Standard Error Intercept 12.924 4.425 X1 -3.682 2.630 X2 45.216 12.560 Refer to Exhibit 15-6. The interpretation of the coefficient of x¡ is that

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Exhibit 15-6
Below you are given a partial Excel output based on a sample of 16 observations.
ANOVA
df
SS
MS
F
Regression
4,853
2,426.5
Residual
485.3
Coefficients
Standard Error
Intercept
12.924
4.425
X1
-3.682
2.630
X2
45.216
12.560
Refer to Exhibit 15-6. The interpretation of the coefficient of x, is that
Transcribed Image Text:Exhibit 15-6 Below you are given a partial Excel output based on a sample of 16 observations. ANOVA df SS MS F Regression 4,853 2,426.5 Residual 485.3 Coefficients Standard Error Intercept 12.924 4.425 X1 -3.682 2.630 X2 45.216 12.560 Refer to Exhibit 15-6. The interpretation of the coefficient of x, is that
a)
a one-unit increase in x, will lead to a 3.682-unit decrease in y when all other variables are held constant
b)
a one-unit change in x1 will lead to a 3.682-unit decrease in y
C) a one-unit increase in x1 will lead to a 3.682-unit increase in x2 when all other variables are held constant
c)
d)
a one-unit increase in x will lead to a 3.682-unit decrease in x, when all other variables are held constant
Transcribed Image Text:a) a one-unit increase in x, will lead to a 3.682-unit decrease in y when all other variables are held constant b) a one-unit change in x1 will lead to a 3.682-unit decrease in y C) a one-unit increase in x1 will lead to a 3.682-unit increase in x2 when all other variables are held constant c) d) a one-unit increase in x will lead to a 3.682-unit decrease in x, when all other variables are held constant
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