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 |
1. Refer to Exhibit 15-6. The estimated regression equation is
a. y = β0 + β1x1 + β2x2 + ε
b. E(y) = β0 + β1x1 + β2x2
c. y hat = 12.924 - 3.682 x1 + 45.216 x2
d. y hat = 4.425 + 2.63 x1 + 12.56 x2
2. Refer to Exhibit 15-6. The interpretation of the coefficient of x1 is that
a. a one unit change in x1 will lead to a 3.682 unit decrease in y
b. a one unit increase in x1 will lead to a 3.682 unit decrease in y when all other variables are held constant
c. a one unit increase in x1 will lead to a 3.682 unit decrease in x2 when all other variables are held constant
d. It is impossible to interpret the coefficient.
3. Refer to Exhibit 15-6. We want to test whether the parameter β1 is significant. The test statistic equals
a. -1.4
b. 1.4
c. 3.6
d. 5
4. Refer to Exhibit 15-6. The t value obtained from the table which is used to test an individual parameter at the 1% level is
a. 2.65
b. 2.921
c. 2.977
d. 3.012
1.
We can clearly see the intercept is 12.924, coefficient of x1 is - 3.682 and coefficient of x2 is 45.216
So, correct option is option c)
2.
Since coefficient of x1 is negative so,
a one unit increase in x1 will lead to a 3.682 unit decrease in y when all other variables are held constant.
correct option is option b)
3.
Test statistic =-3.682/2.630 =-1.4
correct option is option a)
4.
Sample size =16
Dof =16-2-1=13
So, t value from table =t/2=0.005,13 = 3.012
correct option is option d)
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