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Quiz 5 - Chapter 15



Multiple Choice
Identify the letter of the choice that best completes the statement or answers the question.
 

1. 

For a multiple regression model, SSR = 600 and SSE = 200. The multiple coefficient of determination is
a.
0.333
b.
0.275
c.
0.300
d.
0.75
 

2. 

In regression analysis, the response variable is the
a.
independent variable
b.
dependent variable
c.
slope of the regression function
d.
intercept
 
 
Exhibit 15-1
In a regression model involving 44 observations, the following estimated regression equation was obtained.

Y-hat = 29 + 18X1 +43X2 + 87X3

For this model SSR = 600 and SSE = 400.
 

3. 

Refer to Exhibit 15-1. MSR for this model is
a.
200
b.
10
c.
1,000
d.
43
 

4. 

A variable that cannot be measured in numerical terms is called
a.
a nonmeasurable random variable
b.
a constant variable
c.
a dependent variable
d.
a qualitative variable
 
 
Exhibit 15-8
The following estimated regression model was developed relating yearly income (Y in $1,000s) of 30 individuals with their age (X1) and their gender (X2) (0 if male and 1 if female).

Y-hat = 30 + 0.7X1 + 3X2

Also provided are SST = 1,200 and SSE = 384.
 

5. 

Refer to Exhibit 15-8. If we want to test for the significance of the model, the critical value of F at 95% confidence is
a.
3.33
b.
3.35
c.
3.34
d.
2.96
 

6. 

A variable that takes on the values of 0 or 1 and is used to incorporate the effect of qualitative variables in a regression model is called
a.
an interaction
b.
a constant variable
c.
a dummy variable
d.
None of these alternatives is correct.
 
 
Exhibit 15-5
Below you are given a partial Minitab output based on a sample of 25 observations.

 
Coefficient
Standard Error
Constant
145.321
48.682 
X1
 25.625
9.150
X2
 -5.720
3.575
X3
  0.823
0.183
 

7. 

Refer to Exhibit 15-5. The estimated regression equation is
a.
Y = b0 + b1X1 + b2X2 + b3X3 + e
b.
E(Y) = b0 + b1X1 + b2X2 + b3X3
c.
Y-hat = 145.321 + 25.625X1 - 5.720X2 + 0.823X3
d.
Y-hat = 48.682 + 9.15X1 + 3.575X2 + 0.183X3
 

8. 

Refer to Exhibit 15-5. The interpretation of the coefficient on X1 is that
a.
a one unit change in X1 will lead to a 25.625 unit change in Y
b.
a one unit change in X1 will lead to a 25.625 unit increase in Y when all other variables are held constant
c.
a one unit change in X1 will lead to a 25.625 unit increase in X2 when all other variables are held constant
d.
It is impossible to interpret the coefficient.
 

9. 

Refer to Exhibit 15-5. We want to test whether the parameter b1 is significant. The test statistic equals
a.
0.357
b.
2.8
c.
14
d.
1.96
 

10. 

Refer to Exhibit 15-5. The t value obtained from the table to test an individual parameter at the 5% level is
a.
2.06
b.
2.069
c.
2.074
d.
2.080
 



 
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