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 151
In a regression model involving 44 observations, the
following estimated regression equation was obtained.
Yhat = 29 + 18X_{1} +43X_{2} +
87X_{3}
For this model SSR = 600 and SSE = 400.


3.

Refer
to Exhibit 151. MSR for this model is


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 158
The following estimated regression model was developed
relating yearly income (Y in $1,000s) of 30 individuals with their age (X_{1}) and their
gender (X_{2}) (0 if male and 1 if female).
Yhat = 30 + 0.7X_{1} +
3X_{2}
Also provided are SST = 1,200 and SSE =
384.


5.

Refer
to Exhibit 158. If we want to test for the significance of the model, the critical value of F at 95%
confidence is


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 155
Below you are given a partial Minitab output based on
a sample of 25 observations.
 Coefficient  Standard
Error  Constant  145.321  48.682  X_{1}  25.625  9.150  X_{2}  5.720  3.575  X_{3}  0.823  0.183    


7.

Refer
to Exhibit 155. The estimated regression equation is a.  Y = b_{0} +
b_{1}X_{1} + b_{2}X_{2} + b_{3}X_{3} + e  b.  E(Y) = b_{0} + b_{1}X_{1} + b_{2}X_{2} + b_{3}X_{3}  c.  Yhat = 145.321
+ 25.625X_{1}  5.720X_{2} + 0.823X_{3}  d.  Yhat = 48.682 +
9.15X_{1} + 3.575X_{2} + 0.183X_{3}   


8.

Refer
to Exhibit 155. The interpretation of the coefficient on X_{1} is that a.  a one unit
change in X_{1} will lead to a 25.625 unit change in Y  b.  a one unit
change in X_{1} will lead to a 25.625 unit increase in Y when all other variables are held
constant  c.  a one unit change in X_{1} will lead to a 25.625 unit
increase in X_{2} when all other variables are held constant  d.  It is impossible
to interpret the coefficient.   


9.

Refer
to Exhibit 155. We want to test whether the parameter b_{1} is significant. The test statistic
equals


10.

Refer
to Exhibit 155. 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   
