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Ch4
Student: ___________________________________________________________________________
1.
For the equation
Y
=
a
+
bX,
the objective of regression analysis is to
A. estimate the parameters
a
and
b
.
B. estimate the variables
Y
and
X
.
C. fit a straight line through the data scatter in such a way that the sum of the squared errors is minimized.
D. both
a
and
c
E. all of the above
2.
In a linear regression equation of the form
Y
=
a
+
bX,
the slope parameter
b
shows
A.
Δ
X
/
Δ
Y
.
B.
Δ
Y
/
Δ
X
.
C.
Δ
Y
/
Δ
b
.
D.
Δ
X
/
Δ
b
.
E. none of the above
3.
In a linear regression equation of the form
Y
=
a
+
bX
, the intercept parameter
a
shows
A. the value of
X
when
Y
is zero.
B. the value of
Y
when
X
is zero.
C. the amount that
Y
changes when
X
changes by one unit.
D. the amount that
X
changes when
Y
changes by one unit.
4.
In a regression equation, the ______ captures the effects of factors that might influence the dependent
variable but aren't used as explanatory variables.
A. intercept
B. slope parameter
C.
R
square
D. random error term
5.
The sample regression line
A. shows the actual (or true) relation between the dependent and independent variables.
B. is used to estimate the population regression line.
C. connects the data points in a sample.
D. is estimated by the population regression line.
E. maximizes the sum of the squared differences between the data points in a sample and the sample
regression line.
6.
Which of the following is an example of a timeseries data set?
A. Amount of labor employed in each factory in the U.S. in 2010.
B. Amount of labor employed yearly in a specific factory from 1990 through 2010.
C. Average amount of labor employed at specific times of the day at a specific factory in 2010.
D. All of the above are timeseries data sets.
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View Full Document7.
The method of least squares
A. can be used to estimate the explanatory variables in a linear regression equation.
B. can be used to estimate the slope parameters of a linear equation.
C. minimizes the distance between the population regression line and the sample regression line.
D. all of the above
8.
In a linear regression equation
Y
=
a
+
bX,
the fitted or predicted value of
Y
is
A. the value of
Y
obtained by substituting specific values of
X
into the sample regression equation.
B. the value of
X
associated with a particular value of
Y
.
C. the value of
X
that the regression equation predicts.
D. the values of the parameters predicted by the estimators.
E. the value of
Y
associated with a particular value of
X
in the sample.
9.
A parameter estimate is said to be statistically significant if there is sufficient evidence that the
A. sample regression equals the population regression.
B. parameter estimated from the sample equals the true value of the parameter.
C. value of the
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 Spring '10
 HAMZA

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