BUAL 2650 Final Exam (Chen Yan) Questions and
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Terms in this set (42)
a) errors are normally distributed
All of the following are
b) error terms have a mean of zero
assumptions of the error
c) error terms have a constant variance
terms in the simple linear
regression model except?
d) error terms are dependent on each other
The area under the normal greater than
curve between z=0 and z=1
is_________ the area under the
normal curve between z=1
and z=2.
Assume that the current 45.9
date is February 1, 2003.
The linear regression
model was applied to a
monthly time series based
on the last 24 months'
sales (from January 2000
through December 2002).
The following partial
computer output
summarizes the results.
, An automobile finance accurately classified as a Defaulter.
company analyzed a
sample of recent
automobile loans to try to
determine key factors in
identifying borrowers who
would be likely to default
on their auto loan. The
response variable Default
equals 1 if the borrower
defaulted during the term
of the loan and 0
otherwise. The predictor
variable AutoDebt% was
the ratio (expressed as a
percent) of the required
loan payments to the
borrower's take-home
income at the time of
purchase. JobTime was the
number of years the
borrower had worked at
their current job at the
time of purchase.
CredScore was the
borrower's credit score at
the time of purchase.
Below is part of the
classification tree the
finance company derived
from the data collected in
the study. Assume they
classify those with a
default probability
estimate of at least .5 as
Defaulters.
Answers
Save
Terms in this set (42)
a) errors are normally distributed
All of the following are
b) error terms have a mean of zero
assumptions of the error
c) error terms have a constant variance
terms in the simple linear
regression model except?
d) error terms are dependent on each other
The area under the normal greater than
curve between z=0 and z=1
is_________ the area under the
normal curve between z=1
and z=2.
Assume that the current 45.9
date is February 1, 2003.
The linear regression
model was applied to a
monthly time series based
on the last 24 months'
sales (from January 2000
through December 2002).
The following partial
computer output
summarizes the results.
, An automobile finance accurately classified as a Defaulter.
company analyzed a
sample of recent
automobile loans to try to
determine key factors in
identifying borrowers who
would be likely to default
on their auto loan. The
response variable Default
equals 1 if the borrower
defaulted during the term
of the loan and 0
otherwise. The predictor
variable AutoDebt% was
the ratio (expressed as a
percent) of the required
loan payments to the
borrower's take-home
income at the time of
purchase. JobTime was the
number of years the
borrower had worked at
their current job at the
time of purchase.
CredScore was the
borrower's credit score at
the time of purchase.
Below is part of the
classification tree the
finance company derived
from the data collected in
the study. Assume they
classify those with a
default probability
estimate of at least .5 as
Defaulters.
