M6D2 RQ
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School
University of Michigan *
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Course
301
Subject
Industrial Engineering
Date
Jan 9, 2024
Type
png
Pages
1
Uploaded by CommodoreCaribouMaster1044
Question
1
The
logistic
regression
model
below
estimates
the
probability
of
a
teacher
leaving his/her
school
(p)
as
a
function
of
the
number
of
years
at
the
school
()
and
the
number
of
students
in
his/her
class
(z,).
Assume
that
the
fhici
f
both
IVs
ignil
.
What
is
the
probability
that
a
teacher
who
has
been
at
the
school
for
2
years
and
has 25
students
in
the
class
leaves?
as,
0/1pts
[1fyou
pluginr)
=
2
and
x,
=
25
in
the
logistic
function
you
get
0.07.
Question
2
|
Below
s
a
logistic
regression
model
fitted
to
data
on the
success
of
a
chemistry
experiment
based
on
the
heated-to
temperature.
Which
of
the
following
statements
is
TRUE
about
the
plot
above?
|
107
e
emmm
emee
o
mecces
o
.
=
°
°
°
s
a
&
Probability
of
Success
°
00
.
ce
e
150
2%
300
Temperature
The
probability
of
success
when
the
temperature
is
200
or
less
is
about
3
The
experiment
has
always
succeeded
when
the
temperature
is
less
then
100
degree
‘The
probability
of
success
when
temperature
is
150
is
about
70%.
According
to
the
graph
at
150,
the
probability
of
success
is
about
0.7.
We
are
interested
in
predicting
the
probability
of
whether
a
company's
stock
price
falls
on
a
given
day
with
two
predictors:
yesterday's
price
(1)
and
whether
the
company
has
a
risky
credit
position
that
day
(r).
When
r=1,
it
means
the
company
is
in
the "risky"
category,
and
r=0
otherwise.
Here
are the
point
estimates
for
the
coefficients:
y-intercept:
by
=2,
b,
=
0.01,and
b,
=
correct
model
for
predicting
the
probability
of
whether
the
company's
stock
price
falls
(p)
as
a
function
of
its
previous
day
price
()
when
the
company
is
categorized
as
in
a
risky
credit
position
(r=1)2
}
Question
3
|
\
\
P
=05+001p,
1/1pts
0/1pts
1.5.
Which
of
the
following
is
the
=T
|
1
‘We
have
a
binary
dependent
variable
->
we
have
to
use
logistic
regression.
|
For
the
exponent
term
we
have
(2
+
0.01p,
-
1.5)
when
r
=
1
can
be
simplified
to:
|
|
@2+001p,-151)
|
(2+001p,
-
1.5)
(0.5+001p,)
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