W
00~
O
U
B
W
N

A
B
C
D
E
G
H
I
J
K
SUMMARY
OUTPUT
Regression
Statistics
Multiple
R
0.843419937
R
Square
0.71135719
Adjusted
R
Square
0.698807502
Standard
Error
197.4291643
Observations
25
ANOVA
df
SS
MS
F
gnificance
F
Regression
1
2209416
2209416
56.68325963
1.2E07
Residual
23
896500.3
38978.27
Total
24
3105916
Coefficients
andard
Err
t
Stat
Pvalue
Lower
95%Upper
95%ower
95.0%
pper
95.0%
Intercept
1187.312965
164.4746
7.218822
2.39E07
847.0713
1527.555
847.0713
1527.555
Size_(sq._ft)
1.059182176
0.140684
7.528829
1.20E07
0.768156
1.350208
0.768156
1.350208
C)
The
t
stat
as
shown
in
output
is
7.529
We
aren't
told
to
make
a
hypothesis
but
since
we
have
to
make
a
conclusion
at
the
end
we
can
quickly
also
make
one.
HO:
R1=0
(this
means
the
slope=0,
meaning
no
relationship)
H1:
R1#0
(this
means
the
slope
ISNT
0O,
there
can
be
a
linear
relationship)
D)
The
Pvalue
as
shown
in
output
is
1.1957964773231E07
In
simplied
terms
this
number
is
0.0000001
....
so
its
clearly
lower
then
our
alpha
at
0.05.
E)
As
mentioned
above,
our
pvalue
is
MUCH
lower
then
our
significence
level
of
0.05.
This
means
that
we
reject
the
null
hypothesis
and
conclude
the
slope
is
NOT
zero,
there
is
a
relationship
between
rent
and
size!