Sharp EL733A EL-733A Operation Manual - Page 79

Linear, Regression, Stock, Value

Get Sharp EL733A PDF manuals and user guides View all Sharp EL733A manuals
Add to My Manuals
Save this manual to your list of manuals

Page 79 highlights

1. If This graph shows the six data points plotted with a line drawn to approximate their trend over the years 1982 to SLOPE. Y-1NTERCEPT, AND CORRELATION 1987. The line is extended to the year 2000 where it predicts the stock value to be at $78'936.29: Three important values in linear regression are C1 , Ej , El and El . The values 0 and Ell come from the equation for a line (y = a + lax), where is the point that the line crosses the y-axis (the vertical axis) and El is the slope of 80'000 the line. With the equation for a line, you can describe any straight line. The value C) is called the "correlation 75'000 coefficient," and it is a measure of how closely the data points fit the line described by ED and El . 7onoo li 65'000 60'000 55'000 The correlation coefficient IT) ranges from -1 to 1. The closer this value is to 1 or -1, the closer the data points are to the line. For a certain set of data, if El is close to zero, the linear correlation is poor, which means that a straight line is a poor choice for modeling that set of data. To calculate , , and (?) for the previous example, use the following keystrokes: (Mode: STAT) 50'000 45'000 P2 ini TAB 0 El Pod H nd FI (to see all the decimal places) Result: -316581778. Result: 1868.857143 CO CO CO OD CO 03 0) CO CO a CO a CO CO CO 0) Ca 0 aal ,-- aa a CD CD a at a a Linear Regression Of Stock Value Data 0 lard 9 Result: 0.990733242 The reason that laj is such a large negative number in this case, is that the line stretches all the way back to the year 0000 before it crosses the y-axis. Of course, this is just a simple example to demonstrate the (- 1 function. It would probably not be wise to use a linear extrapolation on a five-year trend in stock value to evaluate the distant future of an investment. • 151 155

  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
  • 10
  • 11
  • 12
  • 13
  • 14
  • 15
  • 16
  • 17
  • 18
  • 19
  • 20
  • 21
  • 22
  • 23
  • 24
  • 25
  • 26
  • 27
  • 28
  • 29
  • 30
  • 31
  • 32
  • 33
  • 34
  • 35
  • 36
  • 37
  • 38
  • 39
  • 40
  • 41
  • 42
  • 43
  • 44
  • 45
  • 46
  • 47
  • 48
  • 49
  • 50
  • 51
  • 52
  • 53
  • 54
  • 55
  • 56
  • 57
  • 58
  • 59
  • 60
  • 61
  • 62
  • 63
  • 64
  • 65
  • 66
  • 67
  • 68
  • 69
  • 70
  • 71
  • 72
  • 73
  • 74
  • 75
  • 76
  • 77
  • 78
  • 79
  • 80
  • 81
  • 82
  • 83
1.
If
li
This
graph
shows
the
six
data
points
plotted
with
a
li
ne
drawn
to
approximate
their
trend
over
the
years
1982
to
1987.
The
line
is
extended
to
the
year
2000
where
it
predicts
the
stock
value
to
be
at
$78'936.29:
80'000
75'000
7onoo
65'000
60'000
55'000
50'000
45'000
CO
CO
CO
OD
CO
03
0)
CO
CO
a
CO
0)
CO
a
CO
CO
a
a
Ca
0
al
a
,--
a
CD
a
CD
at
a a
Linear
Regression
Of
Stock
Value
Data
Of
course,
this
is
just
a
simple
example
to
demonstrate
the
(
-1
function.
It
would
probably
not
be
wise
to
use
a
li
near
extrapolation
on
a
fi
ve-year
trend
in
stock
value
to
evaluate
the
distant
future
of
an
investment.
•
151
SLOPE.
Y-1NTERCEPT,
AND
CORRELATION
Three
important
values
in
linear
regression
are
C1
,
Ej
,
and
El
.
The
values
0
and
Ell
come
from
the
equation
for
a
line
(y
=
a
+
lax),
where
El
is
the
point
that
the
line
crosses
the
y-axis
(the
vertical
axis)
and
El
is
the
slope
of
the
line.
With
the
equation
for
a
line,
you
can
describe
any
straight
line.
The
value
C)
is
called
the
"correlation
coefficient,"
and
it
is
a
measure
of
how
closely
the
data
points
fi
t
the
line
described
by
ED
and
El
.
The
correlation
coefficient
IT)
ranges
from
—1
to
1.
The
closer
this
value
is
to
1
or
—1,
the
closer
the
data
points
are
to
the
line.
For
a
certain
set
of
data,
if
El
is
close
to
zero,
the
linear
correlation
is
poor,
which
means
that
a
straight
line
is
a
poor
choice
for
modeling
that
set
of
data.
To
calculate
,
,
and
(?)
for
the
previous
example,
use
the
following
keystrokes:
(Mode:
STAT)
P2
ini
TAB
0
(to
see
all
the
decimal
places)
Result:
—3
1
658
1
778.
Result:
1868.857143
Result:
0.990733242
Pod
H
nd
FI
lard
9
El
0
The
reason
that
laj
is
such
a
large
negative
number
in
this
case,
is
that
the
line
stretches
all
the
way
back
to
the
year
0000
before
it
crosses
the
y-axis.
155