Casio FX-795P - Statistics Output

CHAPTER
2.
Manual
Operations
a
variable statistics.
36
The
details
are
explained
in
the
following
table:
STAT
LIST
(or
STAT
LIST
0)
is
for
outputting
all
of
the
statistics.
STAT
LIST
1
is
for
one-variable
statistics
alone
and
STAT
LIST
2
for
paired-
STAT
LIST
(0)
STAT
LIST
1
STAT
LIST
2
n
n
n
Zax
Ze
:
Sz
Zy
By
Zz?
Zat
2
Dat
2
Zy?
Dyt
2
Eaxy
Zay
=
Za/n
Zx/n
Za/n
y
Zy/n
Zy/n
ron
On
xOn
ron
yon
yon
yon
xO
n-1
xO
a-1
xO
p-1
xO
nt
yO
n-1
yond
yO
nl
a
a
a
b
b
b
r
r
r
Output
of
paired-
Sureaichgt
QUIRHL
SE
RRSicg
|
varitle
secondary.
Regression
formula:
y
=
@
+
bee
EOX
and
EOY
are
treated
as
functions.
These
can
be
calculated
in
the
same
way
as
ordinary
numerical
functions;
“EOX
y
value”
or
“EOY
x
value”,
When
x
and
y
values
are
variables
or.
numeric
values,
parentheses
can
be
omitted
in
the
same
way as in the case of SIN, etc.
Now
master
statistical
calculations
by
doing
the
following
exercises:
-
Exercise:
The
table
at
right
shows
the
state
of
ship-
ments
of
product
x
and
product
y.
Deter-
mine
the
variance
of
shipments
by
finding
the
standard
deviation.
Date
Co | 415 )6)7
x 2.)2)5) 8
y 1{5]/5]5
25 Statistical Calculations
eee
Operation: .
First
input
the
statistical
data
shown
in
the
table.
(Use
the
RUN
mode.)
star
Go) (eu (ceeaa) (exe)
2D) 1 bal
20)5 bal
Input all x and y data.
Upon
completion
of
data
input,
output
all
of
the
statistics
one
by
one
by
using
STAT
LIST.
(Number of data) Gon) or Ose
(Sum of x data) exe}
(Sum of y data) (exe)
(Sum of squares of x data) exe)
(Sum of squares of y data) xe
(Sum of products of x and y data) eq]
(Mean of x data) Ex
(Mean of y data) xe
(Standard deviation of x) (a)
(Standard deviation of y) )
Others omitted
Comparison
of
products
x
and
y
on
the
basis
of
the
above
calculation
results
shows
that
the
sums
total
and
the
mean
values
are
the
same,
but
the
standard
deviation
is
larger
in
the
case
of
product
x.
This
suggests
that
there
is
a
larger
variance
in
shipment
of
this
product.
Now
find
correlation
coefficients
and
estimated
values
through
a
regression
calculation
with
paired
data.
37