Operation Manual

J Fraction−to−decimal conversion
Example 1.:
1
2
Percentage calculations
 Use the COMP mode for percentage cal-
culations.
Example 1.:
To calculate 12 % of 1500
1500
12
Example 2.: To calculate what percentage of
880 is 660
660 880
Example 3.: To add 15 % onto 2500
2500 15
2500
Example 4.: To discount 3500 by 25 %
3500 3500 25
Example 5.: If 300 grams are added to a test
sample originally weighing 500 grams, what is
the percentage increase in weight?
300 500
500
Example 6.: If temperature changes from 40°C
to 46°C, what percentage did it rise?
46 40
40
Scientific function calculations
 Use the COMP mode for scientific function
calculations.
 =3.1415926536
Trigonometric / Inverse trigonometric func-
tions
Example 1.: sin63°52’41"
>
63 52 41
Example 2.:
>
3
Example 3.:
>
2 2
Example 4.: tan
−1
0.741
>
0.741
J Hyperbolic / Inverse hyperbolic
functions
Example 1.: sinh 3.6
3.6
Example 2.: sinh
−1
30
30
J Angle unit conversion
 Press to display the following
menu.
 Pressing , or converts the dis-
played value to the corresponding angle
unit.
Example 1.: To convert 4.25 radians to de-
grees
>
4.25
Common and Natural logarithms /
Antilogarithms
Example 1.: log 1.23
1.23
Example 2.: ln 90(=log
e
90)
90
Example 3.: e
10
10
Example 4.: 10
1.5
1.5
Example 5.: 2
4
2 4
J Square roots, Cube roots, Roots,
Squares, Cubes, Reciprocals, Factorials,
Random Numbers and
Example 1.:
2
+
3
x
5
2 3
5
Example 2.:
5 27
Example 3.:
7 123
Example 4.: 123 + 30
2
123 30
Example 5.: 12
3
12
Example 6.:
3 4
Example 7.: 8!
8
Example 8.: To generate a random number
between 0.000 and 0.999. (Results differ each
time).
Example 9.: 3
3
J FIX, SCI, RND
Example 1.: 200:7x14=400
200
7 14
(Specifies three decimal places.)
(Calculation continues using
10 display digits)
200
7
14
Performing the same calculation using the speci-
fied number of decimal places
200
7
(Internal rounding)
14
 Press to clear FIX specifi-
cation.
Example 2.: 1:3, displaying result with two si-
gnificant digits (SCI2).
 Press
1 3
 Press to clear SCI specifi-
cation.
J ENG calculations
Example 1.: To convert 56088 meters to kilo-
meters
56088
Example 2.: To convert 0.08125 grams to milli-
grams
0.08125
J Coordinate conversion (Pol (x, y),
Rec (r, ))
 Calculation results are automatically assi-
gned to variables E and F.
Example 1.: To convert polar coordinates (r=2,
=60°) to retangular coordinates (x, y) (DEG
mode)
x 2
60
y
 , swaps displayed value
with value in memory.
Example 2.: To convert retangular coordinates
(1,
3
) to polar coordinates (r, ) (RAD mode)
r 1 3
 , swaps displayed value
with value in memory.
J Permutation
Example 1.: To determine how many different
4−digit values can be produced using the num-
bers 1 through 7
 Numbers cannot be duplicated within the
same 4−digit value (1234 is allowed, but
1123 is not).
7 4
J Combination
Example 1.: To determine how many different
4−member groups can be organized in a group
of 10 individuals.
10
4
Statistical Calculations
J Standard deviation (SD mode)
 Press to enter the SD Mode for sta-
tistical calculations using standard devia-
tion.
 Data input always starts with to
clear statistical memory.
 Input data is used to cal-
culate values for n, x, x
2
,
,
ón
and
ón
−1
which you
can recall using the key
operations noted nearby.
Example 1.:
To calculate
ón
−1,
ón
, , n, x and
x
2
for the following data: 55, 54, 51, 55, 53, 53,
54, 52
Enter SD Mode (Memory
Clear).
55 54 51 55
53 54 52
(Sample Standard Deviation
ón
−1)
(Population Standard Deviation
ón
)
(Arithmetic Mean )
(Number of data n)
(Sum of Values x)
(Sum of Squares of Values x
2
)
Data input precautions
 inputs the same data twice.
 You can also input multiple entries of the
same data using . To input the data
110 ten times, for example, press 110
10 .
 The above results can be obtained in any
order and not necessarily that shown
above.
 To delete data you have just input, press
.
J Regression Calculations (REG mode)
 Press to enter the REG mode and
then select one of the following regression
types.
: Linear regression
: Logarithmic regression
: Exponential regression
: Power regression
: Inverse regression
 Data input always starts with to
clear statistical memory.
 The values produced by a regression calcu-
lation depend on the values input and re-
sults can be recalled using the key opera-
tions shown in the table below.
 Linear regression
The regression formula for linear regression is:
y=A+Bx.
Example 1.: Athmospheric Pressure vs. Tem-
perature
Tempera-
ture
Athmosp-
heric
Pressure
10°C 1003 hPa
15°C 1005 hPa
20°C 1010 hPa
25°C 1011 hPa
30°C 1014 hPa
Enter REG Mode (Linear Regression)
(Memory Clear)
10 1003 15
1005
20 1010 25
1011
30 1014
(Regression Coefficient A)
(Regression Coefficient B)
(Correlation Coefficient r)
(Atmospheric Pressure at 18°C)
18
(Temperature at 1000 hPa)
1000
Quadratic Regression
 The regression formula for quadratic
regression is:
y = A+Bx+Cx
2
 Input data using the following key se-
quence.
<x−data> <y−data>
 Example:
xi yi
29 1.6
50 23.5
74 38.0
103 46.4
118 48.0
678910
1
<> 0.5 (Fraction <> Decimal)
2
−
1 2.
0.5
1 2.
180.
75.
2875.
2625.
300+500
500
x100=160(%)
160.
46−40
40
x100=15(%)
15.
0.897859012
cos
3
RAD
0.5
cos
4
RAD
−1 2
2
=
0.785398163
0.25
36.53844577
18.28545536
4.094622224
4.25r
243.5070629
0.089905111
4.49980967
22026.46579
31.6227766
16.
5.287196909
3
5 +
3
−27
−1.290024053
(=123
1
−
7
)
7
123
1.988647795
1023.
1728.
1
3
1
4
1
−
12.
40320.
0.664
9.424777961
400.
400.000
Fix
28.571
400.000
28.571
28.571
399.994
3.3
−01
Scl
56.088
03
81.25
−03
1.
1.732050808
2.
1.047197551
840.
210.
x
2
x
x
n
ón
x
ón
−1
52.
SD.........
1.407885953
1.316956719
53.375
8.
427.
22805.
ón
x
x
2
x
x
n
y
2
y
x
y
3
x
2
x
y
4
x
Perform linear regres-
sion to determine the re-
gression formula terms
and correlation coeffi-
cient for the data nearby.
Next, use the regression
formula to estimate at-
mospheric pressure at
18°C and temperature at
1000 hPa.
30.
REG..............
997.4
0.56
0.982607368
1007.48
4.642857143
Perform quadratic
regression to deter-
mine the regres-
sion formula terms
and correlation
coefficient for the
data nearby. Next,
use the regression
formula to estimate
the values for
(estimated value of
y) for xi = 16 and
(estimated value of
x) for yi = 20.