Ativa AT-30i Panduan Pemilik - Halaman 2

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Example:
4.123.586.4 = 21.1496
Example
4.123.587.1 = 7.6496
Using any four numbers
[ON/AC] [4] [•] [1] [2] []
4.12x3.58+6.
from 1 to 7, how many
[3] [•] [5] [8] [] [6] [•] [4] [=]
21.1496
four digit even numbers
D
can be formed if none of
the four digits consist of
[3]
12x3.58+6.4 _
the same number?
21.1496
(3/7 of the total number
D
of permutations will be
[3] [3] [3] [3]
4.12x3.58+6.
even.)
21.1496
P
37 = 360
7
4
D
If any four items are
[] [7] [•] [1]
12x3.58–7.1 _
removed from a total
21.1496
of 10 items, how many
D
different combinations
[=]
4.12x3.58–7.
of four items are
7.6496
possible?
D
10
C
4
= 210
The replay function is not cleared even when [ON/AC] is
If 5 class officers are
pressed or when power is turned OFF, so contents can be
being selected for a
recalled even after [ON/AC] is pressed.
class of 15 boys and
10 girls, how many
Replay function is cleared when mode or operation is
combinations are
switched.
possible? At least one
girl must be included
Error Position Display Function
in each group.
When an ERROR message appears during operation
C
C
= 50127
25
5
15
5
execution, the error can be cleared by pressing the
[ON/AC] key, and the values or formula can be re-entered
from the beginning. However, by pressing the [3] or [4]
Other Functions (√ , x
key, the ERROR message is cancelled and the cursor moves
to the point where the error was generated.
Example
Example: 1402.3 is input by mistake
√2√5 = 3.65028154
[ON/AC] [1] [4] [] [0] []
Ma ERROR
2
2
3
2
4
2
5
2
[2] [.] [3] [=]
2
(3)
= 9
[3] (or [4] )
14÷0x2.3
1/(1/3–1/4) = 12
0.
8! = 40320
D
3
√(364249) = 42
Correct the input by pressing
Random number
generation (number is
[3] [SHIFT] [INS] [1]
14÷10x2.3
in the range of 0.000 to
0.
0.999)
D
[=]
14÷10x2.3
3.22
D
– 20 –
Scientific Function
Example
Trigonometric functions and inverse trigonometric
2
√(1–sin
40)
functions
= 0.766044443
• Be sure to set the unit of angular measurement before
performing trigonometric
function and inverse
trigonometric function calculations.
1/2!1/4!1/6!1/8!
• The unit of angular measurement (degrees, radians,
= 0.543080357
grads) is selected in sub-menu.
• Once a unit of angular measurement is set, it remains in
effect until a new unit is set. Settings are not cleared
Fractions
when power is switched OFF.
Fractions are input and displayed in the order of integer,
Display
numerator and denominator. Values are automatically
Example
Operation
(Lower)
displayed in decimal format whenever the total number of
sin 63 º 52'41"
[MODE][MODE][1]
("DEG" selected)
digits of a fractional value (interger + numerator +
[sin] 63 [ º ' "] 52 [ º ' "]
= 0.897859012
denominator + separator marks) exceeds 10.
41 [ º ' "][=]
0.897859012
cos (π/3 rad) = 0.5
[MODE][MODE][2]
("RAD" selected)
[cos][(] [SHIFT][π][]3
Example
[)] [=]
0.5
2
1
13
/
3
/
= 3
5
4
tan (–35 grad)
[MODE][MODE][3]
= –0.612800788
("GRA" selected)
[tan] [(–)] 35 [=]
–0.612800788
2sin45 º cos65 º
[MODE][MODE][1]
("DEG")
= 0.597672477
2[sin] 45 [cos] 65 [=]
0.597672477
–1
–1
sin
0.5 = 30
[SHIFT][sin
] 0.5 [=]
30.
456
11
3
/
78
= 8
/
13
cos
–1
(√2/2)
[MODE][MODE][2]
("RAD")
= 0.785398163 rad
[SHIFT][cos
–1
][(][√]2 []2
1
1
/
/
2578
4572
= π/4 rad
[)][=]
0.785398163
= 0.00060662
[][SHIFT][π][=]
0.25
–1
tan
0.741
[MODE][MODE][1]
("DEG")
= 36.53844577 º
[SHIFT][tan
–1
]0.741[=]
36.53844576
= 36 º 32' 18.4"
36 º 32 º 18.4 º
[SHIFT] [
←
º' "]
If the total number of digits for degrees/minutes/seconds exceed
11 digits, the higher order values are given display priority, and
any lower-order values are not displayed. However, the entire
value is stored within the unit as a decimal value.
2.5(sin
–1
0.8cos
–1
0.9)
2.5[] [(] [SHIFT] [sin
–1
]0.8
1
/
0.5 = 0.25
2
= 68 º 13'13.53"
[] [SHIFT] [cos
–1
] 0.9 [)]
1
/
4
/
)–
5
/
3
(–
5
6
←
68 º 13 º 13.53 º
[=] [SHIFT] [
º' "]
1
1
1
/
/
/
2
3
4
13
=
/
60
1
1
(
/
)/
=
/
2
3
6
1
1
1
/(
/
/
) = 1
3
4
– 21 –
Performing Hyperbolic and Inverse Hyperbolic Functions
Degree, Radian, Gradient Interconversion
Degree, radian and gradient can be converted to each
Display
other with the use of [SHIFT][DRG>]. Once [SHIFT]
Example
Operation
(Lower)
[DRG>] have been keyed in, the "DRG" selection menu
will be shown as follows.
sinh3.6= 18.28545536
[hyp][sin] 3.6 [=]
18.28545536
cosh1.23 = 1.856761057
[hyp][cos] 1.23 [=]
1.856761057
D
tanh2.5= 0.986614298
[hyp][tan] 2.5 [=]
0.986614298
1
cosh1.5sinh1.5
[hyp][cos] 1.5 [][hyp]
= 0.22313016
[sin] 1.5 [=]
0.22313016
Example
–1
–1
sinh
30 = 4.094622224
[hyp][SHIFT][sin
] 30 [=]
4.094622224
Define degree first
cosh
–1
(20/15)
[hyp][SHIFT][cos
–1
][(] 20
Change 20 radian to
= 0.795365461
[] 15 [)][=]
0.795365461
degree
x = (tanh
–1
0.88) / 4
[hyp][SHIFT][tan
–1
]0.88
To perform the following
= 0.343941914
[]4[=]
0.343941914
calculation :-
–1
–1
–1
sinh
2cosh
1.5
[hyp][SHIFT][sin
]2[]
10 radians+25.5 gradients
= 1.389388923
[hyp][SHIFT][cos
–1
]1.5[=]
1.389388923
The answer is expressed
sinh
–1
(2/3)tanh
–1
(4/5)
[hyp][SHIFT][sin
–1
][(]2[]
in degree.
–1
= 1.723757406
3[)][][hyp][SHIFT][tan
]
[(]4[]5[)][=]
1.723757406
Degrees, Minutes, Seconds Calculations
You can perform sexagesimal calculations using degrees
Logarithmic and Exponential Functions
(hours), minutes and seconds. And convert between
sexagesimal and decimal values.
Display
Example
Example
Operation
(Lower)
To express 2.258 degrees
log1.23
[log] 1.23 [=]
in deg/min/sec.
= 8.990511110
–2
0.089905111
To perform the calculation:
In90 = 4.49980967
[In] 90 [=]
4.49980967
12 º 34'56"3.45
log456In456
[log]456[In]456 [=]
0.434294481
= 0.434294481
1.23
x
10
= 16.98243652
[SHIFT][10
] 1.23 [=]
16.98243652
e
4.5
= 90.0171313
[SHIFT][e
x
]4.5[=]
90.0171313
10
4
• e
–4
1.2 • 10
2.3
[SHIFT][10
x
]4[][SHIFT][e
x
]
x
= 422.5878667
[(–)]4[]1.2[][SHIFT][10
]
2.3[=]
422.5878667
(–3)
4
= 81
[(][(–)] 3 [)] [x
y
] 4 [=]
81.
–3
4
= –81
[(–)] 3 [x
y
] 4 [=]
–81.
5.6
2.3
= 52.58143837
5.6 [x
y
] 2.3 [=]
52.58143837
7
x
√123 = 1.988647795
7 [SHIFT][
√] 123 [=]
1.988647795
(7823)
–12
[(]78[]23[)][x
y
][(–)]12[=]
1.305111829
–21
= 1.30511182910
–21
3
x
23
√644 = 10
2[]3[]3[SHIFT][
√]64
[]4[=]
10.
23.4
(5+6.7)
= 3306232
2[]3.4[x
y
][(]5[]6.7[)][=]
3306232.001
– 22 –
Coordinate Transformation
Statistical Calculations
• This scientific calculator lets you convert between
This unit can be used to make statistical calculations
rectangular coordinates and polar coordinates, i.e., P(x, y)
including standard deviation in the "SD" mode, and
↔ P(r, )
regression calculation in the "REG" mode.
• Calculation results are stored in variable memory E and
variable memory F. Contents of variable memory E are
Standard Deviation
displayed initially. To display contents of memory F,
In the "SD" mode, calculations including 2 types of
press [RCL] [F].
standard deviation formulas, mean, number of data, sum
• With polar coordinates,  can be calculated within a
of data, and sum of square can be performed.
range of –180 º < ≤180 º .
(Calculated range is the same with radians or grads.)
Data input
1. Press [MODE] [2] to specify SD mode.
Display
2. Press [SHIFT] [Scl] [=] to clear the statistical memories.
Example
Operation
(Lower)
3. Input data, pressing [DT] key (= [M+]) each time a new
x=14 and y=20.7, what
[MODE][MODE][1]
("DEG" selected)
piece of data is entered.
[Pol(]14 [ , ]20.7[)][=]
are r and  º ?
24.98979792(r)
[RCL][F]
55.92839019()
Example Data: 10, 20, 30
←
55 º 55 º 42.2()
[SHIFT][
º' "]
Key operation: 10 [DT] 20 [DT] 30 [DT]
x=7.5 and y=–10, what
[MODE][MODE][2]
("RAD" selected)
• When multiples of the same data are input, two different
[Pol(]7.5[ , ][(–)]10[)][=]
are r and  rad?
12.5(r)
entry methods are possible.
[RCL][F]
–0.927295218()
Example 1 Data: 10, 20, 20, 30
r=25 and = 56 º , what
[MODE][MODE][1]
("DEG" selected)
Key operation: 10 [DT] 20 [DT] [DT] 30 [DT]
[SHIFT][Rec(]25 [ , ]56[)][=]
are x and y?
13.97982259(x)
The previously entered data is entered again each time
[RCL][F]
20.72593931(y)
the DT is pressed without entering data (in this case 20
r=4.5 and =2π/3 rad,
[MODE][MODE][2]
("RAD" selected)
is re-entered).
[SHIFT][Rec(]4.5[ , ][(]2[]
what are x and y?
Example 2 Data: 10, 20, 20, 20, 20, 20, 20, 30
3[][SHIFT][π][)][)][=]
–2.25(x)
Key operation: 10 [DT] 20 [SHIFT] [;] 6 [DT] 30 [DT]
[RCL][F]
3.897114317(y)
By pressing [SHIFT] and then entering a semicolon
Permutation and Combination
followed by value that represents the number of items the
Total number of permutations nPr = n!/(n
r)!
data is repeated (6, in this case) and the [DT] key, the
Total number of combinations nCr = n!/(r!(n
r)!)
multiple data entries (for 20, in this case) are made
automatically.
Display
Deleting input data
Example
Operation
(Lower)
There are various ways to delete value data, depending on
Taking any four out of
10[SHIFT][nPr]4[=]
5040.
how and where it was entered.
ten items and arranging
them in a row, how many
Example 1 40 [DT] 20 [DT] 30 [DT] 50 [DT]
different arrangements
To delete 50, press [SHIFT] [CL].
are possible?
Example 2 40 [DT] 20 [DT] 30 [DT] 50 [DT]
P
= 5040
10
4
To delete 20, press 20 [SHIFT] [CL].
Example 3 30 [DT] 50 [DT] 120 [SHIFT] [;]
To delete 120 [SHIFT] [;] , press [ON/AC].
Example 4 30 [DT] 50 [DT] 120 [SHIFT] [;] 31
To delete 120 [SHIFT] [;] 31, press [AC].
– 23 –
Example 5 30 [DT] 50 [DT] 120 [SHIFT] [;] 31 [DT]
Display
To delete 120 [SHIFT] [;] 31 [DT], press [SHIFT] [CL].
Operation
(Lower)
All manuals and user guides at all-guides.com
Example 6 50 [DT] 120 [SHIFT] [;] 31 [DT] 40 [DT] 30 [DT]
7[SHIFT][nPr]4[]3[]
360.
To delete 120 [SHIFT] [;] 31 [DT], press 120 [SHIFT] [;] 31
7[=]
[SHIFT] [CL].
Example 7 [√] 10 [DT] [√] 20 [DT] [√] 30 [DT]
To delete [√] 20 [DT], press [√] 20 [=] [Ans] [SHIFT] [CL].
Example 8 [√] 10 [DT] [√] 20 [DT] [√] 30 [DT]
To delete [√] 20 [DT], press [√] 20 [SHIFT] [;] [(–)] 1 [DT].
Performing calculations
The following procedures are used to perform the various
standard deviation calculations.
10[nCr]4[=]
210.
Key operation
Population standard deviation, xσ
[SHIFT][xσ
]
n
Sample standard deviation, xσ
[SHIFT][xσ
]
n–1
Mean, x
[SHIFT][x]
[RCL][A]
Sum of square of data, ∑x
[RCL][B]
Sum of data, ∑x
Number of data, n
25[nCr]5[]15[nCr]5[=]
50127.
[RCL][C]
Standard deviation and mean calculations are performed
as shown below:
Population standard deviation σ
where i = 1 to
n
Sample standard deviation σ
where i = 1 to
n
Mean x = (∑x)/
n
Example
Operation
2
, x
–1
, x!,
3
√, Ran#)
Data 55, 54, 51, 55, 53,
[MODE][2]
53, 54, 52
[SHIFT][Scl][=]
Display
55[DT]54[DT]51[DT]
Operation
(Lower)
55[DT]53[DT][DT]54[DT]
[√]2[][√]5[=]
3.65028154
52[DT]
What is deviation of the
[RCL][C]
= 54
2[x
2
][]3[x
2
][]4[x
2
]
54.
[]5[x
2
][=]
unbiased variance, and
[RCL][B]
2
the mean of the above
[RCL][A]
[(][(–)]3[)][x
][=]
9.
data?
[SHIFT][x][=]
[(]3[x
–1
][]4[x
–1
][)][x
–1
][=]
12.
8[SHIFT][x!][=]
40320.
[SHIFT][xσ
3
[SHIFT][xσ
[
√][(]36[]42[]49[)][=]
42.
[SHIFT][xσ
[SHIFT][Ran#][=]
0.792
(random)
[x
2
][=]
– 24 –
Regression Calculation
Display
In the REG mode, calculations including linear regression,
Operation
(Lower)
logarithmic regression, exponential regression, power
[MODE][MODE][1]
("DEG" selected)
regression, inverse regression and quadratic regression
[√][(]1[][(][sin]40[)][x
2
]
can be performed.
[)][=]
0.766044443
[SHIFT][cos
–1
][Ans][=]
40.
Press [MODE] [3] to enter the "REG" mode:
2[SHIFT][x!][x
–1
][]
COMP SD REG
–1
4[SHIFT][x!][x
][]
1
2
6[SHIFT][x!][x
–1
][]
8[SHIFT][x!][x
–1
][=]
0.543080357
and then select one of the following regression types:-
Lin Log Exp
1
2
Lin: linear regression
Log: logarithmic regression
Exp: exponential regression
Display
press [4] for the other three regression types:-
Operation
(Lower)
Pwr Inv Quad
b
b
/
2[a
/
]5[]3[a
/
]1
1
2
20
c
c
b
[a
/
c
]4[=]
3
13
20.
⎦
⎦
b
[a
/
](conversion to decimal)
3.65
Pwr: power regression
c
Fractions can be converted
Inv: inverse regression
to decimals, and then
Quad: quadratic regression
converted back to fractions.
b
b
Linear regression
3[a
/
c
]456[a
/
c
]78[=]
8
11
13.
⎦
⎦
d
[SHIFT][
/
]
115
13.
Linear regression calculations are carried out using the
c
⎦
b
b
1[a
/
]2578[]1[a
/
]
following formula:
c
c
–04
y = A + Bx.
4572[=]
6.066202547
When the total number
of characters, including
Data input
Press [MODE] [3] [1] to specify linear regression under
integer, numerator,
denominator and
the "REG" mode.
Press [Shift] [Scl] [=] to clear the statistical memories.
delimiter mark exceeds
10, the input fraction is
Input data in the following format: <x data> [,] <y data>
automatically displayed
[DT]
• When multiples of the same data are input, two different
in decimal format.
b
1[a
/
]2[].5[=]
0.25
entry methods are possible:
c
= –1
1
/
1[a
b
/
]3[][(–)]4[a
b
/
]5
10
c
c
b
Example 1 Data: 10/20, 20/30, 20/30, 40/50
[]5[a
/
c
]6[=]
–1
1
10.
⎦
⎦
1
b
b
/
1[a
/
]2[]1[a
/
]3[]
Key operation: 10 [,] 20 [DT]
5
c
c
b
b
20 [,] 30 [DT] [DT]
1[a
/
c
]4[]1[a
/
c
]5[=]
13
60.
⎦
b
b
[(]1[a
/
]2[)][a
/
]3[=]
1
6.
40 [,] 50 [DT]
c
c
⎦
5
b
b
/
1[a
/
][(]1[a
/
]3[]
The previously entered data is entered again each time
7
c
c
b
the [DT] key is pressed (in this case 20/30 is re-entered).
1[a
/
c
]4[)][=]
1
5
7.
⎦
⎦
– 25 –
Example 2 Data: 10/20, 20/30, 20/30, 20/30, 20/30, 20/30,
40/50
Key operation: 10 [,] 20 [DT]
20 [,] 30 [SHIFT] [;] 5 [DT]
40 [,] 50 [DT]
By pressing [SHIFT] and then entering a semicolon
R
G
followed by a value that represents the number of times
2
3
the data is repeated (5, in this case) and the [DT] key, the
multiple data entries (for 20/30, in this case) are made
Operation
Display
automatically.
[MODE][MODE][1]
("DEG" selected)
r
20[SHIFT][DRG>][2][=]
20
Deleting input data
1145.91559
There are various ways to delete value data, depending on
10[SHIFT][DRG>][2]
how and where it was entered.
[]25.5[SHIFT][DRG>][3]
[=]
10
r
25.5
g
Example 1
10 [,] 40 [DT]
595.9077951
20 [,] 20 [DT]
30 [,] 30 [DT]
40 [,] 50
To delete 40 [,] 50, press [ON/AC]
Example 2
10 [,] 40 [DT]
20 [,] 20 [DT]
30 [,] 30 [DT]
Operation
Display
40 [,] 50 [DT]
2 º 15 º 28.8
2.258[º' "][=]
To delete 40 [,] 50 [DT], press [SHIFT][CL]
12[º' "]34[º' "]56[º' "][]
Example 3
43 º 24 º 31.2
3.45[=]
To delete 20 [,] 20 [DT], press 20 [,] 20 [SHIFT][CL]
Example 4
[√] 10 [,] 40 [DT]
[√] 40 [,] 50 [DT]
To delete[√]10[,]40[DT],
press [√]10[=][Ans][,]40[SHIFT][CL]
– 26 –
Key Operations to recall regression calculation results
Key operation
Result
[SHIFT][A][=]
Constant term of regression A
[SHIFT][B][=]
Regression coefficient B
[SHIFT][C][=]
Regression coefficient C
Correlation coefficient r
[SHIFT][r][=]
Estimated value of x
[SHIFT][x][=]
Estimated value of y
[SHIFT][y][=]
Population standard deviation, yσ
[SHIFT][yσ
]
n
Sample standard deviation, yσ
[SHIFT][yσ
]
n–1
Mean, y
[SHIFT][y]
Population standard deviation, xσ
[SHIFT][xσ
]
n
Sample standard deviation, xσ
[SHIFT][xσ
]
n–1
Mean, x
[SHIFT][x]
[RCL][A]
Sum of square of data, ∑x
[RCL][B]
Sum of data, ∑x
[RCL][C]
Number of data,
[RCL][D]
Sum of square of data, ∑y
[RCL][E]
Sum of data, ∑y
[RCL][F]
Sum of data, ∑xy
Performing calculations
The following procedures are used to perform the various
linear regression calculations.
The regression formula is y = A + Bx. The constant term of
regression A, regression coefficient B, correlation r,
estimated value of x, and estimated value of y are
calculated as shown below:
A = ( ∑y∑x )/n
B = ( n∑xy∑x∑y ) / ( n∑x
2
r = ( n∑xy∑x∑y ) / √ (( n∑x
y = A + Bx
x = ( yA) / B
– 27 –
Example
Operation
Temperature and length
[MODE][3][1]
of a steel bar
("REG" then select linear regression)
Temp
Length
[SHIFT][Scl][=]
(Memory cleared)
10[ , ]1003[DT]
10ºC
1003mm
15[ , ]1005[DT]
15ºC
1005mm
20[ , ]1010[DT]
20ºC
1010mm
25[ , ]1011[DT]
25ºC
1011mm
30ºC
1014mm
30[ , ]1014[DT]
Using this table, the
[SHIFT][A][=]
(Constant term A)
regression formula and
[SHIFT][B][=]
(Regression coefficient B)
correlation coefficient
can be obtained. Based
[SHIFT][r][=]
(Correlation coefficient r)
Result
on the coefficient
formula, the length of
18[SHIFT][y]
n
(Length at 18ºC)
the steel bar at 18ºC
1000[SHIFT][x]
n–1
(Temp at 1000mm)
and the temperature
[SHIFT][r][x
2
][=]
(Critical coefficient)
2
at 1000mm can be
estimated. Furthermore
[(][RCL][F][–][RCL][C][]
the critical coefficient
[SHIFT][x][][SHIFT][y][)][]
r
(
2
) and covariance can
[(][RCL][C][–]1[)][=]
(Covariance)
also be calculated.
n
= √(∑(x
x)
2
/
)
i
n
Logarithmic regression
n
= √(∑(x
x)
2
/(
-
))
Logarithmic regression calculations are carried out using
n–1
i
1
the following formula:
y = A + B•lnx
Data input
Display
Press [MODE] [3] [2] to specify logarithmic regression
0.
under "REG" mode.
(SD Mode)
Press [SHIFT] [Scl] [=] to clear the statistical memories.
0.
(Memory cleared)
Input data in the following format: <x data>, <y data>
[DT]
• To make multiple entries of the same data, follow
52.
8.
procedures described for linear regression.
(Number of data)
Deleting input data
427.
(Sumof data)
22805.
To delete input data, follow the procedures described for
(Sum of square of data)
53.375
linear regression.
(Mean)
][=]
1.316956719
n
(Population SD)
][=]
1.407885953
n–1
(Sample SD)
]
n–1
1.982142857
(Sample variance)
– 28 –
– 32 –
Performing calculations
The logarithmic regression formula y = A + B•lnx. As x is
input, In(x) will be stored instead of x itself. Hence, we can
treat the logarithmic regression formula same as the
linear regression formula. Therefore, the formulas for
constant term A, regression coefficient B and correlation
coefficient r are identical for logarithmic and linear
regression.
3
Example
Operation
xi
yi
[MODE][3][2]
29
1.6
("REG" then select LOG regression)
50
23.5
[SHIFT][Scl][=]
(Memory cleared)
3
74
38
29[ , ]1.6[DT]
103
46.4
50[ , ]23.5[DT]
118
48.9
74[ , ]38[DT]
The logarithmic
103[ , ]46.4[DT]
regression of the above
118[ , ]48.9[DT]
data, the regression
formula and correlation
[SHIFT][A][=]
(Constant term A)
coefficient are obtained.
[SHIFT][B][=]
(Regression coefficient B)
Furthermore, respective
[SHIFT][r][=]
(Correlation coefficient r)
3
estimated values y and
80[SHIFT][y]
x can be obtained for
(y when xi=80)
xi = 80 and yi = 73 using
73[SHIFT][x]
(x when yi=73)
the regression formula.
A number of logarithmic regression calculation results
differ from those produced by linear regression. Note the
following:
Linear regression Logarithmic regression
∑x
∑Inx
∑x
2
∑(Inx)
2
∑xy
∑y•Inx
Exponential regression
Exponential regression calculations are carried out using
the following formula:
e
B•x
y = A•
(ln y = ln A +Bx)
Data input
Press [MODE] [3] [3] to specify exponential regression
under the "REG" mode.
Press [SHIFT] [Scl] [=] to clear the statistical memories.
Input data in the following format: <x data>,<y data> [DT]
• To make multiple entries of the same data, follow
procedures described for linear regression.
Deleting input data
To delete input data, follow the procedures described for
linear regression.
– 29 –
– 33 –
Performing calculations
If we assume that lny = y and lnA = a', the exponential
e
B•x
regression formula y = A•
(ln y = ln A +Bx) becomes
the linear regression formula y =a' + bx if we store In(y)
instead of y itself. Therefore, the formulas for constant
term A, regression coefficient B and correlation coefficient
r are identical for exponential and linear regression.
A number of exponential regression calculation results
differ from those produced by linear regression. Note the
following:
Linear regression Exponential regression
∑y
∑Iny
∑y
2
∑(Iny)
2
∑xy
∑x•Iny
Example
Operation
xi
yi
[MODE][3][3]
6.9
21.4
("REG" then select Exp regression)
12.9
15.7
[SHIFT][Scl][=]
(Memory cleared)
19.8
12.1
6.9[ , ]21.4[DT]
26.7
8.5
12.9[ , ]15.7[DT]
35.1
5.2
19.8[ , ]12.1[DT]
Through exponential
26.7[ , ]8.5[DT]
regression of the above
35.1[ , ]5.2[DT]
data, the regression
formula and correlation
[SHIFT][A][=]
(Constant term A)
coefficient are obtained.
[SHIFT][B][=]
Furthermore, the
(Regression coefficient B)
regression formula is
[SHIFT][r][=]
used to obtain the
(Correlation coefficient r)
respective estimated
values of y and x, when
16[SHIFT][y]
(y when xi=16)
xi = 16 and yi = 20.
20[SHIFT][x]
(x when yi=20)
Power regression
Power regression calculations are carried out using the
following formula:
x
x
y = A•
B
(lny = lnA + Bln
)
Data input
Press [MODE] [3] [4] [1] to specify "power regression".
Press [SHIFT] [Scl] [=] to clear the statistical memories.
Input data in the following format: <x data>,<y data> [DT]
• To make multiple entries of the same data, follow
procedures described for linear regression.
Deleting input data
To delete input data, follow the procedures described for
linear regression
– 30 –
– 34 –
Performing calculations
If we assume that lny = y, lnA =a' and ln
x
regression formula y = A•
B
(lny = lnA + Bln
the linear regression formula y = a' + b
x
and y themselves. Therefore, the
and In(y) instead of
formulas for constant term A, regression coefficient B and
correlation coefficient r are identical the power and linear
regression.
A number of power regression calculation results differ
n
from those produced by linear regression. Note the
following:
n–1
Linear regression Power regression
n
∑x
∑Inx
n–1
2
2
∑x
∑(Inx)
∑y
∑Iny
2
∑y
2
∑(Iny)
2
n
∑xy
∑Inx•Iny
2
Example
Operation
xi
yi
[MODE][3][4][1]
28
2410
("REG" then select Pwr regression)
30
3033
[SHIFT][Scl][=]
(Memory cleared)
33
3895
28[ , ]2410[DT]
35
4491
30[ , ]3033[DT]
38
5717
33[ , ]3895[DT]
Through power
35[ , ]4491[DT]
regression of the above
data, the regression
38[ , ]5717[DT]
formula and correlation
[SHIFT][A][=]
(Constant term A)
coefficient are obtained.
[SHIFT][B][=]
Furthermore, the
(Regression coefficient B)
regression formula is
[SHIFT][r][=]
used to obtain the
(Correlation coefficient r)
(∑x )
2
)
respective estimated
)( n∑y
values of y and x, when
40[SHIFT][y]
(y when xi=40)
2
2
2
2
(∑x )
(∑y )
))
xi = 40 and yi = 1000.
1000[SHIFT][x]
(x when yi=1000)
Inverse regression
Power regression calculations are carried out using the
following formula:
y = A + ( B/x )
Data input
Press [MODE] [3] [4] [2] to specify "inverse regression".
Press [SHIFT] [Scl] [=] to clear the statistical memories.
Input data in the following format: <x data>,<y data> [DT]
• To make multiple entries of the same data, follow
procedures described for linear regression.
– 31 –
– 35 –
Deleting input data
Display
To delete input data, follow the procedures described for
0.
linear regression
0.
Performing calculations
10.
If 1/x is stored instead of x itself, the inverse regression
15.
formula y = A + ( B/x ) becomes the linear regression
20.
formula y = a + bx. Therefore, the formulas for constant
25.
term A, regression coefficient B and correlation coefficient
30.
r are identical the power and linear regression.
997.4
A number of inverse regression calculation results differ
0.56
from those produced by linear regression. Note the
following:
0.982607368
Linear regression Inverse regression
1007.48
∑x
∑(1/x)
4.642857143
∑x
2
∑(1/x)
2
0.965517241
∑xy
∑(y/x)
Example
Operation
Display
xi
yi
[MODE][3][4][2]
35.
2
2
("REG" then select Inv regression)
3
3
[SHIFT][Scl][=]
(Memory cleared)
4
4
2[ , ]2[DT]
5
5
3[ , ]3[DT]
6
6
4[ , ]4[DT]
Through inverse
5[ , ]5[DT]
regression of the above
6[ , ]6[DT]
data, the regression
formula and correlation
[SHIFT][A][=]
7.272727272
(Constant term A)
coefficient are obtained.
[SHIFT][B][=]
–11.28526646
Furthermore, the
(Regression coefficient B)
regression formula is
[SHIFT][r][=]
–0.950169098
used to obtain the
(Correlation coefficient r)
respective estimated
values of y and x, when
10[SHIFT][y]
6.144200627
(y when xi=10)
xi = 10 and yi = 9.
9[SHIFT][x]
(x when yi=9)
–6.533575316
– 36 –
Quadratic Regression
Quadratic regression calculations are carried out using the
following formula:
y = A + Bx + Cx
2
Data input
Press [MODE] [3] [4] [3] to specify quadratic regression
under the "REG" mode.
Press [SHIFT] [Scl] [=] to clear the statistical memories.
Input data in this format: <x data>,<y data> [DT]
Display
• To make multiple entries of the same data, follow
0.
procedures described for linear regression.
Deleting input data
0.
To delete input data, follow the procedures described for
29.
linear regression.
50.
74.
Performing calculations
103.
The following procedures are used to perform the various
118.
linear regression calculations.
–111.1283975
The regression formula is y = A + Bx + Cx
2
where A, B, C are
34.02014748
regression coefficients.
0.994013946
y∑x
C = [(n∑x
2
(∑x)
2
) (n∑x
2
2
∑y )(n∑x
3
∑x
2
∑x) (n∑xy
37.94879482
2
2
) (n∑x
4
2
)
2
)(n∑x
3
2
∑x∑y)][(n∑x
(∑x)
(∑x
∑x
∑x)
224.1541314
B = [n∑xy∑x∑yC (n∑x
3
∑x
2
∑x)](n∑x
2
(∑x)
2
)
A = (∑yB∑xC∑x
2
) / n
y, you can recall
To read the value of ∑x
3
, ∑x
4
or ∑x
2
memory [RCL] M, Y and X respectively.
Example
Operation
Display
xi
yi
[MODE][3][4][3]
29
1.6
("REG" then select Quad regression)
50
23.5
[SHIFT][Scl][=]
74
38
29[ , ]1.6[DT]
103
46.4
50[ , ]23.5[DT]
118
48
74[ , ]38[DT]
Through power
103[ , ]46.4[DT]
regression of the above
data, the regression
118[ , ]48[DT]
formula and correlation
[SHIFT][A][=]
–35.59856935
(Constant term A)
coefficient are obtained.
[SHIFT][B][=]
1.495939414
Furthermore, the
(Regression coefficient B)
regression formula is
[SHIFT][C][=]
–6.716296671
used to obtain the
(Regression coefficient C)
respective estimated
values of y and x, when
16[SHIFT][y]
(y when xi=16)
–13.38291067
xi = 16 and yi = 20.
20[SHIFT][x]
when yi=20)
47.14556728
(x
1
[SHIFT][x]
when yi=20)
175.5872105
(x
2
– 37 –
Replacing the Battery
Dim figures on the display of the calculator indicate that
battery power is low. Continued use of the calculator
when the battery is low can result in improper operation.
Replace the battery as soon as possible when display
figures become dim.
To replace the battery:-
• Remove the screws that hold the back cover in place and
then remove the back cover,
• Remove the old battery,
• Wipe off the side of the new battery with a dry, soft cloth.
Load it into the unit with the positive(+) side facing up.
• Replace the battery cover and secure it in place with the
screws.
• Press [ON/AC] to turn power on.
Display
Auto Power Off
0.
Calculator power automatically turns off if you do not
perform any operation for about six minutes. When this
0.
happens, press [ON/AC] to turn power back on.
6.9
12.9
Specifications
19.8
Power supply: AG13 x 2 batteries
26.7
Operating temperature: 0 º ~ 40 º C (32 º F ~ 104 º F)
35.1
30.49758742
–0.049203708
–0.997247351
13.87915739
8.574868045
– 38 –
x
x
=
, the power
x
) becomes
x
x
if we store In(
)
Display
0.
0.
28.
30.
33.
35.
38.
0.238801069
2.771866156
0.998906255
6587.674587
20.26225681
0.
0.
2.
3.
4.
5.
6.
2
]
0.
29.
50.
74.
103.
118.
–03