Ativa DS-700 Product Manual - Page 2

Example:

4.12



3.58



6.4 = 21.1496

4.12



3.58



7.1 = 7.6496

[ON/AC] [4] [•] [1] [2] [



]

[3] [•] [5] [8] [



] [6] [•] [4] [=]

[

3

]

[

3

] [

3

] [

3

] [

3

]

[



] [7] [•] [1]

[=]

The replay function is not cleared even when

[ON/AC]

is

pressed or when power is turned OFF, so contents can be

recalled even after

[ON/AC]

is pressed.

Replay function is cleared when mode or operation is

switched.

Error Position Display Function

When an

ERROR

message appears during operation

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

]

key, the ERROR message is cancelled and the cursor moves

to the point where the error was generated.

Example:

14



0



2.3 is input by mistake

[ON/AC] [1] [4] [



] [0] [



]

[2] [.] [3] [=]

[

3

]

(or

[

4

]

)

Correct the input by pressing

[

3

] [SHIFT] [INS] [1]

[=]

Scientific Function

Trigonometric functions and inverse trigonometric

functions

• Be sure to set the unit of angular measurement before

performing

trigonometric

function

and

inverse

trigonometric function calculations.

• The unit of angular measurement (degrees, radians,

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

when power is switched OFF.

Performing Hyperbolic and Inverse Hyperbolic Functions

Logarithmic and Exponential Functions

Coordinate Transformation

• This scientific calculator lets you convert between

rectangular coordinates and polar coordinates, i.e., P(x, y)

↔

P(r,



)

•

Calculation results are stored in variable memory E and

variable memory F.

Contents of variable memory E are

displayed initially.

To display contents of memory F,

press

[RCL] [F]

.

• With polar coordinates,



can be calculated within a

range of –180

º

<



≤

180

º

.

(Calculated range is the same with radians or grads.)

Permutation and Combination

Total number of permutations nPr = n!/(n



r)!

Total number of combinations nCr = n!/(r!(n



r)!)

Other Functions (

√

, x

2

, x

–1

, x!,

3

√

, Ran#)

Fractions

Fractions are input and displayed in the order of integer,

numerator and denominator. Values are automatically

displayed in decimal format whenever the total number of

digits of a fractional value (interger + numerator +

denominator + separator marks) exceeds 10.

Degree, Radian, Gradient Interconversion

Degree, radian and gradient can be converted to each

other with the use of

[SHIFT][DRG>]

.

Once

[SHIFT]

[DRG>]

have been keyed in,

the

"DRG"

selection menu

will be shown as follows.

Degrees, Minutes, Seconds Calculations

You can perform sexagesimal calculations using degrees

(hours), minutes and seconds. And convert between

sexagesimal and decimal values.

Statistical Calculations

This unit can be used to make statistical calculations

including standard deviation in the

"SD"

mode, and

regression calculation in the

"REG"

mode.

Standard Deviation

In the

"SD"

mode, calculations including 2 types of

standard deviation formulas, mean, number of data, sum

of data, and sum of square can be performed.

Data input

1. Press

[MODE] [2]

to specify

SD

mode.

2. Press

[SHIFT] [Scl] [=]

to clear the statistical memories.

3. Input data, pressing

[DT]

key (=

[M+]

) each time a new

piece of data is entered.

Example

Data: 10, 20, 30

Key operation: 10

[DT]

20

[DT]

30

[DT]

•

When multiples of the same data are input, two different

entry methods are possible.

Example 1

Data: 10, 20, 20, 30

Key operation: 10

[DT]

20

[DT] [DT]

30

[DT]

The previously entered data is entered again each time

the DT is pressed without entering data (in this case 20

is re-entered).

Example 2

Data: 10, 20, 20, 20, 20, 20, 20, 30

Key operation: 10

[DT]

20

[SHIFT]

[;]

6

[DT]

30

[DT]

By pressing

[SHIFT]

and then entering a semicolon

followed by value that represents the number of items the

data is repeated (6, in this case) and the

[DT]

key, the

multiple data entries (for 20, in this case) are made

automatically.

Deleting input data

There are various ways to delete value data, depending on

how and where it was entered.

Example 1

40

[DT]

20

[DT]

30

[DT]

50

[DT]

To delete 50, press

[SHIFT] [CL]

.

Example 2

40

[DT]

20

[DT]

30

[DT]

50

[DT]

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]

.

Example 5

30

[DT]

50

[DT]

120

[SHIFT] [;]

31

[DT]

To delete 120

[SHIFT] [;]

31

[DT]

, press

[SHIFT] [CL]

.

Example 6

50

[DT]

120

[SHIFT] [;]

31

[DT]

40

[DT]

30

[DT]

To delete 120

[SHIFT] [;]

31

[DT]

, press 120

[SHIFT] [;]

31

[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.

Standard deviation and mean calculations are performed

as shown below:

Population standard deviation

σ

n

=

√

(

∑

(

x

i



x

)

2

/

n

)

where

i

= 1 to

n

Sample standard deviation

σ

n–1

=

√

(

∑

(

x

i



x

)

2

/(

n

-

1

))

where

i

= 1 to

n

Mean

x

= (

∑

x

)/

n

Regression Calculation

In the REG mode, calculations including linear regression,

logarithmic regression, exponential regression, power

regression, inverse regression and quadratic regression

can be performed.

Press

[MODE] [3]

to enter the

"REG"

mode:

and then select one of the following regression types:-

Lin: linear regression

Log: logarithmic regression

Exp: exponential regression

press

[

4

]

for the other three regression types:-

Pwr: power regression

Inv: inverse regression

Quad: quadratic regression

Linear regression

Linear regression calculations are carried out using the

following formula:

y = A + Bx.

Data input

Press

[MODE] [3] [1]

to specify linear regression under

the

"REG"

mode.

Press

[Shift] [Scl] [=]


Input data in the following format: <x data> [,] <y data>

[DT]

• When multiples of the same data are input, two different

entry methods are possible:

Example 1

Data: 10/20, 20/30, 20/30, 40/50

Key operation: 10 [,]

20 [DT]

20 [,]

30 [DT] [DT]

40 [,]

50 [DT]

The previously entered data is entered again each time

the

[DT]

key is pressed (in this case 20/30 is re-entered).

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

followed by a value that represents the number of times

the data is repeated (5, in this case) and the

[DT]

key, the

multiple data entries (for 20/30, in this case) are made

automatically.

Deleting input data

There are various ways to delete value data, depending on

how and where it was entered.

Example 1

10 [,]

40 [DT]

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]

40 [,]

50 [DT]

To delete 40 [,] 50 [DT], press

[SHIFT][CL]

Example 3

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]

Key Operations to recall regression calculation results



linear regression calculations.

The regression formula is y = A + B

x

. 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



(

∑

x

)

2

)

r

= (

n

∑

xy



∑

x

∑

y

) /

√

((

n

∑

x

2



(

∑

x

)

2

)(

n

∑

y

2



(

∑

y

)

2

))

y

= A + B

x

x

= (

y



A) / B

Logarithmic regression

Logarithmic regression calculations are carried out using

the following formula:

y

= A + B•ln

x

Data input

Press

[MODE] [3] [2]

to specify logarithmic regression

under

"REG"

mode.

Press

[SHIFT] [Scl] [=]


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.


The logarithmic regression formula

y

= A + B•ln

x

.

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.

A number of logarithmic regression calculation results

differ from those produced by linear regression. Note the

following:

Exponential regression

Exponential regression calculations are carried out using

the following formula:

y

= A•

e

B•x

(ln

y

= ln A +

Bx

)

Data input

Press

[MODE] [3]

[3]

to specify exponential regression

under the

"REG"

mode.

Press

[SHIFT] [Scl] [=]


Input data in the following format: <x data>,<y data> [DT]



Deleting input data


linear regression.


If we assume that ln

y

=

y

and lnA = a', the exponential

regression formula

y

= A•

e

B•x

(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:

Power regression

Power regression calculations are carried out using the

following formula:

y

= A•

x

B

(ln

y

= lnA + Bln

x

)

Data input

Press

[MODE] [3] [

4

] [1]

to specify "power regression".

Press

[SHIFT] [Scl] [=]





Deleting input data


linear regression


If we assume that ln

y

=

y

, lnA =a' and ln

x

=

x

, the power

regression formula

y

= A•

x

B

(ln

y

= lnA + Bln

x

) becomes

the linear regression formula

y

= a' + b

x

if we store In(

x

)

and In(

y

) instead of

x

and

y

themselves. Therefore, the

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

from those produced by linear regression. Note the

following:

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] [=]





Deleting input data


linear regression


If 1/

x

is stored instead of

x

itself,

the inverse regression

formula

y

= A + ( B/

x

) becomes the linear regression

formula

y

= a + b

x

. Therefore, the formulas for constant

term A, regression coefficient B and correlation coefficient

r

are identical the power and linear regression.

A number of inverse regression calculation results differ

from those produced by linear regression. Note the

following:

Quadratic Regression

Quadratic regression calculations are carried out using the

following formula:

y = A + B

x

+ C

x

2

Data input

Press

[MODE] [3] [

4

] [3]

to specify quadratic regression

under the

"REG"

mode.

Press

[SHIFT] [Scl] [=]


Input data in this format: <x data>,<y data> [DT]



Deleting input data


linear regression.



linear regression calculations.

The regression formula is y = A + B

x

+ C

x

2

where A, B, C are

regression coefficients.

C = [(

n

∑

x

2



(

∑

x

)

2

) (

n

∑

x

2

y



∑

x

2

∑

y

)



(

n

∑

x

3



∑

x

2

∑

x

) (

n

∑

xy



∑

x

∑

y

)]



[(

n

∑

x

2



(

∑

x

)

2

) (

n

∑

x

4



(

∑

x

2

)

2

)



(

n

∑

x

3



∑

x

2

∑

x

)

2

]

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

To read the value of

∑

x

3

,

∑

x

4

or

∑

x

2

y

, you can recall

memory [RCL] M, Y and X respectively.

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.

Auto Power Off

Calculator power automatically turns off if you do not

perform any operation for about six minutes. When this

happens, press

[ON/AC]

to turn power back on.

Specifications

Power supply:

AG13 x 2 batteries

Operating temperature: 0

º

~ 40

º

C (32

º

F ~ 104

º

F)

– 20 –

– 24 –

– 28 –

– 32 –

– 36 –

– 21 –

– 25 –

– 29 –

– 33 –

– 37 –

– 22 –

– 26 –

– 30 –

– 34 –

– 38 –

– 23 –

– 27 –

– 31 –

– 35 –

Display

Example

Operation

(Lower)

sin 63

º

52'41"

= 0.897859012

cos (

π

/3 rad) = 0.5

tan (–35 grad)

= –0.612800788

2sin45

º



cos65

º

= 0.597672477

sin

–1

0.5 = 30

cos

–1

(

√

2/2)

= 0.785398163 rad

=

π

/4 rad

tan

–1

0.741

= 36.53844577

º

= 36

º

32' 18.4"

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)

= 68

º

13'13.53"

[

MODE

][

MODE

][1]

("DEG" selected)

[sin] 63 [

º

' "] 52 [

º

' "]

41 [

º

' "][=]

[

MODE

][

MODE

][2]

("RAD" selected)

[cos][(] [

SHIFT

][

π

][



]3

[)] [=]

[

MODE

][

MODE

][3]

("GRA" selected)

[tan] [(–)] 35 [=]

[

MODE

][

MODE

][1]

("DEG")

2[sin] 45 [cos] 65 [=]

[

SHIFT

][sin

–1

] 0.5 [=]

[

MODE

][

MODE

][2]

("RAD")

[

SHIFT

][cos

–1

][(][

√

]2 [



]2

[)][=]

[



][

SHIFT

][

π

][=]

[

MODE

][

MODE

][1]

("DEG")

[

SHIFT

][tan

–1

]0.741[=]

[

SHIFT

] [

←

º' "]

2.5[



] [(] [

SHIFT

] [sin

–1

]0.8

[



] [

SHIFT

] [cos

–1

] 0.9 [)]

[=] [

SHIFT

] [

←

º' "]

0.897859012

0.5

–0.612800788

0.597672477

30.

0.785398163

0.25

36.53844576

36

º

32

º

18.4

º

68

º

13

º

13.53

º

4.12x3.58+6.

21.1496

D

4.12x3.58–7.

7.6496

D

Ma ERROR

12x3.58+6.4

_

21.1496

D

12x3.58–7.1

_

21.1496

D

14

÷

10x2.3

0.

D

14

÷

10x2.3

3.22

D

Display

Example

Operation

(Lower)

log1.23

= 8.9905111



10

–2

In90 = 4.49980967

log456



In456

= 0.434294481

10

1.23

= 16.98243652

e

4.5

= 90.0171313

10

4

• e

–4



1.2 • 10

2.3

= 422.5878667

(–3)

4

= 81

–3

4

= –81

5.6

2.3

= 52.58143837

7

√

123 = 1.988647795

(78



23)

–12

= 1.305111829



10

–21

2



3



3

√

64



4 = 10

2



3.4

(5+6.7)

= 3306232

[log] 1.23 [=]

[In] 90 [=]

[log]456



[In]456 [=]

[

SHIFT

][10

x

] 1.23 [=]

[

SHIFT

][e

x

]4.5[=]

[

SHIFT

][10

x

]4[



][

SHIFT

][e

x

]

[(–)]4[



]1.2[



][

SHIFT

][10

x

]

2.3[=]

[(][(–)] 3 [)] [x

y

] 4 [=]

[(–)] 3 [x

y

] 4 [=]

5.6 [x

y

] 2.3 [=]

7 [

SHIFT

][

x

√

] 123 [=]

[(]78[



]23[)][x

y

][(–)]12[=]

2[



]3[



]3[

SHIFT

][

x

√

]64

[



]4[=]

2[



]3.4[x

y

][(]5[



]6.7[)][=]

0.089905111

4.49980967

0.434294481

16.98243652

90.0171313

422.5878667

81.

–81.

52.58143837

1.988647795

1.305111829

–21

10.

3306232.001

Display

Example

Operation

(Lower)

sinh3.6= 18.28545536

cosh1.23 = 1.856761057

tanh2.5= 0.986614298

cosh1.5



sinh1.5

= 0.22313016

sinh

–1

30 = 4.094622224

cosh

–1

(20/15)

= 0.795365461

x = (tanh

–1

0.88) / 4

= 0.343941914

sinh

–1

2



cosh

–1

1.5

= 1.389388923

sinh

–1

(2/3)



tanh

–1

(4/5)

= 1.723757406

[hyp][sin] 3.6 [=]

[hyp][cos] 1.23 [=]

[hyp][tan] 2.5 [=]

[hyp][cos] 1.5 [



][hyp]

[sin] 1.5 [=]

[hyp][

SHIFT

][sin

–1

] 30 [=]

[hyp][

SHIFT

][cos

–1

][(] 20

[



] 15 [)][=]

[hyp][

SHIFT

][tan

–1

]0.88

[



]4[=]

[hyp][

SHIFT

][sin

–1

]2[



]

[hyp][

SHIFT

][cos

–1

]1.5[=]

[hyp][

SHIFT

][sin

–1

][(]2[



]

3[)][



][hyp][

SHIFT

][tan

–1

]

[(]4[



]5[)][=]

18.28545536

1.856761057

0.986614298

0.22313016

4.094622224

0.795365461

0.343941914

1.389388923

1.723757406

Display

Example

Operation

(Lower)

x=14 and y=20.7, what

are r and



º

?

x=7.5 and y=–10, what

are r and



rad?

r=25 and



= 56

º

, what

are x and y?

r=4.5 and =2

π

/3 rad,

what are x and y?

[

MODE

][

MODE

][1]

("DEG" selected)

[Pol(]14 [

,

]20.7[)][=]

[RCL][F]

[

SHIFT

][

←

º' "]

[

MODE

][

MODE

][2]

("RAD" selected)

[

Pol(

]

7.5

[

,

][(–)]

10

[)][=]

[RCL][F]

[

MODE

][

MODE

][1]

("DEG" selected)

[

SHIFT

][Rec(]25 [

,

]56[)][=]

[RCL][F]

[

MODE

][

MODE

][2]

("RAD" selected)

[

SHIFT

][Rec(]4.5[

,

][(]2[



]

3[



][

SHIFT

][

π

][)][)][=]

[RCL][F]

24.98979792(r)

55.92839019(



)

55

º

55

º

42.2(



)

12.5(r)

–0.927295218

(



)

13.97982259(x)

20.72593931(y)

–2.25(x)

3.897114317(y)

Example

Operation

Display

Define degree first

Change 20 radian to

degree

To perform the following

calculation :-

10 radians+25.5 gradients

The answer is expressed

in degree.

[

MODE

][

MODE

][1]

("DEG" selected)

20[

SHIFT

][DRG>][2][=]

10[

SHIFT

][DRG>][2]

[



]25.5[

SHIFT

][DRG>][3]

[=]

20

r

1145.91559

10

r



25.5

g

595.9077951

Example

Operation

Display

To express 2.258 degrees

in deg/min/sec.

To perform the calculation:

12

º

34'56"



3.45

2.258[º' "][=]

12[º' "]34[º' "]56[º' "][



]

3.45[=]

2

º

15

º

28.8

43

º

24

º

31.2

Display

Example

Operation

(Lower)

Taking any four out of

ten items and arranging

them in a row, how many

different arrangements

are possible?

10

P

4

= 5040

10[

SHIFT

][nPr]4[=]

5040.

Display

Example

Operation

(Lower)

Using any four numbers

from 1 to 7, how many

four digit even numbers

can be formed if none of

the four digits consist of

the same number?

(3/7 of the total number

of permutations will be

even.)

7

P

4



3



7 = 360

If any four items are

removed from a total

of 10 items, how many

different combinations

of four items are

possible?

10

C

4

= 210

If 5 class officers are

being selected for a

class of 15 boys and

10 girls, how many

combinations are

possible? At least one

girl must be included

in each group.

25

C

5



15

C

5

= 50127

7[

SHIFT

][nPr]4[



]3[



]

7[=]

10[nCr]4[=]

25[nCr]5[



]15[nCr]5[=]

360.

210.

50127.

Display

Example

Operation

(Lower)

√

2



√

5 = 3.65028154

2

2



3

2



4

2



5

2

= 54

(



3)

2

= 9

1/(1/3–1/4) = 12

8! = 40320

3

√

(36



42



49) = 42

Random number

generation (number is

in the range of 0.000 to

0.999)

[

√

]2[



][

√

]5[=]

2[x

2

][



]3[x

2

][



]4[x

2

]

[



]5[x

2

][=]

[(][(–)]3[)][x

2

][=]

[(]3[x

–1

][



]4[x

–1

][)][x

–1

][=]

8[

SHIFT

][x!][=]

[

3

√

][(]36[



]42[



]49[)][=]

[

SHIFT

][Ran#][=]

3.65028154

54.

9.

12.

40320.

42.

0.792

(random)

Display

Example

Operation

(Lower)

2

/

5



3

1

/

4

= 3

13

/

20

3

456

/

78

= 8

11

/

13

1

/

2578



1

/

4572

= 0.00060662

1

/

2



0.5 = 0.25

1

/

3



(–

4

/

5

)–

5

/

6

= –1

1

/

10

1

/

2



1

/

3



1

/

4



1

/

5

=

13

/

60

(

1

/

2

)/

3

=

1

/

6

1

/(

1

/

3



1

/

4

)

= 1

5

/

7

2[a

b

/

c

]5[



]3[a

b

/

c

]1

[a

b

/

c

]4[=]

[a

b

/

c

]

(conversion to decimal)

Fractions can be converted

to decimals, and then

converted back to fractions.

3[a

b

/

c

]456[a

b

/

c

]78[=]

[

SHIFT

][

d

/

c

]

1[a

b

/

c

]2578[



]1[a

b

/

c

]

4572[=]

When the total number

of characters, including

integer, numerator,

denominator and

delimiter mark exceeds

10, the input fraction is

automatically displayed

in decimal format.

1[a

b

/

c

]2[



].5[=]

1[a

b

/

c

]3[



][(–)]4[a

b

/

c

]5

[



]5[a

b

/

c

]6[=]

1[a

b

/

c

]2[



]1[a

b

/

c

]3[



]

1[a

b

/

c

]4[



]1[a

b

/

c

]5[=]

[(]1[a

b

/

c

]2[)][a

b

/

c

]3[=]

1[a

b

/

c

][(]1[a

b

/

c

]3[



]

1[a

b

/

c

]4[)][=]

3

⎦

13

⎦

20.

3.65

8

⎦

11

⎦

13.

115

⎦

13.

6.066202547

–04

0.25

–1

⎦

1

⎦

10.

13

⎦

60.

1

⎦

6.

1

⎦

5

⎦

7.

Display

Example

Operation

(Lower)

√

(1–sin

2

40)

= 0.766044443

1/2!



1/4!



1/6!



1/8!

= 0.543080357

[

MODE

][

MODE

][1]

("DEG" selected)

[

√

][(]1[



][(][sin]40[)][x

2

]

[)][=]

[

SHIFT

][cos

–1

][Ans][=]

2[

SHIFT

][x!][x

–1

][



]

4[

SHIFT

][x!][x

–1

][



]

6[

SHIFT

][x!][x

–1

][



]

8[

SHIFT

][x!][x

–1

][=]

0.766044443

40.

0.543080357

D

R

G

1

2

3

COMP SD REG

1

2

3

Key operation

Result

[

SHIFT

][x

σ

n

]

[

SHIFT

][x

σ

n–1

]

[

SHIFT

][x]

[RCL][A]

[RCL][B]

[RCL][C]

Population standard deviation,

x

σ

n

Sample standard deviation,

x

σ

n–1

Mean,

x

Sum of square of data,

∑

x

2

Sum of data,

∑

x

Number of data,

n

Linear regression

Logarithmic regression

∑

x

∑

x

2

∑

xy

∑

In

x

∑

(In

x

)

2

∑

y

•In

x

Linear regression

Exponential regression

∑

y

∑

y

2

∑

xy

∑

In

y

∑

(In

y

)

2

∑

x

•In

y

Example

Operation

Display

Data 55, 54, 51, 55, 53,

53, 54, 52

What is deviation of the

unbiased variance, and

the mean of the above

data?

[

MODE

][2]

(SD Mode)

[

SHIFT

][Scl][=]

(Memory cleared)

55[DT]54[DT]51[DT]

55[DT]53[DT][DT]54[DT]

52[DT]

[RCL][C]

(Number of data)

[RCL][B]

(Sumof data)

[RCL][A]

(Sum of square of data)

[

SHIFT

][x][=]

(Mean)

[

SHIFT

][x

σ

n

][=]

(Population SD)

[

SHIFT

][x

σ

n–1

][=]

(Sample SD)

[

SHIFT

][x

σ

n–1

]

[x

2

][=]

(Sample variance)

0.

0.

52.

8.

427.

22805.

53.375

1.316956719

1.407885953

1.982142857

Key operation

Result

[

SHIFT

][A][=]

[

SHIFT

][B][=]

[

SHIFT

][C][=]

[

SHIFT

][r][=]

[

SHIFT

][x][=]

[

SHIFT

][y][=]

[

SHIFT

][y

σ

n

]

[

SHIFT

][y

σ

n–1

]

[

SHIFT

][y]

[

SHIFT

][x

σ

n

]

[

SHIFT

][x

σ

n–1

]

[

SHIFT

][x]

[RCL][A]

[RCL][B]

[RCL][C]

[RCL][D]

[RCL][E]

[RCL][F]

Constant term of regression A

Regression coefficient B

Regression coefficient C

Correlation coefficient

r

Estimated value of

x

Estimated value of

y


y

σ

n


y

σ

n–1

Mean,

y


x

σ

n


x

σ

n–1

Mean,

x


∑

x

2

Sum of data,

∑

x

Number of data,

n


∑

y

2

Sum of data,

∑

y

Sum of data,

∑

xy

Linear regression

Inverse regression

∑

x

∑

x

2

∑

xy

∑

(1/

x

)

∑

(1/

x

)

2

∑

(

y

/

x

)

Linear regression

Power regression

∑

x

∑

x

2

∑

y

∑

y

2

∑

xy

∑

In

x

∑

(In

x

)

2

∑

In

y

∑

(In

y

)

2

∑

In

x

•In

y

4.12x3.58+6.

21.1496

D

14

÷

0x2.3

0.

D

Lin Log Exp

1

2

3

Pwr Inv Quad

1

2

3

Example

Operation

Display

xi

yi

29

1.6

50

23.5

74

38

103

46.4

118

48

Through power

regression of the above

data, the regression

formula and correlation

coefficient are obtained.

Furthermore, the

regression formula is

used to obtain the

respective estimated

values of

y

and

x

, when

xi

= 16 and

yi

= 20.

[

MODE

][3][

4

][3]

("REG" then select Quad regression)

[

SHIFT

][Scl][=]

29[

,

]1.6[DT]

50[

,

]23.5[DT]

74[

,

]38[DT]

103[

,

]46.4[DT]

118[

,

]48[DT]

[

SHIFT

][A][=]

(Constant term A)

[

SHIFT

][B][=]

(Regression coefficient B)

[

SHIFT

][C][=]

(Regression coefficient C)

16[

SHIFT

][y]

(

y

when

xi

=16)

20

[

SHIFT

][x]

(

x

1

when

yi

=20)

[

SHIFT

][x]

(

x

2

when

yi

=20)

0.

29.

50.

74.

103.

118.

–35.59856935

1.495939414

–6.716296671

–03

–13.38291067

47.14556728

175.5872105

Example

Operation

Display

xi

yi

2

2

3

3

4

4

5

5

6

6

Through inverse





Furthermore, the


used to obtain the


values of

y

and

x

, when

xi

= 10 and

yi

= 9.

[

MODE

][3][

4

][2]

("REG" then select Inv regression)

[

SHIFT

][Scl][=]

(Memory cleared)

2[

,

]2[DT]

3[

,

]3[DT]

4[

,

]4[DT]

5[

,

]5[DT]

6[

,

]6[DT]

[

SHIFT

][A][=]

(Constant term A)

[

SHIFT

][B][=]


[

SHIFT

][r][=]

(Correlation coefficient

r

)

10[

SHIFT

][y]

(

y

when

xi

=10)

9

[

SHIFT

][x]

(

x

when

yi

=9)

0.

0.

2.

3.

4.

5.

6.

7.272727272

–11.28526646

–0.950169098

6.144200627

–6.533575316

Example

Operation

Display

Temperature and length

of a steel bar

Temp

Length

10ºC

1003mm

15ºC

1005mm

20ºC

1010mm

25ºC

1011mm

30ºC

1014mm

Using this table, the

regression formula and

correlation coefficient

can be obtained. Based

on the coefficient

formula, the length of

the steel bar at 18ºC

and the temperature

at 1000mm can be

estimated. Furthermore

the critical coefficient

(

r

2

) and covariance can

also be calculated.

[

MODE

][3][1]

("REG" then select linear regression)

[

SHIFT

][Scl][=]

(Memory cleared)

10[

,

]1003[DT]

15[

,

]1005[DT]

20[

,

]1010[DT]

25[

,

]1011[DT]

30[

,

]1014[DT]

[

SHIFT

][A][=]

(Constant term A)

[

SHIFT

][B][=]


[

SHIFT

][r][=]


r

)

18[

SHIFT

][y]

(Length at 18ºC)

1000

[

SHIFT

][x]

(Temp at 1

000

mm)

[

SHIFT

][r][x

2

][=]

(Critical coefficient)

[(][RCL][F][–][RCL][C][



]

[

SHIFT

][x][



][

SHIFT

][y][)][



]

[(][

RCL

][

C

][

–

]1[)][=]

(Covariance)

0.

0.

10.

15.

20.

25.

30.

997.4

0.56

0.982607368

1007.48

4.642857143

0.965517241

35.

Example

Operation

Display

xi

yi

29

1.6

50

23.5

74

38

103

46.4

118

48.9

The logarithmic





Furthermore, respective

estimated values y and

x

can be obtained for

xi

= 80 and

yi

= 73 using

the regression formula.

[

MODE

][3][2]

("REG" then select LOG regression)

[

SHIFT

][Scl][=]

(Memory cleared)

29[

,

]1.6[DT]

50[

,

]23.5[DT]

74[

,

]38[DT]

103[

,

]46.4[DT]

118[

,

]48.9[DT]

[

SHIFT

][A][=]

(Constant term A)

[

SHIFT

][B][=]


[

SHIFT

][r][=]


r

)

80[

SHIFT

][y]

(

y

when

xi

=80)

73

[

SHIFT

][x]

(

x

when

yi

=73)

0.

0.

29.

50.

74.

103.

118.

–111.1283975

34.02014748

0.994013946

37.94879482

224.1541314

Example

Operation

Display

xi

yi

6.9

21.4

12.9

15.7

19.8

12.1

26.7

8.5

35.1

5.2

Through exponential





Furthermore, the


used to obtain the


values of

y

and

x

, when

xi

= 16 and

yi

= 20.

[

MODE

][3][3]

("REG" then select Exp regression)

[

SHIFT

][Scl][=]

(Memory cleared)

6.9[

,

]21.4[DT]

12.9[

,

]15.7[DT]

19.8[

,

]12.1[DT]

26.7[

,

]8.5[DT]

35.1[

,

]5.2[DT]

[

SHIFT

][A][=]

(Constant term A)

[

SHIFT

][B][=]


[

SHIFT

][r][=]


r

)

16[

SHIFT

][y]

(

y

when

xi

=16)

20

[

SHIFT

][x]

(

x

when

yi

=20)

0.

0.

6.9

12.9

19.8

26.7

35.1

30.49758742

–0.049203708

–0.997247351

13.87915739

8.574868045

Example

Operation

Display

xi

yi

28

2410

30

3033

33

3895

35

4491

38

5717

Through power





Furthermore, the


used to obtain the


values of

y

and

x

, when

xi

= 40 and

yi

= 1000.

[

MODE

][3][

4

][1]

("REG" then select Pwr regression)

[

SHIFT

][Scl][=]

(Memory cleared)

28[

,

]2410[DT]

30[

,

]3033[DT]

33[

,

]3895[DT]

35[

,

]4491[DT]

38[

,

]5717[DT]

[

SHIFT

][A][=]

(Constant term A)

[

SHIFT

][B][=]


[

SHIFT

][r][=]


r

)

40[

SHIFT

][y]

(

y

when

xi

=40)

1000

[

SHIFT

][x]

(

x

when

yi

=1000)

0.

0.

28.

30.

33.

35.

38.

0.238801069

2.771866156

0.998906255

6587.674587

20.26225681

Ativa DS-700 Product Manual - Page 2

Performing Hyperbolic and Inverse Hyperbolic Functions - 36 scientific calculator

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