Hp SmartCalc 300s Manual de usuario descargar pdf (Pagina 20)

■ Sum sub-menu(sums),Var sub-menu(number of

samples,mean, standard deviatian),and MinMax

sub-menu(maximum value,minmum value)

operations are the same those for linear regression

calculations.

Quadratic Regression Calculation:

• For examples:

All the data be used as follow table:

1.0 1.0 2.1 1.5

1.2

1.1

2.4

1.6

1.5 1.2 2.5

1.7

1.6 1.3 2. 7 1.8

1.9

1.4

3.0 2.0

sK_+cx^:

1:1-VAR, 2:A-rBX

3: -rCX^ 4:lnX ^

5:^'X^ 6:A-B^X

7:A-X^B 8:1/X

STAT

1 ^ 1

' 1

2 1.2

3 1.5

i:2 1

STAT

1:A

3:C

55i2

2:B

4:5^1

6:y

0.7028598638

ISHIFT im(STAT) H(Reg) B

E](B)S

0.2576384379

STAT B

ISHIFT im(STAT) H(Reg) C

)H 0.05610274153

y=3^-xi=?

_____

I staT

rslISHiFT im(STAT) 0(Reg) 3ih

3](xi)H

4.502211457

y= 3-^X2=?

______

I STAT B I

i3llSHIFT imfSTAT) [7](Reg) 3ib

S](^)S -9.094472563

x=2-^y=?

STAT B I

rSIISHIFT im(STAT) [7](Reg) 2y

y)S 1.442547706

Comments for Other Types of Regression

For details about the calculation formula of the

command included in each regression type, refer to

the indicated calculation formulas

For example:

Logarithmic Regression (In X)

y=A+BlnX

A Ey-B-EInx

75— n

p n-Eilnxly-EInxEy

“ n-E(lnx)2-(Elnx)5

V— n-E(lnx)y^ElnxEy

7{n-E(lnxy-(Elnx)2}{n-E)7-(Eyn

A -fci

x=e ®

y-A+Blnx

e Exponential Regression (e" X)

y=Ae“

A=exp(5iny_B^^

D _ xl n y-E x*£ I ny

n£x2-(Ex)2

n*Exlny-ExElny

V{n-Ex2-(i:x)2^{n-i:(|ny)2-(Elny)2}

A lny-ln>A

^=Ae^

ab Exponential Regression (A ■ B~X)

y=AB"

A= ex

B=exp(TSl|n^|^)

nExIny-ExElny

7{n-Ex2-(Ex)2}{n-E(lny)2-{Slny)2}

-----------------------------------SS

-----------------------------------

_lny-

InA

y=AET

Power Regression(A • X B)

y^AX'

A=exp(51yc551iit^

D nEinxInv-Einx'Elnv

n.E(lnxP-(Elnx)2

n-EinxIny-EinxElny

y{n-E(lnx)2(Elnx}^{n.E(lny)2-(Elny)2}

. Iny—InA

x=e^

^=Ax‘

Inverse Regression (1/X)

y=A4

A Tly-BEx’

f- Sxy

VSxxSyy

Sxx=E(x'p-

(Ex')2

Syy=Ey2-%i'

Sxy=E(x')y-^4^

y-A

9=A+i

Comparison Regression Curves

The following example uses the data input in as

following table:

1.0 1.0

2.1

1.5

1.2 1.1 2.4 1.6

1.5

1.2

2.5 1.7

1.6 1.3

2.7

1.8

1.9

1.4

3.0 2.0

Compare the correlation coefficient for logarithmic,

e exponential, ab exponential. Power, and inverse

regression.

1 2 ... 15 16 17 18 19 20 21 22 23 24 25 26 27

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