Texas Instruments TI-86 User Manual

Page 202

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190

Chapter 14: Statistics

14STATS.DOC TI-86, Chap 14, US English Bob Fedorisko Revised: 02/13/01 2:33 PM Printed: 02/13/01 3:04 PM Page 190 of 14

14STATS.DOC TI-86, Chap 14, US English Bob Fedorisko Revised: 02/13/01 2:33 PM Printed: 02/13/01 3:04 PM Page 190 of 14

14STATS.DOC TI-86, Chap 14, US English Bob Fedorisko Revised: 02/13/01 2:33 PM Printed: 02/13/01 3:04 PM Page 190 of 14

LinR

(linear regression) Fits the model equation y=a+bx to the data; displays values for

a

(slope) and

b

(y-intercept)

LnR

(logarithmic regression) Fits the model equation y=a+b ln x to the data using transformed
values ln(x) and y; displays values for

a

and

b

ExpR

(exponential regression) Fits the model equation y=ab

x

to the data using transformed

values x and ln(y); displays values for

a

and

b

; elements in the x-list and y-list elements

must be integers

PwrR

(power regression) Fits the model equation y=ax

b

to the data using transformed values

ln(x) and ln(y); displays values for

a

and

b

SinR

(sinusoidal regression) Fits the model equation y=a¹sin(bx+c)+d to the data; displays
values for

a

,

b

,

c

, and

d

;

SinR

requires at least four data points; it also requires at least

two data points per cycle to avoid aliased frequency estimates

LgstR

(logistic regression) Fits the model equation y=a

à(1+be

cx

)+d to the data; displays

a

,

b

,

c

, and

d

P

2Reg

(quadratic regression) Fits the second-degree polynomial y=ax

2

+bx+c to the data;

displays values for

a

,

b

, and

c

; for three data points, the equation is a polynomial fit; for

four or more, it is a polynomial regression;

P

2Reg

requires at least three data points

P

3Reg

(cubic regression) Fits the third-degree polynomial y=ax

3

+bx

2

+cx+d to the data; displays

values for

a

,

b

,

c

, and

d

; for four points, the equation is a polynomial fit; for five or more, it

is a polynomial regression;

P

3Reg

requires at least four data points

P

4Reg

(quartic regression) Fits the fourth-degree polynomial y=ax

4

+bx

3

+cx

2

+dx+e to the data;

displays values for

a

,

b

,

c

,

d

, and

e

; for five points, the equation is a polynomial fit; for six

or more, it is a polynomial regression;

P

4Reg

requires at least five data points

StReg

(store regression equation) Pastes

StReg(

to the home screen; enter a variable and press

b; the current regression equation is stored to variable

For regression analysis, the
statistical results are
calculated using a least-
squares fit.

SinR

and LgstR are

calculated using an iterative
least-squares fit.

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