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=a
¹
sin(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
2
Reg
(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
2
Reg
requires at least three data points
P
3
Reg
(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
3
Reg
requires at least four data points
P
4
Reg
(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
4
Reg
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.
