12–26 Statistics
82D315~1.DOC TI-83 international English Bob Fedorisko Revised: 10/26/05 1:36 PM Printed: 10/27/05 2:53
PM Page 26 of 38
CubicReg (cubic regression) fits the third-degree polynomial
y=ax
3
+bx
2
+cx+d to the data. It displays values for a, b, c, and
d; when DiagnosticOn is set, it also displays a value for R
2
. For
four points, the equation is a polynomial fit; for five or more, it
is a polynomial regression. At least four points are required.
CubicReg [Xlistname,Ylistname,freqlist,regequ]
QuartReg (quartic regression) fits the fourth-degree polynomial
y=ax
4
+bx
3
+cx
2
+dx+e to the data. It displays values for a, b, c,
d, and e; when DiagnosticOn is set, it also displays a value for
R
2
. For five points, the equation is a polynomial fit; for six or
more, it is a polynomial regression. At least five points are
required.
QuartReg [Xlistname,Ylistname,freqlist,regequ]
LinReg(a+bx) (linear regression) fits the model equation y=a+bx
to the data using a least-squares fit. It displays values for
a
(y-intercept) and b (slope); when DiagnosticOn is set, it also
displays values for
r
2
and r.
LinReg(a+bx) [Xlistname,Ylistname,freqlist,regequ]
LnReg (logarithmic regression) fits the model equation
y=a+b ln(x) to the data using a least-squares fit and transformed
values ln(x) and y. It displays values for
a and b; when
DiagnosticOn is set, it also displays values for r
2
and r.
LnReg [Xlistname,Ylistname,freqlist,regequ]
ExpReg (exponential regression) fits the model equation y=ab
x
to
the data using a least-squares fit and transformed values x and
ln(y). It displays values for
a and b; when DiagnosticOn is set, it
also displays values for
r
2
and r.
ExpReg [Xlistname,Ylistname,freqlist,regequ]
STAT CALC Menu (continued)
CubicReg
(ax
3
+bx
2
+cx+d)
QuartReg
(ax
4
+bx
3
+cx
2
+
dx+e)
LinReg
(a+bx)
LnReg
(a+b ln(x))
ExpReg
(ab
x
)
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