Texas Instruments TINSPIRE Manual Book page 587
Teacher software guidebook
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Also See for TINSPIRE:
- Software manual (380 pages) ,
- Manual book (230 pages) ,
- Reference manual (164 pages)
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correlation coefficient, R.
Linear Regression (mx+b) (LinRegMx)
y=ax+b to the data using a least-squares fit. It displays values for
and
(y-intercept).
b
Linear Regression (a+bx) (LinRegBx)
y=a+bx to the data using a least-squares fit. It displays values for
(y-intercept),
(slope),
b
Median-Median Line (MedMed)
to the data using the median-median line (resistant line) technique,
calculating the summary points x1, y1, x2, y2, x3, and y3.
Median-Median Line
Quadratic Regression (QuadReg)
polynomial y=ax
For three data points, the equation is a polynomial fit; for four or more,
it is a polynomial regression. At least three data points are required.
Cubic Regression (CubicReg)
3
2
y=ax
+bx
+cx+d to the data. It displays values for
four points, the equation is a polynomial fit; for five or more, it is a
polynomial regression. At least four points are required.
Quartic Regression (QuartReg)
4
3
2
y=ax
+bx
+cx
+dx+e to the data. It displays values for
2
. For five points, the equation is a polynomial fit; for six or more, it is a
R
polynomial regression. At least five points are required.
Power Regression (PowerReg)
the data using a least-squares fit on transformed values ln(x) and ln(y). It
displays values for
Exponential Regression (ExpReg)
the data using a least-squares fit on transformed values x and ln(y). It
displays values for
Logarithmic Regression (LogReg)
y=a+b ln(x) to the data using a least-squares fit on transformed values
ln(x) and y. It displays values for
Sinusoidal Regression (SinReg)
y=a sin(bx+c)+d to the data using an iterative least-squares fit. It displays
values for
,
,
a
b
c
two data points per cycle are required in order to avoid aliased frequency
estimates.
2
, and
.
r
r
displays values for
2
+bx+c to the data. It displays values for
2
,
,
, and
.
a
b
r
r
2
,
,
, and
.
a
b
r
r
, and
. At least four data points are required. At least
d
fits the model equation
fits the model equation
fits the model equation y=mx+b
(slope) and
m
fits the second-degree
fits the third-degree polynomial
fits the fourth-degree polynomial
fits the model equation y=ax b to
fits the model equation y=ab
fits the model equation
2
,
,
, and
.
a
b
r
r
fits the model equation
Using Lists & Spreadsheet
m
a
(y-intercept).
b
,
,
, and
a
b
c
2
,
,
,
, and
a
b
c
d
R
,
,
,
,
a
b
c
d
e
(slope)
2
.
R
. For
, and
x
to
575
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