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Texas Instruments TI-36X Pro Manual

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37
3: 2-Var Stats Analyzes paired data from 2 data sets with
2 measured variables—x, the independent
variable, and y, the dependent variable.
Frequency data may be included.
Note: 2-Var Stats also computes a linear
regression and populates the linear
regression results.
4: LinReg ax+b Fits the model equation y=ax+b to the data
using a least-squares fit. It displays values
for a (slope) and b (y-intercept); it also
displays values for r
2
and r.
5: QuadraticReg Fits the second-degree polynomial
y=ax
2
+bx+c to the data. It displays values
for a, b, and c; it also displays a value for
R
2
. 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.
6: CubicReg Fits the third-degree polynomial
y=ax
3
+bx
2
+cx+d to the data. It displays
values for a, b, c, and d; 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.
7: LnReg a+blnx 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; it also displays values
for r
2
and r.
8: PwrReg ax^b
Fits the model equation y=ax
b
to the data
using a least-squares fit and transformed
values ln(x) and ln(y). It displays values for
a and b; it also displays values for r
2
and r.
9: ExpReg ab^x
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; it also displays values for r
2
and r.
… 37 …


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