Texas Instruments TI-36X Pro User Manual page 37

3: 2-Var Stats
4: LinReg ax+b
5: QuadraticReg Fits the second-degree polynomial
6: CubicReg
7: LnReg a+blnx Fits the model equation y=a+b ln(x) to the
8: PwrReg ax^b Fits the model equation y=ax
9: ExpReg ab^x Fits the model equation y=ab
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.
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
y=ax +bx+c to the data. It displays values
for a, b, and c; it also displays a value for
2
R . 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.
Fits the third-degree polynomial
3 2
y=ax +bx +cx+d to the data. It displays
values for a, b, c, and d; it also displays a
2
value for R . For four points, the equation
is a polynomial fit; for five or more, it is a
polynomial regression. At least four points
are required.
data using a least squares fit and
transformed values ln(x) and y. It displays
values for a and b; it also displays values
2
for r and r.
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
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
37
2
and r.
b
to the data
x
to the data
2
and r.
2
and r.