Texas Instruments TI-89 Titanium User Manual page 535

Calc Type Description
LinReg Linear regression — Fits the data to the model y=ax+b
(where a is the slope, and b is the y-intercept) using a least-
squares fit and x and y.
LnReg Logarithmic regression — Fits the data to the model
equation y=a+b ln(x) using a least-squares fit and
transformed values ln(x) and y.
Logistic Logistic regression — Fits the data to the model
y=a/(1+b
variables.
MedMed Median-Median — Fits the data to the model y=ax+b (where
a is the slope, and b is the y-intercept) using the median-
median line, which is part of the resistant line technique.
Summary points medx1, medy1, medx2, medy2, medx3,
and medy3 are calculated and stored to variables, but they
are not displayed on the STAT VARS screen.
PowerReg Power regression — Fits the data to the model equation
y=ax
and ln(y).
QuadReg Quadratic regression — Fits the data to the second-order
polynomial y=ax
points.
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•
Statistics and Data Plots
ù ù
e^(c x))+d and updates all the system statistics
b
using a least-squares fit and transformed values ln(x)
2
+bx+c. You must have at least three data
For three points, the equation is a polynomial fit.
For four or more points, it is a polynomial regression.
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