Statistics and Data Plots 546
Calc Type Description
OneVar One-variable statistics — Calculates the statistical variables.
TwoVar Two-variable statistics — Calculates the statistical variables.
CubicReg Cubic regression — Fits the data to the third-order
polynomial y=ax
3
+bx
2
+cx+d. You must have at least four
data points.
• For four points, the equation is a polynomial fit.
• For five or more points, it is a polynomial regression.
ExpReg Exponential regression — Fits the data to the model
equation y=ab
x
(where a is the y-intercept) using a least-
squares fit and transformed values x and ln(y).
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
ùe^(cùx))+d and updates all the system statistics
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.
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