TI-89 / TI-92 Plus / Voyage™ 200 PLT Statistics with List Editor App † Calc Menu 76
Regressions Menu
Description
† (
Calc) Æ 3:Regressions
The options in the Regressions menu are summarized in the table below. Details about
each option follow.
LinReg(a+bx)
linear regression
Calculates the linear regression, y = a+b*x on lists X and Y.
LinReg(ax+b)
linear regression
Calculates the linear regression, y = a*x+b on lists X and Y.
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.
QuadReg
quadratic regression
Calculates the quadratic polynomial regression, y=a*x^2+b*x+c on lists
X and Y.
CubicReg
cubic regression
Calculates the cubic polynomial regression, y=a*x^3+b*x^2+c*x+d on
lists X and Y.
QuartReg
quartic regression
Calculates the quartic polynomial regression, y =a*x^4+b*x^3+c*
x^2+d*x+e on lists X and Y.
LnReg
logarithmic regression
Calculates the logarithmic regression, y = a+b*ln(x) on lists X and Y.
ExpReg
exponential regression
Calculates the exponential regression, y = a*(b)^x on lists X and Y.
PowerReg
power regression
Calculates the power regression, y = a*(x)^b on lists X and Y.
Logist83
Fits the model equation y=c/(1+a*e^(-bx)) to the data in lists X and Y
using an iterative least-squares fit. It displays values for a,b, and c.
Logistic
logistic regression
Fits the data in lists X and Y to the model equation y=a/(1+b*e^(c*x))+d.
It displays values for a,b, and c.
SinReg
sinusoidal regression
Fits the model equation y=a*sin(bx+c)+d to the data in lists X and Y
using an iterative least-squares fit. It displays values a, b, c, and d. At
least four data points are required. At least two data points per cycle are
required in order to avoid aliased frequency estimates.
MultReg
multiple regression
Calculates multiple linear regression of Y list on X1, X2, . . . , X10 lists.
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