Texas Instruments NS/CLM/1L1/B Reference Guide - Page 57

Residuals: Resid=y

Page 57 highlights

Output variable stat.bList stat.Resid Description List of regression coefficients, {b0,b1,b3,...}. Residuals of the curves fit y = b0 + b1 · x1 + b2 · x2 + ... MultRegTests MultRegTests Y,X1,X2[,X3[,...[,X10]]] Multiple linear regression t test computes a linear regression on the given data, and provides the F test statistic for linearity. A summary of results is stored in the stat.results variable. (See page 76.) Outputs Catalog > Output variable stat.RegEqn stat.F stat.PVal stat.R2 stat.AdjR2 stat.s stat.DW stat.dfReg stat.SSReg stat.MSReg stat.dfError stat.SSError stat.MSError stat.bList stat.tList stat.PList stat.SEList y stat. List stat.Resid stat.sResid stat.CookDist stat.Leverage Description Regression Equation: b0+b1·x1+b2·x2+ ... Global F test statistic. Least probability at which the null hypothesis can be rejected. Coefficient of multiple determination. Adjusted coefficient of multiple determination. Standard deviation of the error. Durbin-Watson statistic; used to determine whether first-order auto correlation is present in the model. Regression degrees of freedom. Regression sum of squares. Regression mean square. error degrees of freedom error sum of squares error MEan square {b0,b1,...} List of coefficients of the regression equation ? = b0+b1·x1+... y list of t statistics for each coefficient in (B List) list of probability values for each t statistic list of SE slopes of each coefficient in B yList = b0+b1·x1+ . . . y y - list y Residuals: Resid=y - list Cook's distance; measure of the influence of an observation based on the residual and leverage Measure of how far the values of the independent variable are from their mean values TI-Nspire™ Reference Guide 51

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TI-Nspire™ Reference Guide
51
Outputs
stat.bList
List of regression coefficients, {b0,b1,b3,...}.
stat.Resid
Residuals of the curves fit y = b0 + b1
·
x1 + b2
·
x2 + ...
MultRegTests
Catalog >
MultRegTests
Y
,
X1
,
X2
[
,
X3
[
,
...[
,
X10
]]]
Multiple linear regression
t
test computes a linear regression on the
given data, and provides the
F
test statistic for linearity. A summary
of results is stored in the
stat.results
variable. (See page 76.)
Output variable
Description
stat.RegEqn
Regression Equation: b0+b1
·
x1+b2
·
x2+ ...
stat.
F
Global
F
test statistic.
stat.PVal
Least probability at which the null hypothesis can be rejected.
stat.R
2
Coefficient of multiple determination.
stat.AdjR
2
Adjusted coefficient of multiple determination.
stat.s
Standard deviation of the error.
stat.DW
Durbin-Watson statistic; used to determine whether first-order auto correlation is present in the model.
stat.dfReg
Regression degrees of freedom.
stat.SSReg
Regression sum of squares.
stat.MSReg
Regression mean square.
stat.dfError
error degrees of freedom
stat.SSError
error sum of squares
stat.MSError
error MEan square
stat.bList
{b0,b1,...}
List of coefficients of the regression equation ? = b0+b1
·
x1+...
stat.tList
list of t statistics for each coefficient in
y
(B List)
stat.PList
list of probability values for each t statistic
stat.SEList
list of SE slopes of each coefficient in B
stat.
y
List
y
List = b0+b1
·
x1+ . . .
stat.Resid
y -
y
list
stat.sResid
Residuals: Resid=y -
y
list
stat.CookDist
Cook’s distance; measure of the influence of an observation based on the residual and leverage
stat.Leverage
Measure of how far the values of the independent variable are from their mean values
Output variable
Description