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Apple Reference & Present…nuary (Partner) - Disc 2
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The Apple Reference and Presentations Library (Disc 2)(January 1994).iso
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SAS Institute
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US English
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JMP Statistical
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JMP-68K
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JMP Demo 68k
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JMP Demo 68k.rsrc
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STR#_24003.txt
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1994-09-02
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Continuous effects cannot be random
Can save only if all regressors are continuous
This will cause a huge formula.
Tested against reduced model: Y=mean
Tested against reduced model: Y=0
WARNING: Used Synthetic Denominator from Test
WARNING: Non-Testable Contrast
Contrast Specification
Click on + or - to make contrast values.
Contrast Dialog for Effect
Odds Upper
Odds Lower
Odds Ratio
Alpha out-of-range
Specify alpha for 1-alpha Confidence Level
Upper
Lower
Fit: Confidence Intervals
Can't do ChiSquare quantile for confid interval.
Likelihood Ratio Tests
Probability
This could take a long time. Are you sure?
Prob<DW
AutoCorrelation
Number of Obs.
Durbin-Watson
Residual
Whole Model
Singular EMS Matrix
Mixed Response types
Multiple Y's only allowed for continuous measurement type.
X Values
1-Alpha
Upper Limit
Lower Limit
Unable to calculate fiducial interval
At least one Y (or Probability) needs to be specified.
Exactly one missing X needed.
Click/Enter values for
Click/Enter X values. Clear one X to predict.
1-Alpha
Inverse Prediction
Iteration History
Obj-Criterion
Delta-Criterion
Step
Iter
Sequential (Type 1) Tests
Response Contour Plot
Profile Plot
LSMeans
WARNING: Non-Testable Contrast
Add Column
Click and Type Above to form hypothesis test.
Custom Test
Test
Power Details Dialog
Calculations will be done on all combinations
Help
Cancel
Done
Click and Enter 1, 2 or a sequence of values for each:
Inflation
Delta
s [std dev error]
N [Sample Size]
Adjusted Power and Confidence Interval
Solve for Least Significant Value
Solve for Least Significant Number
Solve for Power
AdjPower.05
LSN.05
LSV.05
Power Details
LSV
Least Significant Value
Number(LSN)
Least Significant Number
UpperCL
LowerCL
AdjPower
Delta
Sigma
Number
Alpha
Power
Seq SS
Warning: Std Err calculated with respect to Synthetic Denominator.
Upper CL
Lower CL
ApproxStdErr
Parameter
RMSE
MSE
DFE
Solution
Alpha
Limit
Current
Click Go to start.
Std Dev
Model has no formula
Upper
Lower
Current Value
Reset
Step
Stop
Go
Lock
Nonlinear Fitting Control Panel
Formulas
Loss Variable has no formula.
Loss Formula does not reference Model. It will not be used.
Iteration Log
Confid Limits
Correlation of Estimates
Graph
Can't do F quantile for confid interval.
Non-linear Fitting
Denominator MS Synthesis:
DF Num
MS Num
Tests wrt Random Effects
Denom MS Synthesis
DF Den
MS Den
Test Denominator Synthesis
These estimates based on equating Mean Squares to Expected Value.
Var Comp Est
Component
Variance Component Estimates
plus 1.0 times Residual Error Variance
The Mean Square per row by the Variance Component per column
Expected Mean Squares
Cook’s D Influence
ALERT: Failed to converge—max iterations
ALERT: Failed to converge—step–halving limit
Converged by Gradient
Converged by Objective
Leverage
Pred Formula 
Upper 95% Indiv 
Upper 95% Pred 
StdErr Indiv 
StdErr Resid 
StdErr Pred 
h
Studentized Resid 
Lower 95% Indiv 
Lower 95% Pred 
Residual 
Predicted 
Surface
Poly
 LostDFs
 {Error Effect}
 NonEstimable
 Biased
 Zeroed
 Leverage of 
Pred Formula 
Whole–Model Test
Response:
Polynomial Fit, degree=n
Linear Fit
Help
Done
New Column
EigenStructure
EigenValues and EigenVectors
    Solution is a
Critical Value
Variable
Solution
Degenerate
Minimum
Maximum
SaddlePoint
Response Surface
Prob > F
F Ratio
Numerator DF
Sum of Squares
SS
Prob>|t|
t Ratio
Std Error
Estimate
Contrast
Signif. Prob
Correlation
Bivariate Normal Ellipse P=
Can only handle responses with 2 levels
Y by X
Model Fit
Likelihood Ratio
Test
Max RSq
Observations (or Sum Wgts)
Mean of Response
Root Mean Square Error
RSquare Adj
RSquare
Summary of Fit
Specify Smoothness Value for Spline
Smoothing Spline Fit, lambda=
Sum of Squares Error
R–Square
Predicted 
Residuals 
SSE
Responses should have the same measurement levels.
No Y's selected, or personality unchosen
Polynomial Degree must be between 1 and 5
Effect Attributes
Macros
Effect
Prob>ChiSq
ChiSquare
Nparm
Wald ChiSquare
Prob>ChiSq
ChiSquare
–LogLikelihood
DF
Source
Analysis of LogLikelihood
Observations (or Sum Wgts)
RSquare (U)
Summary of Fit
Singularity Details
Mean
Std Error
Least Sq Mean
Level
Least Squares Means
Prob>|t|
t Ratio
Std Error
Estimate
DF
Term
Parameter Estimates
Total Error
Pure Error
Lack of Fit
C Total
Error
Model
Effect Test
Nparm
Prob>F
F Ratio
Mean Square
Sum of Squares
DF
Source
Analysis of Variance
> Weight >
> Censor >
{RS}
{Variance}
{Random}
Intercept
Model Fit