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Statistical Reference Guide
Fit model
Linear fit
Plotting residuals
Plot the residuals to check the fit and assumptions of the model.
Activate the analysis report worksheet.
On the
Analyse-it
ribbon tab,
in the
Diagnostics
group, click
Residuals
, and then click:
Option
Description
Residual
Plot the residuals.
3-up
Plot the residuals and a histogram and normal plot.
5-up
Plot the residuals, a histogram and normal plot, a sequence plot, and a lag plot.
The analysis task pane, the
Residuals
panel opens.
In the
Residuals
drop-down list, select:
Option
Description
Raw
Plot the raw residual Y - Y fitted.
Standardized
Plot the standardized residual (Y - Y fitted) / SE.
Optional:
To test the normality of the residuals,
On the
Analyse-it
ribbon tab,
in the
Diagnostics
group, click
Test Normality
.
Optional:
To test for autocorrelation amongst the residuals,
On the
Analyse-it
ribbon tab,
in the
Diagnostics
group, click
Test Autocorrelation
.
Click
Recalculate
.
Related concepts
Residual plot
Residuals - normality
Residuals - independence
Available in Analyse-it Editions
Standard edition
Method Validation edition
Quality Control & Improvement edition
Ultimate edition
What is Analyse-it?
What's new?
Administrator's Guide
User's Guide
Statistical Reference Guide
Distribution
Compare groups
Compare pairs
Contingency tables
Correlation and association
Principal component analysis (PCA)
Factor analysis (FA)
Item reliability
Fit model
Linear fit
Simple regression models
Fitting a simple linear regression
Advanced models
Fitting a multiple linear regression
Performing ANOVA
Performing 2-way or higher factorial ANOVA
Performing ANCOVA
Fitting an advanced linear model
Scatter plot
Summary of fit
Parameter estimates
Effect of model hypothesis test
ANOVA table
Predicted against actual Y plot
Lack of Fit
Effect of terms hypothesis test
Effect leverage plot
Effect means
Plotting main effects and interactions
Multiple comparisons
Multiple comparison procedures
Comparing effect means
Residual plot
Residuals - normality
Residuals - independence
Plotting residuals
Outlier and influence plot
Identifying outliers and other influential points
Prediction
Making predictions
Making inverse predictions
Saving variables
Logistic / Probit fit
Study design
Method comparison / Agreement
Measurement systems analysis (MSA)
Reference interval
Diagnostic performance
Survival/Reliability
Control charts
Process capability
Pareto analysis
Study Designs
Bibliography
Version 6.15
Published 18-Apr-2023
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