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Statistical Reference Guide
Principal component analysis (PCA)
Calculating principal components
Reduce the dimensionality of multidimensional data using PCA.
Select a cell in the dataset.
On the
Analyse-it
ribbon tab,
in the
Statistical Analyses
group,
click
Multivariate
, and then click
Principal Components
.
The analysis task pane opens.
In the
Variables
list, select the variables.
Optional:
To highlight the coefficients depending on their sign and magnitude, select the
Color maps
check box.
Optional:
To show a plot of the cumulative variance explained by each principal component, select the
Scree plot
check box.
Click
Calculate
.
To save the computed principal component scores back to the dataset for further analysis, on the
Analyse-it
ribbon tab, click
Save Variable
>
Scores
and select the number of dimensions to store.
Related concepts
Principal components
Scree plot
Color map
Related reference
Dataset layout
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)
Principal components
Scree plot
Calculating principal components
Biplot
Monoplot
Creating a biplot
Creating a correlation monoplot
Factor analysis (FA)
Item reliability
Fit model
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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