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RAISINS- Canonical Correlation Analysis Module
Discover R A I S I N S (R & AI Solutions in INferential Statistics) - your dedicated platform for performing Canonical Correlation Analysis (CCA) with ease and confidence. Simply upload your data to explore the multivariate relationships between two sets of variables through comprehensive canonical correlation tables that clearly present canonical correlations, significance tests, and variable contributions. Explore intuitive visualizations to better understand the complex associations between your variable sets.
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The module is a part of RAISINS Software ©
STATOBERRY LLP
Canonical Correlation Analysis
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Developed by
Team RAISINS, STATOBERRY LLP
Author: Chief Statistician
© All rights reserved to STATOBERRY LLP
Scatter Plot
canonical Biplot
Loadings Heatmap
Network Biplot
Scree Plot
Canonical Variates Scatter Plot (U vs V)
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Customize Your Plot
Scree Plot (Squared Canonical Correlations)
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Scree Plot Settings
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CCA Canonical Biplot
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CCA Biplot Settings
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Joint biplot: X and Y variables are shown simultaneously. Axis labels update automatically based on the selected canonical variates.
Biplot Scaling
Unit Circle
Variables inside the circle have weaker loadings; variables near or outside have stronger loadings.
Variable Filtering
Plot Title
Axis Label Style
Axis labels are generated automatically from the selected canonical variates.
Axis Tick Labels
Group Color Palette
Controls the fill color of observation points. Arrow colors are controlled separately under Variable Arrows.Point Appearance
Point Labels
Arrow Appearance
Variable Labels
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CCA Network Biplot
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Customize Your Network Plot
Network biplot shows observations and variables as nodes, connected by edges representing their canonical relationships.
Variable Node Positioning
Increase amplification to spread variable nodes further from center for better visual separation.
Edge Filtering
Higher threshold = fewer edges shown. Lower values create denser networks.Plot Title
Axis Label Style
Axis labels are generated automatically from the selected canonical variates.
Axis Tick Labels
Observation Node Colors
Controls the fill color of observation nodes by group.Node Appearance
Glow effect adds a subtle halo around nodes for enhanced visual appeal.
Node Labels
Node Appearance
When enabled, variables with stronger loadings appear larger.
Variable Colors
X variables use squares, Y variables use triangles.
Variable Labels
Edge Style
Edge Appearance
Edge Colors
Try different color modes to reveal different aspects of the data structure.
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Heatmap Settings
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Color Palette
Cell Styling
Font Sizes
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CSV Data File Creator for Correlation Analysis
This tool generates clean CSV files for Canonical Correlation Analysis.
Each column represents a variable (X1, X2, X3,...). You may later rename variables in your dataset if required.
Copy and paste numeric values under each variable column using Ctrl+V. Non-numeric values will be ignored automatically.
After entering data, click