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RAISINS-Cluster Analysis Module

Discover R A I S I N S (R & AI Solutions in INferential Statistics) - your ultimate tool for mastering Cluster Analysis! Effortlessly upload your data and unlock instant, polished tables tailored for your analysis. Dive deeper with stunning advanced plots, and explore automated table interpretations. Transform complex stats into clear, actionable results with ease!

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Cluster Analysis (Hierarchical)



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Developed by
STATOBERRY LLP
Author: Chief Statistician
© All rights reserved to STATOBERRY LLP


Heirarchical Clustering













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Heatmap Interpretation



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Hierarchical clustering on principal components (HCPC) is a hybrid approach that combines the strengths of principal component analysis (PCA) and hierarchical clustering. PCA first reduces the dimensionality of the dataset by summarizing correlated variables into a smaller set of uncorrelated components that retain most of the original variance. Then, hierarchical clustering is performed on these principal components instead of the raw variables, which enhances the separation of clusters and reduces noise caused by variable correlations. This method is particularly useful for visualizing and identifying meaningful groupings in complex multivariate datasets, as it simplifies interpretation while preserving the main structure of the data.




Factor Map Interpretation







Chord Diagram Interpretation








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CSV Data File Creator for Cluster Analysis






This is a user-friendly platform where you can generate CSV files for Cluster Analysis.

Enter the number of variables and observations in the sidebar panel. Upon submission, a table will appear in the main panel, where you can enter or paste numeric data.

You can copy numeric data from Excel and paste using Ctrl+V (non-numeric values will be ignored).

After entering data, download the CSV file and upload it in the analysis tab for Cluster Analysis.

This tool simplifies data entry and manipulation for efficient analysis.



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