Overview

Multivariate methods analyse multiple variables simultaneously and uncover latent structures, natural groups or classification rules in datasets. The four calculators available here cover the most important use cases – from dimensionality reduction to supervised classification.

01
Discover structureReduce variables to fewer dimensions → PCA
02
Latent factorsGemeinsame Ursachen hinter Variablen finden → Factor Analysis
03
Form groupsBeobachtungen nach Ähnlichkeit clustern → Cluster Analysis
04
Separate groupsClassify known groups and assign new cases → LDA

Interaktive Rechner

Method comparison

Criterion 📐 PCA 🔬 Factor Analysis 🔵 Cluster Analysis 🎯 Discriminant Analysis
Objective Dimensionality reduction Latent factors Group formation Group classification
Groups known? – not required – not required – not required ✓ required
Objectivevariable keine keine keine Group membership
Rotation Varimax (optional) Varimax / none – –
Goodness criterion Explained variance KMO, Bartlett Silhouette, WCSS Wilks' Λ, Hit rate
Output Scores, Loadings Loadings, communalities Cluster assignment Classification, DF scores
Typical application Index construction, preprocessing Scale construction, psychometrics Segmentation, taxonomies Credit scoring, diagnostics