Advanced Analytics · TOOL GUIDE

Principal Component Analysis (PCA)

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Understand the method. Use it with confidence.

Dimensionality reduction to identify main patterns. Quantly runs the method against your active analysis context and returns structured results for review and interpretation.

01

When to use it

Use this tool when the question requires multivariate structure, segmentation, simulation, causal-design assumptions, or model explainability.
Use it only when the selected variables and study design match the method's requirements.

02

How to use it

  1. Open the tool from the Quantly Tools panel.
  2. Confirm the active dataset and analysis session.
  3. Set Select Numeric Columns (Required): Choose numeric columns for PCA.
  4. Set Number of Components (Optional) (Optional): Number of components to keep. Default is 2.
  5. Set Scale Data (Optional): Standardize features by removing the mean and scaling to unit variance.
  6. Review optional or advanced settings and keep defaults unless your design requires a change.
  7. Run the tool, inspect warnings and diagnostics, then save or export the result with its assumptions.
03

How to interpret results

Interpret results in the context of preprocessing, tuning choices, stability, validation, and domain knowledge. Complex outputs are sensitive to assumptions and should be checked with alternative specifications.