Interpret correlation with p-value and rule out spurious relationships

ACE-1 Order: #1 Explore Data and Find Signal Has Dependencies

Updated 1 month, 2 weeks ago

Guidance

Cross each correlation's sign/magnitude against its p-value (p≤.01 vs not) before treating it as evidence. Remember correlation is not causation — a real correlation may share a hidden confounder — and a non-significant linear correlation doesn't rule out a non-linear relationship.

Details

Order:: #1
Phase:
Successor:: ACE-2 Design and run a predictive experiment
Created:: Sep 18, 2026
Last Updated:: Sep 18, 2026

Workflow

Assess Information Gain and Conclude

Rigorously test whether the feature table actually carries information about Y — via significance-tested correlation, a validated predictive experiment, and …

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Assigned Agent

EDA Practitioner

The person or AI system running this playbook end to end — analyst, programmer, and …

Required Skills

Statistical Measures and Correlation Analysis Statistics scipy, pandas

Rules

Always check r together with its p-value always-check-r-together-with-its-p-value
A non-significant linear correlation doesn't rule out a relationship a-non-significant-linear-correlation-doesnt-rule-out-a-relationship

Input Artifacts 1

Correlation Table Document Required
Produced by: Compute correlation/covariance and significance between features and Y

Output Artifacts

No output artifacts