🔍 Correlation ≠ Causation
In data science it’s easy to fall into the trap of interpreting relationships that don’t actually exist.
📊 Tools like R or Python let us detect and analyze these spurious correlations, reminding us that data always needs solid context.
💡 The key: combine statistical analysis with critical thinking to avoid drawing misleading conclusions.
More information at the link 👇
Also published on LinkedIn.
