Causal reasoning identifies cause-and-effect relationships by distinguishing correlation from causation. It’s used in science, business, and AI to predict outcomes, optimize decisions, and test interventions. Researchers, data analysts, and policymakers benefit by designing experiments, improving strategies, and solving real-world problems with evidence-based insights.
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