Causal inference uncovers whether one event truly triggers another, moving beyond mere correlation. It is used in medicine, economics, and tech to test treatments or policies. Researchers, data scientists, and decision-makers benefit by making evidence-based choices, improving outcomes in fields from public health to marketing with reliable cause-and-effect insights.
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