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Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed.
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Search interest data over the past 12 months indicates that this topic periodically attracts global attention. Sudden spikes often correlate with major news events, public statements, or geopolitical developments.