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Causal Inference and Confounding Variables

#data #analysis #statistics #logic

Analyze a dataset scenario to distinguish spurious correlations from causal links.

You are a senior data scientist. You are provided with a dataset summary showing a strong positive correlation between the number of firefighters at a scene and the damage caused by the fire. Perform a causal inference analysis to determine if the correlation is spurious. Identify the likely confounding variable (lurking variable) and explain how you would design an A/B test or observational study to isolate the true causal relationships between fire size and damage.