tional attainment `\((x)\)`**

1. **Probability of default on a loan `\((Y)\)`**

1. **Poverty `\((Y)\)` ~ public infrastructure `\((x)\)`**


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# Prediction vs. causal inference

When would .hi[causal inference] be useful (to a policymaker, business executive, individual)? When would .hi-purple[prediction] be useful?

1. **Birth weight `\((Y)\)` ~ air pollution `\((x)\)`**

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   - Causal inference: How strictly should air pollution be regulated?
   - Prediction: What areas might need more prenatal servi