kflow for predictive analysis:

1. **Choose** a model.
2. **Train** the model (estimate its parameters).
3. **Assess** its performance.
4. Repeat steps 1-3 for different models, and choose the **best** model.

&lt;!-- -- --&gt;

&lt;!-- .qa[Q] Why don't we do this for causal inference? --&gt;
&lt;!-- - In causal inference, the best model is determined by outside knowledge (i.e., which research design is most plausible). --&gt;
&lt;!-- - In prediction, the best model is simply the one that performs best. --&