Designing Experiments

Helps choose and specify a research design before data analysis starts. This skill owns study-design decisions: what is treated, what is compared, what outcome is measured, which assumptions are required, which validation or recovery experiment should follow a failed scientific experiment, and which design is defensible.

It does not fit causal models, estimate treatment effects, interpret fitted model output from existing data, or debug software/build failures.

Decision Framework

1. Control Group?

   • Yes: Go to Step 2.
   • No: Consider Interrupted Time Series (ITS).

2. Unit Structure?

   • Single Treated Unit:
     • With multiple controls: Synthetic Control (SC).
     • No controls: ITS.
   • Multiple Treated Units:
     • With control group: Difference-in-Differences (DiD).