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Methods: Overview, resources
"Qualitative" design issues: How to design the 'content' of experiments and surveys to have internal validity and external generalizability
Adaptive design/sampling, reinforcement learning: Adjusting the treatments and design as you learn, to 'get to the highest value in the end'
Analysis: Statistical approaches: How to make inferences from the data after you have it (and plan this in advance)
Rethink Priorities notes (some are works in progress)...
How to Visualize
RP dynamic doc on making graphs etc
The https://declaredesign.org/ framework and R package seems very helpful. I (David Reinstein) am learning and trying to adapt it.