Data Science & Analytics
Running CausalPy Experiments
Fit, summarize, plot, and interpret a chosen CausalPy experiment. Use after the causal method has been selected, including when configuring PyMC/sklearn models and scale-aware custom priors.
- Publisher / source
- brycewang-stanford/Auto-Empirical-Research-Skills (found on GitHub top repositories)
- Upstream record
- brycewang-stanford/Auto-Empirical-Research-Skills
- Version
- Version 1
- Published
- Publication review
- Approved for publication · recorded passed scan 2026-11-05
- Content fingerprint
e393e3b7ed54fa2598aebd07d4438f35204384fe35cba6efa85b415e398ec001