designing-experiments
SolidSelects the appropriate quasi-experimental method (DiD, ITS, SC) based on data structure and research questions. Use when the user is unsure which method to apply.
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Quality Score: 89/100
Skill Content
Details
- Author
- foryourhealth111-pixel
- Repository
- foryourhealth111-pixel/Vibe-Skills
- Created
- 3 months ago
- Last Updated
- 1 weeks ago
- Language
- Python
- License
- Apache-2.0
Similar Skills
Semantically similar based on skill content — not just same category
experiment-designer
Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.
experiment-designer
Use when planning product experiments, writing testable hypotheses, estimating sample size, prioritizing tests, or interpreting A/B outcomes with practical statistical rigor.
performing-causal-analysis
Fits causal models, estimates impacts, and plots results using CausalPy. Use when performing analysis with DiD, ITS, SC, or RD.
causal-inference-methods
Apply propensity score methods, instrumental variables, difference-in-differences, and regression discontinuity designs for causal identification
experiment-design
A discipline for designing experiments (A/B tests, multivariate, holdouts) so the results actually answer the question you asked. Hypothesis writing, sample size, duration, segment analysis, interpretation, decision-making, and the common failure modes that produce confidently wrong shipping decisions.