conbio-data-analysis
Use when executing and reporting the analysis for a Conservation Biology manuscript so it survives expert, double-blind review — appropriate ecological/statistical models, honest uncertainty, robustness, and reproducibility. Covers detection, hierarchical models, spatial structure, and effect sizes that matter for conservation. Guides analysis norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conbio-data-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Data Analysis (conbio-data-analysis) *Conservation Biology* reviewers are methodologically sophisticated, and the journal expects a **data-availability statement** with data and code deposited at acceptance (see `conbio-reporting-and-data-policy`). Analyze as if your code will be re-run — because it may be. This skill covers execution and reporting norms; design decisions live in `conbio-study-design`. ## When to trigger - Running main and supporting analyses; building the results section - A reviewer asked for robustness, alternative models, or uncertainty - Reconciling exploratory vs. confirmatory analyses - Making the analysis reproducible before deposit ## Analysis norms Conservation Biology expects 1. **Report uncertainty honestly.** Confidence/credible intervals, not just stars or p-values; report the **magnitude and conservation meaning** of the estimate, not only significance. 2. **Use the right model for the data.** Hierarchical/mixed models for nested data; occupancy and N-mixture for detection; capture-recapture for survival/abundance; GLMs/GAMs for nonlinearity; account for spatial autocorrelation and zero-inflation where present. 3. **Robustness that probes, not deco
- When to trigger
- Analysis norms Conservation Biology expects
- Conservation-specific reporting
- Reproducibility while you work (not at the end)
- Anti-patterns
- Evidence pass for Conservation Biology
- Output format
- Supplementary resources
What does the conbio-data-analysis skill do?
Use when executing and reporting the analysis for a Conservation Biology manuscript so it survives expert, double-blind review — appropriate ecological/statistical models, honest uncertainty, robustness, and reproducibility. Covers detection, hierarchical models, spatial structure, and effect sizes that matter for conservation. Guides analysis norms; it does not fabricate results.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill conbio-data-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.