est-data-analysis
Use when executing and reporting the analysis for an Environmental Science & Technology (ES&T) manuscript so it survives expert review — analytical QA/QC, honest uncertainty, statistics appropriate to environmental data, and closed mass balances. It guides analysis and reporting norms; it does not fabricate results.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill est-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 (est-data-analysis) ES&T reviewers scrutinize the analytical chain: blanks, recoveries, detection limits, replicates, and whether the numbers add up. This skill covers execution and reporting; design decisions live in `est-study-design`, and deposit/reproducibility in `est-reporting-and-reproducibility`. ## When to trigger - Reducing raw instrument/field data into results - Building the results section and the QA/QC reporting - A reviewer asked about detection limits, recoveries, replicates, or statistics - Closing a mass/energy balance or fitting kinetics/dose–response ## Analysis norms ES&T expects 1. **Report QA/QC explicitly.** Method/field blanks, matrix-spike recoveries, CRM results, **LOD/LOQ**, calibration range and R², surrogate/internal-standard recoveries, and how non-detects were handled. 2. **Honest uncertainty.** Report replicates with measures of dispersion (SD/SE/CI), not single values; propagate uncertainty through derived quantities; state n every time. 3. **Right statistics for environmental data.** Handle left-censored (below-LOD) data correctly (e.g., substitution caveats, MLE/ROS, Kaplan–Meier); check distributional assumptions; use nonparametr
- When to trigger
- Analysis norms ES&T expects
- Reproducibility while you work (not at the end)
- QA/QC reporting table reviewers expect to see
- Worked micro-example (illustrative — PFAS quantitation with censored data)
- Referee-pushback patterns and the venue-specific fix
- Anti-patterns
- Output format
- Supplementary resources
What does the est-data-analysis skill do?
Use when executing and reporting the analysis for an Environmental Science & Technology (ES&T) manuscript so it survives expert review — analytical QA/QC, honest uncertainty, statistics appropriate to environmental data, and closed mass balances. It guides analysis and reporting norms; it does not fabricate results.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill est-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.