Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add AlterLab-IEU/AlterLab-Academic-Skills --skill alterlab-statistical-analysisgit clone --depth 1 https://github.com/AlterLab-IEU/AlterLab-Academic-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-statistical-analysis)<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-statistical-analysis"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-statistical-analysis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alterlab-ieu/alterlab-academic-skills/alterlab-statistical-analysis"><img src="https://agentmods.dev/badge/skills/alterlab-ieu/alterlab-academic-skills/alterlab-statistical-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00074 | $0.01901 |
| Opus 5 | $0.00037 | $0.00950 |
| Sonnet 5 | $0.00015 | $0.00380 |
| Haiku 4.5 | $0.00007 | $0.00190 |
Grade A, and why
alterlab-statistical-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Statistical Analysis
Overview
A systematic process for testing hypotheses and quantifying relationships. Conduct hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, and Bayesian analyses with assumption checks and APA reporting. For academic research.
When to Use This Skill
Use when:
- Conducting hypothesis tests (t-tests, ANOVA, chi-square)
- Performing regression or correlation analyses
- Running Bayesian statistical analyses
- Checking statistical assumptions and diagnostics
- Calculating effect sizes and conducting power analyses
- Reporting statistical results in APA format
Core Capabilities
- Test selection & planning — choose tests by research question and data type; a priori power analysis; multiple-comparison strategy.
- Assumption checking — verify normality, homogeneity, linearity; diagnostic plots; remediation when violated.
- Statistical testing — parametric and non-parametric tests; regression; correlation; Bayesian alternatives with Bayes Factors.
- Effect sizes & interpretation — appropriate effect sizes with CIs; statistical vs. practical significance.
- Professional reporting — APA-style reports, publication-ready figures and tables.
Workflow
SELECT a test? → Test Selection Guide
CHECK assumptions? → Assumption Checking
RUN analysis? → Running Statistical Tests + references/code_examples.md
REPORT results? → Reporting Results + references/apa_report_templates.md
Worked code for every step is in references/code_examples.md.
Test Selection Guide
Quick reference (full decision tree: references/test_selection_guide.md):
Two groups — independent + normal → independent t-test; independent + non-normal → Mann-Whitney U; paired + normal → paired t-test; paired + non-normal → Wilcoxon signed-rank; binary outcome → chi-square or Fisher's exact.
3+ groups — independent + normal → one-way ANOVA; independent + non-normal → Kruskal-Wallis; paired + normal → repeated-measures ANOVA; paired + non-normal → Friedman.
What ships with it
9 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- evals/evals.json 5.7 KB
- references/apa_report_templates.md 2.4 KB
- references/assumptions_and_diagnostics.md 11 KB
- references/bayesian_statistics.md 17 KB
- references/code_examples.md 6.9 KB
- references/effect_sizes_and_power.md 15 KB
- references/reporting_standards.md 19 KB
- references/test_selection_guide.md 5.0 KB
- scripts/assumption_checks.py 15 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 183 lines · 74 tokens per session scan A 0cd7f4566a26
alterlab-statistical-analysis is a skill published in the GitHub repository AlterLab-IEU/AlterLab-Academic-Skills (66 stars, last pushed 4d ago), licensed MIT. It adds 74 tokens to every session and 1,901 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
r-spss-syntax-architect
A guide for turning research hypotheses into repeatable R or SPSS code for statistical analysis. It covers panel data, where the same companies or other units are observed over time, as well as interaction effects, curves, and mediation.
ob-hrm-scale-adaptor
A guide for adapting organisational behaviour and human-resources survey scales across languages and cultures. It covers permission checks, translation and back-translation, expert review, participant interviews, and tests of whether groups interpret the scale comparably.
management-figure
A chart-making toolkit for evidence-based management, finance, and strategy research. It creates publication-ready plots from regression results and tracking data, including coefficient, interaction, group-comparison, trend, and curved-relationship charts.
reproducibility-architect
A guide for packaging research so another person can rerun its data processing and analysis. A replication package is the project files, instructions, code, data guidance, and software details needed to reproduce published results.
thesis-consistency-audit
A consistency audit for quantitative master’s and doctoral theses in management, finance, or strategy. It checks whether numbers, tables, analyses, and claims agree, and can inspect hidden author information in office documents.
journal-submission-scout
A research tool for choosing a journal for a completed paper. It searches for journals that publish similar work, compares public information such as citation data, fees, open-access listing, and review practices, and screens for warning signs of predatory journals, which charge authors without providing trustworthy publishing services.