{"enrichment":{"faq":[{"a":"data-stats-analysis enables rigorous statistical hypothesis testing and significance analysis using standard Python libraries (scipy, statsmodels, numpy) that run locally in your environment. You can perform t-tests, ANOVA, correlation analysis, non-parametric tests like Mann-Whitney and Kruskal-Wallis, chi-square tests, and normality testing with Shapiro-Wilk\u2014all without cloud dependencies.","q":"What statistical analysis python scipy capabilities does data-stats-analysis provide?"},{"a":"data-stats-analysis applies multiple testing corrections to control false discovery rate (FDR), including Bonferroni and other established methods. These corrections adjust p-values when conducting multiple comparisons, helping you avoid false positives and maintain statistical rigor across batch testing scenarios like differential gene expression analysis or cluster enrichment studies.","q":"How does data-stats-analysis handle multiple testing correction?"},{"a":"Yes, data-stats-analysis compares means across groups using t-tests for two-group comparisons, ANOVA for multiple groups, and non-parametric alternatives like Mann-Whitney and Kruskal-Wallis tests when data violates normality assumptions. It also supports post-hoc pairwise comparisons following ANOVA to identify which specific groups differ significantly.","q":"Can data-stats-analysis compare means across groups?"},{"a":"data-stats-analysis analyzes correlations and relationships between variables using both Pearson correlation (for linear relationships) and Spearman correlation (for monotonic relationships). These analyses help you detect associations in your data while providing p-values and confidence intervals to assess statistical significance.","q":"What correlation and relationship analysis does data-stats-analysis support?"},{"a":"Yes, data-stats-analysis is compatible with any LLM provider including GPT, Claude, Gemini, and others. It executes statistical tests locally using standard Python libraries, so you maintain full control over your analysis environment without vendor lock-in or cloud dependencies.","q":"Does data-stats-analysis work with any LLM provider?"},{"a":"data-stats-analysis calculates effect sizes (including Cohen's d) and confidence intervals for statistical results, giving you not just p-values but also practical measures of result magnitude. These metrics help you interpret whether statistically significant findings are also practically meaningful.","q":"Can data-stats-analysis calculate effect sizes and confidence intervals?"}],"shadow_tags":["local-execution","hypothesis-testing","genomics-analysis","effect-sizes","parametric-tests","non-parametric-methods","multiple-comparisons","data-validation"],"summary_rewrite":"This skill brings rigorous statistical testing to your LLM workflow using standard Python libraries (scipy, statsmodels, numpy) that execute locally in your environment. Perform t-tests, ANOVA, correlation analysis, multiple testing corrections, and non-parametric tests\u2014all compatible with any LLM provider including GPT, Claude, Gemini, and others."},"files":[{"bytes":15462,"path":"skills/data-stats-analysis/SKILL.md","sha256":"c66803cf420440801607f26d13d887e9e20aa7b92c7d6b50b630771c4b343422","url":"https://skillfed.io/files/beita6969/ScienceClaw/data-stats-analysis/63bb0c6b/SKILL.md"}],"id":"beita6969/ScienceClaw/data-stats-analysis","links":{"html":"https://skillfed.io/beita6969/ScienceClaw/data-stats-analysis","md":"https://skillfed.io/beita6969/ScienceClaw/data-stats-analysis.md","repo":"https://github.com/beita6969/ScienceClaw"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":101,"language":"TypeScript","last_updated":"2026-06-08","license":"MIT","name":"data-stats-analysis","publisher":"beita6969","stars":869},"relations":{"similar":[{"id":"aj-geddes/useful-ai-prompts/statistical-hypothesis-testing"},{"id":"beita6969/ScienceClaw/statistical-testing"},{"id":"aj-geddes/useful-ai-prompts/ab-test-analysis"},{"id":"personamanagmentlayer/pcl/research-expert"},{"id":"beita6969/ScienceClaw/data-analysis"},{"id":"jaechang-hits/SciAgent-Skills/statistical-significance-annotation"},{"id":"foryourhealth111-pixel/Vibe-Skills/statistical-analysis"},{"id":"wangyendt/wayne-skills/statistics"},{"id":"synthetic-sciences/openscience/statistical-analysis"},{"id":"zLanqing/codex-claude-academic-skills/statistical-analysis"}]},"slug":{"owner":"beita6969","repo":"ScienceClaw","skill":"data-stats-analysis"},"version":"63bb0c6b"}