Agent skill · research science · aiskillstore
statistical-analysis
Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research.
Why this skill is useful
Provides specific statistical analysis techniques and workflows that the AI wouldn't reliably generate on its own.
What it needs
About 10k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
Statistical Analysis Overview Statistical analysis is 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. Apply this skill for academic research. When to Use This Skill This skill should be used when: Conducting statistical 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 Analyzing experimental or observational data for research --- Core Capabilities 1. Test Selection and Planning Choose appropriate statistical tests based on research questions and data characteristics Conduct a priori power analyses to determine required sample sizes Plan analysis strategies including multiple comparison corrections 2. Assumption Checking Automatically verify all relevant assumptions before running tests Provide diagnostic visualizations (Q-Q plots, residual plots, box plots) Recommend remedial actions when assumptions are violated 3. Statistical Testing Hypothesis testing: t-tests, ANOVA, chi-square, non-parametric alternatives Regression: linear, multiple, logistic, with diagnostics Correlations: Pearson, Spearman, with confidence intervals Bayesian alternatives: Bayesian t-tests, ANOVA, regression with Bayes Factors 4. Effect Sizes and Interpretation Calculate and interpret appropriate effect sizes for all analyses Provide confidence intervals for effect estimates Distinguish statistical from practical significance 5. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/statistical-analysis