Statistics (design → assumptions → method → diagnostics → effects)
Statistical method selection and testing for a dataset and hypothesis — identify the design, audit the assumptions, choose and justify the test or model, run it with the verified tools, run diagnostics, and report effects with uncertainty (effect size · CI · power) in a statistical report.
Key
statisticsTypeWorkflow skill
DomainPsychometrics & stats
Slash command
/statsHow to run it
Type the slash command in the composer followed by your request, or describe what you need in plain language — the skill is selected automatically.
/stats <your request>
Step-by-step walkthrough with screenshots: Skill guide →
Method skills it composes
- t-test (with assumptions)
- One-way ANOVA
- Power analysis
- Bayesian estimation (Bayes factor)
- Reliability (Cronbach α · McDonald ω)
- Exploratory Factor Analysis
- Confirmatory Factor Analysis
- Structural Equation Modeling
- Item Response Theory
- Test selection & execution (parametric ↔ non-parametric)
- Assumption checks & test selection
- Effect size estimation
- Multiple-comparison correction