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moheetsubudhi-isb/statistics-toolkit

v1.0.0MIT

Statistics skills for the moments that decide things at work: designing and reading A/B tests, comparing groups, estimating with a margin of error, setting control limits, checking causal claims, trusting a regression, giving honest prediction ranges, and modelling counts and rates.

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Statistics toolkit

Statistics skills for the moments that decide things at work: designing and reading A/B tests, comparing groups, estimating with a margin of error, setting control limits, checking causal claims, trusting a regression, giving honest prediction ranges, and modelling counts and rates.

Part of Business Analytics Skills, a set of agent skills that make an AI assistant work like a decision scientist and an advisor. Each skill asks what the work is for only when the answer would change the result, follows a real method step by step, runs a check wherever there is logic to verify, and hands back a plain-language brief plus a technical appendix.

Skills (8)

  • causal-claim-check: Pressure-test a claim that one thing caused another before anyone acts on it.
  • control-limits-and-error-costs: Set the threshold for a monitored measurement or quality check, balancing false alarms against missed problems.
  • count-and-rate-models: Model outcomes that are counts or rates, such as orders per day, defects per batch, claims per policy, visits per store or units sold per product and month.
  • estimate-with-margin-of-error: Estimate a true average or rate from a sample and say how precise it is, or work out how big a sample is needed.
  • experiment-design-and-readout: Design and read randomised experiments and A/B tests.
  • group-difference-test: Check whether two groups, or two points in time, differ by more than chance in data you already have.
  • prediction-interval-reporting: Give an honest range around a single prediction or forecast.
  • regression-diagnostics: Read a regression output table and check whether it can be trusted for inference.

Use

Skills load by themselves when a request matches. Ask a normal work question; to call one directly, type / and the skill name in Claude Code, Cursor or Copilot, or $ and the name in Codex.

What it runs

Instructions only, plus small optional Python checks (scripts/, standard library, numpy, pandas or scikit-learn) that read only the file you point them at. Nothing here reads credentials, environment secrets or your files on its own, makes network calls, or sends data anywhere.

Licence

MIT. Source and issues: https://github.com/moheetsubudhi-isb/business-analytics-skills