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statistical-analysis

Open source alternatives to statistical-analysis

24 open source AI Skills apps to use instead, best rated first.

Top picks

  1. G

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  2. O

    opensource-pipeline

    Launch

    opensource-pipeline is an agent skill from the ECC collection by affaan-m, listed on skills.sh. It prepares a private project for safe public release through a three-stage pipeline. The fork stage strips secrets from a copy. The sanitise st

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  3. A

    andrej-karpathy-skills

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    andrej-karpathy-skills is a single CLAUDE.md file from the multica-ai project that is meant to improve how Claude Code behaves on coding tasks. It is derived from Andrej Karpathy's public observations about LLM coding pitfalls. The file dis

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  4. M

    microsoft/markitdown

    Launch

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  5. O

    od-contribute

    Launch

    od-contribute is an agent skill in the OpenDesign project that provides a guided, one-click contribution flow to the OpenDesign repository, written so that people without a coding background can send a real pull request. It is locked to the

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  6. G

    github-deep-research

    Launch

    github-deep-research is an agent skill from the DeerFlow project that researches a single GitHub repository in several rounds and writes a report in Markdown. It is for requests that need more than a README summary, such as a comprehensive

    Open source

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About statistical-analysis

S

statistical-analysis

Apply statistical methods including descriptive stats, trend analysis

Statistical-analysis is an agent skill that applies common statistical methods to business and research data. It covers descriptive statistics, trend analysis, outlier detection and hypothesis testing, and it also includes guidance on when a statistical claim should be treated with caution. Its methodology section explains how to choose a measure of center for the shape of the data. The mean is the most efficient estimate for symmetric data without outliers, the median is robust when data is skewed, and the mode is the only option for categorical or ordinal data. For highly skewed business metrics such as revenue per user, the skill recommends reporting the mean and the median together, because the gap between them shows how skewed the data is. It is useful when you want to check that a number you are about to report describes the data fairly. The skill is part of Anthropic's knowledge-work plugins.

View statistical-analysisAll AI Skills apps
Price
Free
Made by
anthropics
Category
AI Skills
Website
github.com/anthropics/knowledge-work-plugins/statistical-analysis