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thinking-bayesian

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Update beliefs with evidence, precisely.

Data & Analytics#evidence#probability#uncertainty#bayesian#posterior#prior#likelihood
Authortjboudreaux
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Bayesian thinking provides a disciplined framework for updating beliefs as new evidence arrives, helping you avoid overconfidence or underreaction.

Core Features & Use Cases

  • Establish priors, assess likelihoods, and compute posteriors to refine beliefs.
  • Apply to probability estimation, test interpretation, hypothesis evaluation, and learning from experiments.
  • Use cases include debugging uncertain failures, evaluating feature hypotheses, and interpreting A/B test results.

Quick Start

Explain a hypothesis to an AI and have it perform Bayesian updating to produce a posterior probability given new data.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: thinking-bayesian
Download link: https://github.com/tjboudreaux/cc-thinking-skills/archive/main.zip#thinking-bayesian

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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