Can this skill help with A/B testing?

Yes, it helps determine if a conversion lift is actual performance or random noise by checking if the confidence interval excludes the status quo value.

How does sample size affect the intervals generated?

Larger sample sizes reduce the standard error, which results in narrower and more precise confidence intervals, leading to more certain decisions.

What does a 95% confidence interval actually mean?

It means that if you repeated the measurement 100 times using the same method, 95 of those calculated intervals would contain the true population value.

When should I use a 99% confidence level instead of 95%?

Use 99% for high-stakes decisions like medical data, safety protocols, or irreversible infrastructure changes where the cost of being wrong is extremely high.

What is the main benefit of using Confidence Intervals in Claude?

It prevents overconfidence by providing a range of plausible values instead of a single, often misleading, point estimate, allowing for honest uncertainty in reports.

Confidence Intervals Thinking Pattern

Name: Confidence Intervals Thinking Pattern
Author: lev-os

bylev-os

0•

Data Science & ML

Quantifies uncertainty in estimates by generating plausible ranges to enable more reliable data-driven decision making.

This skill implements a structured statistical framework to combat overconfidence bias and false precision in technical and business estimates. It guides Claude through the process of calculating point estimates, determining appropriate confidence levels (90%, 95%, or 99%), and deriving standard errors to construct reliable intervals. By transforming single-point data into actionable ranges, it enables users to make more informed decisions in A/B testing, growth forecasting, and risk assessment, effectively signaling when more data is required or when a result is statistically significant enough for action.

Key Features

010 GitHub stars

02Multi-level confidence interval construction (90%, 95%, 99%)

03Bias mitigation against overconfidence and false precision

04Sample size requirement estimation for desired precision goals

05Standard Error (SE) calculation for both proportions and means

06Decision framework for interpreting interval overlaps and widths

Use Cases

01Validating A/B test results to determine if a performance lift is statistically significant or random noise

02Evaluating risk in high-stakes scenarios by bounding worst-case and best-case outcomes

03Forecasting user growth or churn rates with explicit uncertainty bounds for resource planning

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lev-os/agents confidence-intervals

For use in Claude.ai and ChatGPT

Download Skill