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Correlation Analyzer

Listed
jeremylongshore·vlatest·data·MIT

This Correlation Analyzer identifies relationships between variables, revealing hidden patterns and insights for data exploration and analysis.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add jeremylongshore/tons-of-skills-marketplace --skill correlation-analyzer -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

jeremylongshore

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

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Automated safety checks

scanned

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Not scanned. none of the 396 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as jeremylongshore/claude-code-plugins-plus-skills.
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About this skill

What it does

The correlation-analyzer skill identifies and quantifies the statistical relationship between two datasets. It can determine if a positive, negative, or no correlation exists, along with a correlation coefficient value to indicate strength. This allows for data-driven insights into potential dependencies and patterns within datasets.

When to use it

  • Market Research: Analyze the correlation between advertising spend and sales figures to optimize marketing campaigns.
  • Scientific Studies: Determine if there's a relationship between different variables in an experiment, like temperature and reaction rate.
  • Financial Analysis: Investigate correlations between stock prices or economic indicators to inform investment strategies.
  • Customer Behavior: Identify relationships between website activity and purchase conversion rates.

Key capabilities

  • Calculates correlation coefficients.
  • Identifies positive and negative correlations.
  • Quantifies the strength of correlations.

Example prompts

  • "Analyze the correlation between these two datasets: [dataset 1] and [dataset 2]."
  • "What is the correlation coefficient between temperature and ice cream sales?"
  • "Is there a significant relationship between website visits and product purchases? Provide the correlation coefficient."

Tips & gotchas

The quality of the analysis depends heavily on the data provided; ensure datasets are clean, relevant, and appropriately formatted. Correlation does not equal causation - further investigation is often needed to understand underlying relationships.