Compute Pearson and Spearman correlation matrices with p-values and partial correlations.
npx skills add https://github.com/haomingz/kimi-skills --skill corr-insight
Please help me install this Agent Skill. Skill: corr-insight Source: https://github.com/haomingz/kimi-skills/tree/main/skills/corr-insight Command: npx skills add https://github.com/haomingz/kimi-skills --skill corr-insight
This tool analyzes numeric data to reveal both simple and partial correlations, helping identify true relationships and flag potential confounding effects.
Run correlation analysis on a numeric dataset to obtain matrices, partial correlations, and spurious-detection results.
High-intent search queries and answers about installing and using this skill.
Detect spurious correlations by comparing simple Pearson and Spearman matrices against partial correlations. This identifies relationships that weaken or disappear when controlling for confounding variables.
Simple correlation measures the direct association between two numeric variables, while partial correlation calculates their net relationship after controlling for the influence of other confounding variables.
Compute Pearson and Spearman correlation matrices with associated p-values to quantify the strength and statistical significance of relationships among numeric variables in your dataset.
Yes, partial correlation reveals direct links by calculating the net relationship between variable pairs after mathematically controlling for the effects of all other numeric variables.
You need a structured numeric dataset, typically managed via pandas, to compute the correlation matrices and partial correlations required for the analysis.
The analysis returns a structured JSON payload including metadata, matrices, p-values, and interpretation guidance to help you understand the significance of the relationships.
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