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Numora Statistics Correlation
x402
Numora Statistics Correlation is a paid API for AI agents from numormo.vercel.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-14).
Computes the Pearson correlation coefficient between two numeric arrays, quantifying the linear relationship between them
Price / call$0.1
Success—
StatusUnknown
How this service works
100 pure math computation endpoints for AI agents. Statistics, financial math, linear algebra, equation solving, calculus, number theory, sequence generation, and unit conversions. Zero external dependencies. x402 micropayments on Base.
Output
Returns a JSON object with a boolean 'success' field, a 'computation' string describing what was calculated, and a 'result' object containing the Pearson correlation coefficient (typically an r-value between -1 and 1) along with any supporting statistical values such as sample size or significance.
Example use cases
Sales and temperature correlation analysis
“I have monthly average temperatures [32, 35, 45, 60, 72, 85, 90, 88, 75, 60, 45, 34] and monthly ice cream sales [200, 210, 350, 500, 720, 950, 1050, 1020, 800, 580, 320, 210]. Can you compute how correlated those two series are?”
Portfolio return correlation check
“I want to know the correlation between these two stocks' daily returns — stock A: [0.5, -0.3, 1.2, 0.8, -0.1] and stock B: [0.4, -0.2, 1.0, 0.9, -0.2]. Are they moving together?”
Study hours vs exam score relationship
“I collected data on students: study hours were [1, 2, 3, 4, 5, 6, 7, 8] and their exam scores were [45, 52, 60, 68, 75, 82, 88, 94]. Compute the correlation so I can see how strongly study time predicts score.”
Technical details
Endpoint
POSThttps://numormo.vercel.app/api/statistics/correlationWhen to prefer
Choose this endpoint when you need a fast, serverless, dependency-free Pearson correlation computation on two numeric arrays without setting up a local math library or data science environment. Ideal for AI agents that need quick statistical checks, micropayment-friendly per-call pricing, and no infrastructure overhead. Prefer over general-purpose code execution when you simply need the correlation coefficient reliably returned as structured JSON.
Side effects
- Arrays x and y of different lengths — likely returns an error or validation failure
- Non-numeric values in arrays — may cause computation failure
- Empty arrays provided — endpoint may return error or undefined result
- Missing required field x or y — returns 400-level error
- Arrays too short to compute meaningful correlation (e.g., single element)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| xrequired | array | |
| yrequired | array |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| resultrequired | object | Computation result varies by endpoint |
| successrequired | boolean | Always true on success |
| computationrequired | string | Human-readable description of what was computed |
Tags
x402
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