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Numora Statistics Outlier Detection API
x402
Numora Statistics Outlier Detection API 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).
Detects outliers in a numeric dataset using IQR or Z-score statistical methods
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 success flag, a human-readable computation description, and a result object containing identified outlier values, their indices in the original array, and relevant statistical thresholds (e.g. IQR bounds or Z-score cutoffs) used to classify them.
Example use cases
Sensor data anomaly detection
“I have a list of temperature sensor readings [20.1, 21.3, 19.8, 20.5, 85.2, 21.0, 20.7, 19.9] — can you flag any outliers using the z-score method so I know which ones to discard?”
Financial data quality check
“Here are daily transaction amounts for a user: [50, 45, 60, 55, 48, 5000, 52, 47] — can you detect any outliers using IQR to help me spot potentially fraudulent transactions?”
Student grade distribution review
“I have these student test scores: [72, 75, 68, 80, 74, 12, 77, 73, 71, 99] — can you identify statistical outliers using the z-score method so I can review those edge cases?”
Technical details
Endpoint
POSThttps://numormo.vercel.app/api/statistics/outlierWhen to prefer
Choose this endpoint when you need a deterministic, dependency-free statistical outlier detection on a numeric array without needing to run code locally or invoke a heavy ML service. Ideal for data cleaning pipelines, anomaly flagging in small-to-medium datasets, and situations where you want a choice between classic IQR (robust to skew) and Z-score (assumes normality) methods with a clear, interpretable result.
Side effects
- Empty or missing data array returns validation error
- Non-numeric values in array cause computation failure
- Invalid method enum value (not 'iqr' or 'zscore') returns error
- Single-element arrays may not support meaningful outlier detection
- Payment failure via x402 micropayment returns 402 error before computation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| datarequired | array | |
| method | string |
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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