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KiHustle Covariance Calculator
x402
KiHustle Covariance Calculator is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-10).
Computes the covariance between two numeric data series provided as input arrays
Price / call$0.002
Success—
StatusUnknown
How this service works
Kostenlose Guides, Solo-Playbooks und Artikel zu KI, Automation und Side Hustles — für Menschen, die mit echten Systemen online Einkommen aufbauen wollen. Transparent finanziert über faire Affiliate-Links.
Output
Returns a JSON object with a 'result' field containing the computed covariance value and a 'status' field indicating success. The covariance quantifies the joint variability between the two input numeric series.
Example use cases
Portfolio asset correlation analysis
“I have daily returns for two stocks over the past week — Stock A was [0.02, -0.01, 0.03, 0.005, -0.02] and Stock B was [0.015, -0.008, 0.025, 0.004, -0.018]. Can you compute their covariance so I can understand how they move together?”
Sales and marketing spend relationship
“I want to know the covariance between my monthly ad spend [1200, 1500, 1800, 2100, 2400] and my monthly revenue [8000, 9500, 11000, 13500, 15000] — can you calculate that for me?”
Scientific experiment variable analysis
“I have two measurement series from my experiment: temperature readings [20.1, 22.3, 24.5, 26.7, 28.9] and reaction rates [0.45, 0.52, 0.61, 0.70, 0.79]. Please compute the covariance between them.”
Technical details
Endpoint
POSThttps://kihustle.tech/nexus/api/v1/covariance-calculator?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a simple, low-cost ($0.002) API call to compute pairwise covariance between two numeric arrays without setting up local statistical libraries. Suitable for lightweight agent workflows that need on-demand statistical computation.
Side effects
- Mismatched array lengths between series_a and series_b may cause computation errors
- Empty arrays may return an error or undefined result
- Non-numeric values in arrays will likely cause processing failures
- Very large arrays may time out or produce unexpected results
- Minimal response schema means error details may be limited
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| series_a | array | |
| series_b | array |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "processed",
"status": "success"
}
}Tags
x402
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