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KiHustle Paired T-Test API
x402
KiHustle Paired T-Test API is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).
Performs a paired (before/after) t-test on two matched numeric arrays and returns a statistical result
Price / call$0.002
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object with a 'result' field indicating the outcome of the paired t-test and a 'status' field confirming success. In a well-formed response, this would include the t-statistic, degrees of freedom, and p-value to determine statistical significance of the before-after difference.
Example use cases
A/B experiment significance check
“I ran a before-and-after experiment on 8 users — their scores before were [55, 60, 58, 62, 50, 57, 63, 61] and after were [60, 65, 61, 67, 55, 62, 68, 66]. Can you run a paired t-test and tell me if the improvement is statistically significant?”
Weight loss program evaluation
“My clients tracked their weights before and after a 4-week program — before: [82.1, 75.3, 90.5, 68.2, 77.4] and after: [80.5, 74.1, 88.9, 67.0, 76.2]. Run a paired t-test to see if the weight reduction is statistically meaningful.”
Marketing campaign lift analysis
“I want to know if my marketing campaign actually moved the needle. Conversion rates before the campaign were [0.12, 0.15, 0.11, 0.14, 0.13] and after were [0.17, 0.19, 0.16, 0.18, 0.15] for the same store locations. Do a paired t-test on those.”
Technical details
Endpoint
POSThttps://kihustle.tech/api/v1/t-test-pairedWhen to prefer
Choose this endpoint when you have paired/matched observations (same subjects measured before and after an intervention) and need to test whether the mean difference is statistically significant. Prefer a paired t-test over an independent samples t-test when the two samples are correlated (e.g., same individuals measured twice). This endpoint is a low-cost, simple API call suitable for lightweight statistical checks in automated pipelines.
Side effects
- Mismatched array lengths between 'before' and 'after' causing computation failure
- Empty or null arrays resulting in an error response
- Non-numeric values in the input arrays
- Arrays with only one element (insufficient degrees of freedom)
- Response schema is vague (only 'processed'/'success') — actual statistical values may not be returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| after | array | |
| before | array |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "processed",
"status": "success"
}
}Tags
x402
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