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Chi-Square Goodness-of-Fit Test
x402
Chi-Square Goodness-of-Fit Test is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-14).
Performs a chi-square goodness-of-fit statistical test comparing observed frequencies to expected frequencies
Price / call$0.002
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object with a result field indicating whether the chi-square test was processed and a status field confirming success. Note: the response schema is minimal and may not include the full chi-square statistic, p-value, or degrees of freedom in the current implementation.
Example use cases
Testing fairness of a die
“I rolled a die 120 times and got these counts per face: [18, 22, 19, 21, 17, 23]. Expected is 20 for each face. Can you run a chi-square goodness-of-fit test to tell me if the die is fair?”
Validating survey response distribution
“My survey has 4 response options and I expected responses to be split 25% each, but I got [45, 30, 15, 10] out of 100 responses. Run a chi-square test to see if the distribution is significantly different from expected.”
Checking if sales match forecast
“I forecasted sales per category as [200, 150, 100, 50] units but actually sold [210, 140, 95, 55]. Can you do a chi-square goodness-of-fit test to see if the actual sales match my forecast?”
Technical details
Endpoint
POSThttps://kihustle.tech/nexus/api/v1/chi-square-goodnessWhen to prefer
Use this endpoint when you need a quick, cheap statistical computation to test whether observed categorical frequencies match a theoretically expected distribution. Suitable for automated pipelines needing hypothesis testing at scale without spinning up a local statistics library.
Side effects
- Mismatched array lengths between observed and expected arrays may cause errors
- Non-numeric values in arrays will likely cause computation failure
- Empty arrays may return an error or unexpected result
- Expected frequencies of zero could cause division-by-zero issues in chi-square calculation
- Very large arrays may time out
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| expected | array | |
| observed | array |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "processed",
"status": "success"
}
}Tags
x402
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