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Sampling Observations — Record Quality Audit + Two-Measure Correlation
x402
Sampling Observations — Record Quality Audit + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Runs a record quality audit and a two-measure correlation analysis on up to 200 sampling observation rows (sample_value, sample_weight), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Sampling observations — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied sampling observations records (sample_value, sample_weight). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two independent analytical reports: (1) a record quality audit flagging issues such as missing values, invalid formats, or out-of-range entries across the submitted rows; and (2) a two-measure correlation analysis quantifying the statistical relationship between sample_value and sample_weight across the dataset. Both reports are generated locally from the supplied data with no external lookups.
Example use cases
Survey sample quality check before analysis
“I have 120 survey response rows with fields for row ID, group label, date, a numeric sample value, and a response weight — can you run a data quality audit and also tell me how correlated the sample values are with the weights?”
A/B test observation validation
“Before I run my A/B test analysis, can you check these 80 observation records for quality issues and give me a correlation report between the measured values and the assigned weights? Each row has a row ID, group name, date, sample_value, and sample_weight.”
Weighted sampling dataset integrity check
“I'm working with two dataset groups of sampling observations, about 150 rows total, each tagged with a date and row ID. Can you audit them for record quality problems and compute the correlation between sample_value and sample_weight?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-15-015?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a correlation report on sampling observations in a single paid call, especially when your dataset has up to 200 rows with sample_value and sample_weight fields. Prefer this over separate audit or correlation tools when cost efficiency and bundled reporting matter, and when no live data lookup, prediction, or external action is required.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, sample_value, sample_weight, dataset_group) cause row-level rejection
- Dates not matching YYYY-MM-DD pattern are flagged or rejected
- Numeric values outside ±1,000,000,000,000 are rejected by schema validation
- Submitting fewer than 1 row returns an error
- Insufficient USDC payment prevents endpoint execution
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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