# Numeric Precision Comparisons — IQR Outlier Flags + Secondary-Measure Weighted Mean

> Numeric Precision Comparisons — IQR Outlier Flags + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Analyzes up to 200 rows of source/transformed numeric value pairs, flagging IQR-based outliers and computing a secondary-measure weighted mean in two independent local analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-177?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/numeric-precision-comparisons-iqr-outlier-flags-secondary-measure-5c8ff3cd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_cPe7htCBFFUpCwzXa7jhE

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability numeric-precision-comparisons-iqr-outlier-flags-secondary-measure-5c8ff3cd -d '<json body>'
```

Example prompt: Can you run IQR outlier detection and a weighted mean calculation on these 50 rows of source and transformed values — the dataset group is 'sales-q3', dates range from 2025-01-01 to 2025-03-31, and I want the analysis run on source_value?

## When to prefer this

Choose this endpoint when you need fast, local statistical analysis on a batch of up to 200 numeric source/transformed value pairs — specifically IQR-based outlier detection plus weighted mean — without any external data lookups, ML predictions, or professional assessment. Ideal for data quality audits on ETL pipelines, sensor calibration checks, or financial data reconciliation where you need two standard statistical reports in a single low-cost call.

## Known failure modes

- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) — schema validation failure
- Invalid date format (not YYYY-MM-DD) — pattern validation error
- Numeric values outside allowed range (±1,000,000,000,000) — validation rejection
- Empty rows array — minItems constraint violation
- All values null for selected field — statistical computation may return undefined results

## How this service works

Numeric precision comparisons — IQR outlier flags + Secondary-measure weighted mean: IQR outlier flags + Secondary-measure weighted mean for supplied numeric precision comparisons records (source_value, transformed_value). 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

Returns two independent analytical reports for the submitted rows: (1) IQR outlier flags identifying which rows fall outside the interquartile range for the selected field, and (2) a secondary-measure weighted mean computed across the dataset. All analysis is performed locally with no external lookups or predictions.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "source_value",
     "transformed_value"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_value": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "transformed_value": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_value": 10,
     "dataset_group": "group-a",
     "transformed_value": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_value": 20,
     "dataset_group": "group-b",
     "transformed_value": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_value": 15,
     "dataset_group": "group-a",
     "transformed_value": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_value": 30,
     "dataset_group": "group-b",
     "transformed_value": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "source_value",
    "transformed_value"
   ],
   "type": "string",
   "default": "source_value"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-iqr-outlier-flags-secondary-measure-5c8ff3cd/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)