# Training Assessments Two-Measure Correlation + Explicit Missing-Value Fill

> Training Assessments Two-Measure Correlation + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Computes Pearson correlation between pre_score and post_score columns and fills missing values in a chosen score column for up to 200 training assessment rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-11-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/training-assessments-two-measure-correlation-explicit-missing-value-b971d1cc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_oPrvQLH4U5dxmZVx_5NPj

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 training-assessments-two-measure-correlation-explicit-missing-value-b971d1cc -d '<json body>'
```

Example prompt: I have 150 training assessment records with pre_score and post_score columns — some post_scores are missing. Can you compute the correlation between pre and post scores, and fill in missing post_score values using the median method?

## When to prefer this

Choose this endpoint when you have training assessment data with pre_score and post_score columns and need both a correlation analysis and missing-value imputation in a single paid call. It is ideal for education and e-learning datasets of up to 200 rows where you want offline, local statistical computation without any external data lookups, live scoring, or AI-generated predictions. Prefer this over general-purpose analytics tools when you need a cost-effective ($0.01 USDC) bundled report covering both correlation and imputation in one API call.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, course_group, date, pre_score, or post_score) — validation error
- Date format not matching YYYY-MM-DD pattern — schema validation failure
- Invalid enum value for field or method parameters — rejected with schema error
- All values in the target fill field are null — mean/median imputation may be undefined
- Payment not completed via x402 — request not processed

## How this service works

Training assessments — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied training assessments records (pre_score, post_score). 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 analytical reports: (1) a two-measure correlation report showing the statistical relationship (correlation coefficient) between pre_score and post_score across all supplied rows, and (2) an explicit missing-value fill report showing the chosen field with nulls replaced by the selected method (zero, mean, or median) applied to the non-null values. No external lookups or predictions are made.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/training-assessments-two-measure-correlation-explicit-missing-value-b971d1cc/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)