# Teradata Z-Test

> Z-test for population mean comparison with known variance

- Skill: `teradata-labs/teradata-z-test` (Agent Skill, multi-file: 11 files)
- Install (CLI): `npx skillmds@latest add teradata-labs/teradata-z-test`
- Raw SKILL.md: https://api.skillmd.com/api/skills/teradata-labs/teradata-z-test/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Data & Analytics
- Author: teradata-labs (https://skillmd.com/u/teradata-labs)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/teradata-labs/teradata-z-test

---


# Teradata Z-Test

| Property | Value |
|----------|-------|
| **Skill Name** | Teradata Z-Test |
| **Description** | Z-test for population mean comparison with known variance |
| **Category** | Hypothesis Testing |
| **Primary Function** | TD_ZTest |
| **Framework** | SQLE |

## Core Capabilities

- Automated table structure analysis via DBC.ColumnsV
- Dynamic SQL generation for TD_ZTest
- Complete workflow from data preparation to results interpretation
- Data quality validation and preprocessing guidance
- Parameter optimization and tuning

## Key Parameters

- **TargetColumn**: Numeric column to test
- **PopulationMean**: Hypothesized population mean (H0)
- **PopulationSD**: Known population standard deviation
- **TestType**: 'TWOSIDED', 'LEFTSIDE', 'RIGHTSIDE'
- **Significance**: Significance level (default 0.05)

## Use Cases

1. Test population mean against hypothesis
2. Quality control process monitoring
3. A/B testing with large samples
4. Production benchmark validation

## Example Usage

```sql
-- TD_ZTest execution
SELECT * FROM TD_ZTest (
    ON {USER_DATABASE}.{USER_TABLE} AS InputTable
    USING
    TargetColumn ('{NUMERIC_COLUMN}')
    PopulationMean ({HYPOTHESIZED_MEAN})
    PopulationSD ({KNOWN_STD_DEV})
    TestType ('TWOSIDED')              -- 'TWOSIDED','LEFTSIDE','RIGHTSIDE'
    Significance (0.05)
) AS dt;
```

## Scripts Included

### Core Analytics Scripts
- **`table_analysis.sql`**: Automatic table structure discovery
- **`preprocessing.sql`**: Data preparation and feature engineering
- **`model_training.sql`**: TD_ZTest execution
- **`evaluation.sql`**: Results analysis and metrics
- **`complete_workflow_template.sql`**: End-to-end workflow

### Utility Scripts
- **`data_quality_checks.sql`**: Comprehensive data validation
- **`parameter_tuning.sql`**: Parameter optimization
- **`diagnostic_queries.sql`**: Results diagnostics and interpretation

## Best Practices

- Always run table_analysis.sql first to understand your data structure
- Validate data quality before executing the analytical function
- Use parameter_tuning.sql to find optimal configuration
- Review diagnostic_queries.sql output for model/results validation

## Limitations

- Requires Teradata Vantage 17.20+ with ClearScape Analytics
- Input data must meet function-specific requirements
- Results depend on data quality and parameter configuration

*Teradata Z-Test - ClearScape Analytics skill for Teradata Vantage*