Teradata F-Test

Teradata F-Test

Core Capabilities

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

Key Parameters

• TargetColumn: Numeric column with sample data
• GroupColumn: Grouping column (two groups)
• Significance: Significance level (default 0.05)

Use Cases

1. Compare variances between populations
2. Pre-test for t-test assumptions
3. Quality control variance analysis
4. Process consistency evaluation

Example Usage

-- TD_FTest execution
SELECT * FROM TD_FTest (
    ON {USER_DATABASE}.{USER_TABLE} AS InputTable
    USING
    TargetColumn ('{NUMERIC_COLUMN}')
    GroupColumn ('{GROUP_COLUMN}')
    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_FTest 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 F-Test - ClearScape Analytics skill for Teradata Vantage