Purpose

This section documents the data preprocessing pipeline for the marketing ROI analysis. It shows that no data rows were processed during the preprocessing stage, which is inconsistent with the main analysis that evaluated 200 observations. This discrepancy suggests the preprocessing metadata may not have been properly captured or the pipeline documentation is incomplete.

Key Findings

Initial Rows: 0 - No input data recorded in preprocessing logs
Final Rows: 0 - No output data documented after cleaning
Retention Rate: 100% - Perfect retention rate, but meaningless given zero rows
Data Quality: No transformations, filtering, or quality checks are documented despite the main analysis using 200 complete observations

Interpretation

The preprocessing section shows zero rows processed, yet the regression model successfully analyzed 200 observations with no rows removed (initial_rows = 200, rows_removed = 0). This indicates either the preprocessing documentation failed to capture the actual data pipeline, or the data was loaded directly without formal preprocessing steps. The 100% retention rate is technically accurate but uninformative—it reflects that no data was explicitly removed, not that preprocessing was thorough.

Context

This metadata gap creates uncertainty about data quality decisions, missing value handling, and feature engineering applied before modeling. Given the main analysis shows heteroscedasticity issues and non-normal residuals, understanding preprocessing choices would be critical