Purpose

This section documents the data cleaning and preparation phase for the Kruskal-Wallis statistical analysis comparing five groups. Perfect retention indicates no missing values, duplicates, or outliers were removed during preprocessing, which is critical for maintaining statistical power in the hypothesis test and ensuring the final sample accurately represents the underlying population.

Key Findings

Retention Rate: 100% (1,000 of 1,000 rows retained) - No data loss occurred during cleaning, preserving the full analytical dataset
Rows Removed: 0 - No filtering, deduplication, or outlier removal was applied
Data Completeness: All 1,000 observations remained eligible for analysis across all five groups
Train/Test Split: Not applicable - This is a descriptive/inferential analysis rather than a predictive modeling task

Interpretation

The complete retention of all observations strengthens the Kruskal-Wallis test results (H=57.08, p<0.001) by maximizing sample size and statistical power. With no rows excluded, the group distributions reflect the raw data without artificial filtering. However, the absence of any data cleaning raises questions about whether missing values, outliers, or data quality issues were genuinely absent or simply not addressed during preprocessing.

Context

The lack of train/test split is appropriate for this statistical inference task,