Purpose

This section documents the data preprocessing pipeline for the one-way ANOVA analysis comparing five groups. It shows that no data cleaning or filtering was applied, meaning all 1,000 observations proceeded directly to statistical testing. Understanding preprocessing decisions is critical because they affect the validity of group comparisons and the reliability of the significant findings (p < 0.001).

Key Findings

Retention Rate: 100% (1,000 of 1,000 rows retained) - No observations were removed during preprocessing, preserving the full dataset for analysis
Rows Removed: 0 - No filtering, outlier removal, or missing value imputation occurred
Data Quality: Complete dataset with no documented transformations applied before ANOVA testing
Train/Test Split: Not applicable - This is a descriptive/inferential analysis rather than a predictive modeling task

Interpretation

The perfect retention rate indicates a clean, complete dataset with no missing values or quality issues requiring removal. However, the absence of any preprocessing steps means potential outliers or data quality issues were not explicitly addressed before statistical testing. Given the ANOVA results show statistical significance (F=14.59, p≈0) but the Q-Q plot reveals non-normality (Shapiro-Wilk p≈0), the lack of preprocessing decisions—such as transformation or outlier handling—