[Chart: QQ plot before/after] Report saved: normality_report_sales_revenue.pdf The Normality Plugin transforms a tedious, error‑prone assumption check into an automated, visual, and actionable workflow. It fits naturally into statistical QA, feature engineering, and model validation pipelines — saving time and improving analytical rigor.
DIAGNOSTICS: Skewness: 2.34 (high positive skew) Kurtosis: 6.78 (leptokurtic – heavy tails) normality plugin
CODE (Python): from scipy.stats import boxcox df['sales_revenue_norm'] = boxcox(df['sales_revenue'], lmbda=0.22) error‑prone assumption check into an automated
TRANSFORMATION SUGGESTION: → Box–Cox (λ=0.22) recommended Post‑transformation Shapiro–Wilk: W=0.99, p=0.31 → NORMAL p=0.31 → NORMAL