Estadistica Practica Para Ciencia | De Datos Y Python High Quality

from statsmodels.stats.outliers_influence import variance_inflation_factor
X_multi = df[['total_bill', 'size', 'tip']].values
vif = [variance_inflation_factor(X_multi, i) for i in range(X_multi.shape[1])]
print(f"VIF: vif")  # VIF > 5 → problematic

Quantify uncertainty.

df = pd.DataFrame( 'ingresos': np.random.exponential(scale=50000, size=50_000_000), 'edad': np.random.normal(loc=35, scale=10, size=50_000_000) ) from statsmodels