Estadistica Practica Para Ciencia De Datos Y Python High Quality ✪

# Probability of 7 successes in 10 trials, p=0.5 stats.binom.pmf(7, 10, 0.5)

# Visualización elegante fig, axes = plt.subplots(1, 2, figsize=(14, 6)) # Probability of 7 successes in 10 trials, p=0

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 0.5) # Visualización elegante fig

loop, they saw exactly how likely the result was due to chance. It wasn't just a number anymore; it was a simulation he could visualize. axes = plt.subplots(1