Estadistica Practica Para Ciencia De Datos Y Python High Quality Fix Jun 2026

import plotly.express as px

def bootstrap_ci(data, statistic=np.mean, n_boots=1000, ci=95): boots = [statistic(np.random.choice(data, len(data), replace=True)) for _ in range(n_boots)] lower = np.percentile(boots, (100 - ci) / 2) upper = np.percentile(boots, (100 + ci) / 2) return lower, upper import plotly

import pandas as pd import numpy as np

) focuses on bridging the gap between traditional statistical theory and modern data science practices. Its primary feature is 50+ essential concepts import plotly.express as px def bootstrap_ci(data