The second edition is particularly valuable for Python users, as it provides comprehensive code examples using industry-standard libraries like Pandas, NumPy, SciPy, and Statsmodels. 📊 Core Domains for Data Science
buyers = df[df.purchased == 1]['price'] non_buyers = df[df.purchased == 0]['price'] t_stat, p_value = stats.ttest_ind(buyers, non_buyers) print(f"p-value: p_value:.5f") # 0.32 The second edition is particularly valuable for Python
A diferencia de los libros de texto tradicionales, este enfoque se centra en lo que en el día a día de un profesional de datos: p_value = stats.ttest_ind(buyers
# Generate & test normality sample = np.random.normal(loc=0, scale=1, size=1000) stats.normaltest(sample) # p > 0.05 → normal size=1000) stats.normaltest(sample) # p >