Estadistica Practica Para Ciencia De Datos Y Python High Quality | EASY — RELEASE |

# Calcular media y varianza media = datos['variable'].mean() varianza = datos['variable'].var()

# Evaluar modelo y_pred = modelo.predict(X_test) print(f'MSE: {np.mean((y_test - y_pred) ** 2):.2f}') # Calcular media y varianza media = datos['variable']

# Calcular estadístico z z = (media_muestra - mu) / (sigma / np.sqrt(n)) y_test = train_test_split(datos.drop('variable'

# Entrenar modelo modelo.fit(X_train, y_train) # Calcular media y varianza media = datos['variable']

# Dividir datos en entrenamiento y prueba X_train, X_test, y_train, y_test = train_test_split(datos.drop('variable', axis=1), datos['variable'], test_size=0.2, random_state=42)