# Definir límites limite_inferior = Q1 - 1.5 * IQR limite_superior = Q3 + 1.5 * IQR
told him more about his messy outliers than any automated cleaner ever could. The Power of Sampling # Definir límites limite_inferior = Q1 - 1
model = smf.logit("purchased ~ error_occurred * device", data=df).fit() print(model.summary()) scale=sem) print(f"95% CI: ci")
data = df['total_bill'] mean = np.mean(data) sem = stats.sem(data) # standard error of mean ci = stats.t.interval(0.95, len(data)-1, loc=mean, scale=sem) print(f"95% CI: ci") # Definir límites limite_inferior = Q1 - 1