Data Science, Product Analytics, Ab Testing, Simulation, Deep Dives.
get_ci_for_retention(df, boot_iters, confidence_level): tmp_data = [] for iter in range(boot_iters): sample_df = df.sample(df.shape[0], replace = True) ret_model = smf.logit('retention ~ treatment + num_family_members', data = sample_df).fit(disp = 0) tmp_data.append( { 'iteration': iter, 'coef':