From 394f85863acabbfe91ec715e40eb6d6d6e664af7 Mon Sep 17 00:00:00 2001 From: mbi6245 Date: Mon, 5 Aug 2024 10:45:23 -0700 Subject: [PATCH] include sample size in sigma passed to univariate simulations --- simulations.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/simulations.ipynb b/simulations.ipynb index acb8dcb..537ee03 100644 --- a/simulations.ipynb +++ b/simulations.ipynb @@ -53,14 +53,14 @@ " # generate data from given distribution, calculate sample_mean, sample_sd\n", " data = distribution_func(size=sample_size, **distribution_params)\n", " x_bar = np.mean(data)\n", - " sigma_hat = np.std(data)\n", + " sigma_hat = np.std(data) / np.sqrt(sample_size)\n", "\n", " # run delta method transformation for transformed_mean and transformed_sd\n", " mu_txs[i], sigma_tx = transform_univariate(x_bar, sigma_hat, transform_func, \"delta\")\n", "\n", " # calculate CI bounds with transformed_mean + Q * transformed_sd / sqrt(sample_size)\n", - " ci_uppers[i] = mu_txs[i] + Q * sigma_tx / np.sqrt(sample_size)\n", - " ci_lowers[i] = mu_txs[i] - Q * sigma_tx / np.sqrt(sample_size)\n", + " ci_uppers[i] = mu_txs[i] + Q * sigma_tx\n", + " ci_lowers[i] = mu_txs[i] - Q * sigma_tx\n", "\n", " # indicate coverage success when transformed mean lies between CI bounds as described above\n", " if (ci_lowers[i] < truth and truth < ci_uppers[i]):\n",