{ "cells": [ { "cell_type": "markdown", "id": "c0e86df8", "metadata": {}, "source": [ "# Chapter 7: Sampling\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "aa859587-e549-4925-854b-13ddecf26421", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ ":228: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n" ] } ], "source": [ "import pandas as pd\n", "import sidetable\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "from scipy.stats import norm\n", "\n", "import rpy2.robjects as ro\n", "from rpy2.robjects.packages import importr\n", "from rpy2.robjects import pandas2ri\n", "pandas2ri.activate()\n", "from rpy2.robjects.conversion import localconverter\n", "# import NHANES package\n", "base = importr('NHANES')\n", "\n", "with localconverter(ro.default_converter + pandas2ri.converter):\n", " NHANES = ro.conversion.rpy2py(ro.r['NHANES'])\n", "\n", " \n", "NHANES = NHANES.drop_duplicates(subset='ID')\n", "NHANES_adult = NHANES.dropna(subset=['Height']).query('Age > 17')\n", "\n", "rng = np.random.RandomState(12345)\n" ] }, { "cell_type": "markdown", "id": "895bf09a", "metadata": {}, "source": [ "## Table 7.1" ] }, { "cell_type": "code", "execution_count": 2, "id": "0599d110-8c0a-43c5-a815-077126d24488", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
meansd
0166.7909.942985
1168.3449.248589
2170.0969.579143
3169.1148.705499
4169.00210.450593
\n", "
" ], "text/plain": [ " mean sd\n", "0 166.790 9.942985\n", "1 168.344 9.248589\n", "2 170.096 9.579143\n", "3 169.114 8.705499\n", "4 169.002 10.450593" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "NHANES_height = NHANES_adult.dropna(subset=['Height'])\n", "\n", "sample_stats = []\n", "sampsize = 50\n", "\n", "for i in range(5):\n", " samp = NHANES_adult.sample(sampsize, random_state=rng)['Height']\n", " sample_stats.append([samp.mean(), samp.std()])\n", "\n", "sample_stats_df = pd.DataFrame(sample_stats, columns=['mean', 'sd'])\n", "\n", "sample_stats_df" ] }, { "cell_type": "markdown", "id": "fa7537ac-7ad6-4ad0-8be2-025571c20d4e", "metadata": {}, "source": [ "## Figure 7.1\n" ] }, { "cell_type": "code", "execution_count": 3, "id": "ec74ea2b-e473-4f7f-bf9a-54dc70945f94", "metadata": {}, "outputs": [], "source": [ "sampSize = 50 # size of sample\n", "nsamps = 5000 # number of samples we will take\n", "\n", "sampMeans = []\n", "for i in range(nsamps):\n", " samp = NHANES_adult.sample(sampsize, random_state=rng)['Height']\n", " sampMeans.append([samp.mean()])\n", "\n", "sampMeansDf = pd.DataFrame(sampMeans, columns=['sampleMean'])" ] }, { "cell_type": "code", "execution_count": 4, "id": "d823f2d6-bff9-4d55-965e-e5ce26cd21d9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(170.3497077244259, 0.3, 'Population mean')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAEGCAYAAAB/+QKOAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/NK7nSAAAACXBIWXMAAAsTAAALEwEAmpwYAAAjLUlEQVR4nO3de3xcVb338c8vadOWAoKmIPRiCxSB3ksoeDgo5SXIRaxyXigcBYtCHxAOB4+cR85NKwfP4/HxQbwgFRQBj4IXBKsWqWIBUXpJoZS20DaECmlFWsCWtMlcf88fsyedTPYkk2Z2Zk/6fb9eeWXvtdea+SWZzG/WWnuvbe6OiIhIsbpqByAiIvGkBCEiIqGUIEREJJQShIiIhFKCEBGRUMOqHUAlNTY2+sSJE6sdhohIzVi9evUOdx8TdmxIJYiJEyfS3Nxc7TBERGqGmf2p1DENMYmISCglCBERCaUEISIioZQgREQklBKEiIiEUoIQEZFQShAiIhJKCUJEREIpQYgMIncnmUyi+7BILVCCEBlEqVSKj9y6jFQqVe1QRPqkBCEyyOrqh9QKNzKEKUGIiEgoJQgREQmlBCEiIqGUIEREJJQShEiM1dfXM3PmTKZOncqFF17Inj17Kvr4p59+ep/3ULnlllu6Pe+5557LX//614rGIfGkBCESY6NGjWLNmjWsW7eOhoYGFi1aNOgxFCeIJUuWcMghhwx6HDL4lCBEasRpp51GS0sLr7/+Oh/84AeZPn06p5xyCmvXrgVg4cKFXHLJJZxxxhlMnjyZO+64A4BHH32U97///V2Pc80113DXXXf1ePyrrrqKpqYmpkyZwuc//3kAvv71r7Nt2zbmzp3L3LlzgdydG3fs2AHAzTffzNSpU5k6dSq33HILAFu2bOH444/niiuuYMqUKZx11ll0dHT0eL758+dz1VVXMXfuXI466igee+wxPvGJT3D88cczf/78rnpLly7lXe96F7Nnz+bCCy+kvb0dgBtvvJGTTjqJqVOnsmDBgq6LD08//XQ++9nPMmfOHI499lh+//vfD+C3vn9TghCpAel0moceeohp06bx+c9/nlmzZrF27Vr+67/+i0svvbSr3tq1a/nVr37Fk08+yY033si2bdvKfo4vfvGLNDc3s3btWh577DHWrl3Ltddey5FHHsmyZctYtmxZt/qrV6/me9/7HitWrGD58uXccccdPP300wBs3ryZq6++mvXr13PIIYdw//33hz7nG2+8we9+9zu++tWvcv755/PpT3+a9evX8+yzz7JmzRp27NjBTTfdxG9/+1ueeuopmpqauPnmm4Fcolu1ahXr1q2jo6ODX/7yl91+XytXruSWW27hC1/4Qtm/A+ku0gRhZmeb2UYzazGzG0KOzzOztWa2xsyazexvy20rsj/o6Ohg5syZNDU1MWHCBD75yU/yxBNPcMkllwBwxhln8Nprr7Fz504A5s2bx6hRo2hsbGTu3LmsXLmy7Of68Y9/zOzZs5k1axbr169nw4YNvdZ/4okn+NCHPsTo0aM58MADueCCC7o+rU+aNImZM2cCcOKJJ7Jly5bQxzj//PMxM6ZNm8bhhx/OtGnTqKurY8qUKWzZsoXly5ezYcMGTj31VGbOnMndd9/Nn/6Uu4XysmXLOPnkk5k2bRq/+93vWL9+fdfjXnDBBX0+t/Qtsks6zaweuBU4E2gDVpnZYncvfNU9Aix2dzez6cCPgePKbCsy5OXnIAqFreNkZt2+F5YPGzaMbDbbVdbZ2dmj/YsvvshXvvIVVq1axaGHHsr8+fND6/UVR96IESO6tuvr60OHmArr1dXVdWtTV1dHOp2mvr6eM888k3vvvbdbu87OTj71qU/R3NzM+PHjWbhwYbd4849VX19POp3u9eeQ0qLsQcwBWty91d2TwH3AvMIK7t7ue19lowEvt63I/urd7343P/jBD4Dc/EJjYyMHH3wwAD//+c/p7Ozktdde49FHH+Wkk07iHe94Bxs2bCCRSLBz504eeeSRHo+5a9cuRo8ezVve8hb+8pe/8NBDD3UdO+igg3jzzTdD43jwwQfZs2cPu3fv5oEHHuC0006r6M96yimn8Ic//IGWlhYA9uzZw6ZNm7qSQWNjI+3t7fz0pz+t6PNKTpSLwowFXi7YbwNOLq5kZh8C/g9wGHBef9qK1KJnfvYtPrP5Qb7xjW/sU/uFCxdy2WWXMX36dA444ADuvvvurmNz5szhvPPO46WXXuI//uM/OPLIIwH48Ic/zPTp05k8eTKzZs3q8ZgzZsxg1qxZTJkyhaOOOopTTz2169iCBQs455xzOOKII7rNQ8yePZv58+czZ84cAC6//HJmzZpV0SGdMWPGcNddd3HxxReTSCQAuOmmmzj22GO54oormDZtGhMnTuSkk06q2HPKXhbVssNmdiHwPne/PNi/BJjj7v9Qov67gc+5+3v709bMFgALACZMmHBifnxSJI6SySRjTziJ4444mMcff7zHkNBALFy4kAMPPJDrr7++Yo8pQ5+ZrXb3prBjUQ4xtQHjC/bHASVPqXD3x4GjzayxP23d/XZ3b3L3pjFjxgw8apGIOc5z23ZqyW+JvSiHmFYBk81sErAVuAj4+8IKZnYM8EIwST0baABeA/7aV1uRWlbJnkPewoULK/6Ysn+LLEG4e9rMrgEeBuqBO919vZldGRxfBPwdcKmZpYAO4CPBpHVo26hiFRGRniK9c4m7LwGWFJUtKtj+b+C/y20rIiKDR1dSi4hIKCUIEREJpQQhIiKhdPd0kUHg7qRSqV6XpxCJG/UgRAZBKpXiI7cu07UPUlOUIEQGSV199w67u5NMJtWrkNhSghCpEvUqJO6UIESqqLhXIRInShAiIhJKCUJEREIpQYiISCglCBERCaUEITJIsukUyWQS3NGJrVILlCBERCSUEoSIiIRSghAZRLkhpmpHIVIeJQgREQmlBCEiIqGUIESqwbO54SaRGFOCEKkSJQiJOyUIkSpwd664awWe1Yy1xJcShEiVaCVXiTslCBERCaUEISIioSJNEGZ2tpltNLMWM7sh5PhHzWxt8PVHM5tRcGyLmT1rZmvMrDnKOEVEpKfIBkHNrB64FTgTaANWmdlid99QUO1F4D3u/oaZnQPcDpxccHyuu++IKkYRESktyh7EHKDF3VvdPQncB8wrrODuf3T3N4Ld5cC4COMRqSp316mtUlOiTBBjgZcL9tuCslI+CTxUsO/AUjNbbWYLSjUyswVm1mxmzdu3bx9QwCJR8kyaq+5ZSX6x72w6hXu2ylGJlBbleXYWUhZ60reZzSWXIP62oPhUd99mZocBvzGz59398R4P6H47uaEpmpqadFK5xJpObZVaEmUPog0YX7A/DthWXMnMpgPfAea5+2v5cnffFnx/FXiA3JCVyJDSdRMhkRiKMkGsAiab2SQzawAuAhYXVjCzCcDPgEvcfVNB+WgzOyi/DZwFrIswVhERKRJZf9fd02Z2DfAwUA/c6e7rzezK4Pgi4HPA24BvmRlA2t2bgMOBB4KyYcAP3f3XUcUqIiI9RTog6u5LgCVFZYsKti8HLg9p1wrMKC4XGWryZzYlEgnMjIaGhmqHJNJFV1KLDIJkMhm6MJ9n0lx253JSqVQVohLpnRKESJXpzCaJKyUIkSrTmUwSV0oQIiISSglCRERCKUGIRExrMEmt0uyYSMRSqRQf//ZjhK8+IxJf6kGIDAKdqSS1SAlCRERCKUGIVFl+jsJdixFLvChBiETI3Wlvbw+9irqrTibNFXet0NXUEjtKECIR2r17N5fe9mifNwbSHIXEkRKESMT05i+1SglCRERCKUGIiEgoJQiRiCSTSV1BLTVNCUJEREIpQYiISCglCBERCaUEISIioZQgREQklBKESAxoPSaJIyUIkYj050ZBnklz2Z3LtR6TxEqkCcLMzjazjWbWYmY3hBz/qJmtDb7+aGYzym0rEnepVIrLv/vHPtdhytOSHBI3kSUIM6sHbgXOAU4ALjazE4qqvQi8x92nA/8J3N6PtiKxpzd9qWVR9iDmAC3u3uruSeA+YF5hBXf/o7u/EewuB8aV21akFmTTKc0rSM2KMkGMBV4u2G8Lykr5JPBQf9ua2QIzazaz5u3btw8gXBERKRRlggi7Q3voRykzm0suQXy2v23d/XZ3b3L3pjFjxuxToCIi0lOUA6RtwPiC/XHAtuJKZjYd+A5wjru/1p+2IiISnSh7EKuAyWY2ycwagIuAxYUVzGwC8DPgEnff1J+2IiISrbIShJndb2bnmVnZCcXd08A1wMPAc8CP3X29mV1pZlcG1T4HvA34lpmtMbPm3tqW/VOJiMiAlTvEdBtwGfB1M/sJcJe7P99XI3dfAiwpKltUsH05cHm5bUVEZPCU1SNw99+6+0eB2cAW4DfBhW2XmdnwKAMUEZHqKHvIyMzeBswn94n/aeBr5BLGbyKJTEREqqqsISYz+xlwHPB94Hx3/3Nw6Ef5eQMRERlayp2D+E4wJ9DFzEa4e8LdmyKIS0REqqzcIaabQsqerGQgIiISL732IMzs7eSWuBhlZrPYe4XzwcABEccmIiJV1NcQ0/vITUyPA24uKH8T+NeIYhIRkRjoNUG4+93A3Wb2d+5+/yDFJCIiMdDXENPH3P1/gIlm9k/Fx9395pBmIiIyBPQ1xDQ6+H5g1IGIiEi89DXE9O3g+xcGJxyR/Vc2nSKZTNLQ0FDtUESA8hfr+7KZHWxmw83sETPbYWYfizo4ERGpnnKvgzjL3XcB7yd3r4ZjgX+OLCoREam6chNEfkG+c4F73f31iOIREZGYKHepjV+Y2fNAB/ApMxsDdEYXloiIVFu5y33fALwLaHL3FLAbmBdlYCIiUl39uSf18eSuhyhsc0+F4xERkZgod7nv7wNHA2uATFDsKEGIiAxZ5fYgmoAT3N2jDEZkKHB3UqkU+neRWlfuWUzrgLdHGYjIUJFKpfjIrctIpVL9apdJJWlvb1dikdgoN0E0AhvM7GEzW5z/ijIwkVpWV9+f6b0cz6RZcM/qficWkaiU+ypeGGUQIpJTN6z/iUUkKmW9Gt39MTN7BzDZ3X9rZgcA9dGGJiIi1VTuWkxXAD8Fvh0UjQUeLKPd2Wa20cxazOyGkOPHmdmTZpYws+uLjm0xs2fNbI2ZNZcTp0itc3eSyaTmISQWyp2DuBo4FdgF4O6bgcN6a2Bm9cCtwDnACcDFZnZCUbXXgWuBr5R4mLnuPtPdm8qMU6SmZRIdfHTR45qHkFgoN0Ek3D2Z3wkuluvrI84coMXdW4O291F09bW7v+ruqwD9N4gE9mWCWyQK5SaIx8zsX4FRZnYm8BPgF320GQu8XLDfFpSVy4GlZrbazBaUqmRmC8ys2cyat2/f3o+HF4lO/pRVkVpWboK4AdgOPAv8L2AJ8O99tLGQsv4MrJ7q7rPJDVFdbWbvDqvk7re7e5O7N40ZM6YfDy8SHc+kueqelbhnqx2KyD4r9yymrJk9CDzo7uV+TG8DxhfsjwO2lRuYu28Lvr9qZg+QG7J6vNz2ItVWVz+MbFqjp1K7eu1BWM5CM9sBPA9sNLPtZva5Mh57FTDZzCaZWQNwEVDWxXVmNtrMDspvA2eRu5pbREQGSV89iOvInb10kru/CGBmRwG3mdmn3f2rpRq6e9rMrgEeJnfNxJ3uvt7MrgyOLzKztwPNwMFA1syuI3fGUyPwgJnlY/yhu/96339MERHpr74SxKXAme6+I1/g7q3B/aiXAiUTRFB3Cbn5isKyRQXbr5Abeiq2C5jRR2wiIhKhviaphxcmh7xgHmJ4SH0RERki+koQyX08JiIiNa6vIaYZZrYrpNyAkRHEIyIiMdFrgnB3LcgnIrKfKvdCORER2c8oQYjEjFZ0lbhQghCJGc+k+di3n9CKrlJ1ShAiMaQVXSUOlCBERCSUEoSIiIRSghCJoWw6RTKpa1GlupQgRGImm07pPhISC0oQIiISSglCpMKSySSe1TUMUvuUIEREJJQShIiIhFKCEImpZDKpM5mkqpQgREQklBKEiIiEUoIQEZFQShAiIhJKCUJEREIpQYiISKhIE4SZnW1mG82sxcxuCDl+nJk9aWYJM7u+P21FRCRakSUIM6sHbgXOAU4ALjazE4qqvQ5cC3xlH9qKDFm67ajEQZQ9iDlAi7u3unsSuA+YV1jB3V9191VA8b0V+2wrEjeVfFP3TJor7lqh245KVUWZIMYCLxfstwVlFW1rZgvMrNnMmrdv375PgYpUQiqV4iO3LqvYm7puOyrVFmWCsJCycj9ald3W3W939yZ3bxozZkzZwYlEQW/qMpREmSDagPEF++OAbYPQVqRqdCc4GUqiTBCrgMlmNsnMGoCLgMWD0FZERCogsv6wu6fN7BrgYaAeuNPd15vZlcHxRWb2dqAZOBjImtl1wAnuviusbVSxilRKfqJaZCiIdMDU3ZcAS4rKFhVsv0Ju+KistiJx55k0V92zUnMRMiToSmqRClNykKFCCUJEREIpQYiISCglCBERCaUEISIioZQgREQklBKEiIiEUoIQqQBdICdDkRKESAWkUik+etujeFb3b5ChQwlCpEIqfYGcbhok1aYEIRJTnklz2Z3LddMgqRolCJEY07IdUk1KECIiEkoJQqRCsukU7tlqhyFSMUoQIiISSglCpAKSyWQkp7jqFqZSTUoQIiISSglCRERCKUGIiEgoJQgREQmlBCEiIqGUIEREJJQShEjMJZNJneoqVRFpgjCzs81so5m1mNkNIcfNzL4eHF9rZrMLjm0xs2fNbI2ZNUcZp4iI9BTZSmBmVg/cCpwJtAGrzGyxu28oqHYOMDn4Ohm4LfieN9fdd0QVo0glJBIJ2tvbqx2GSMVF2YOYA7S4e6u7J4H7gHlFdeYB93jOcuAQMzsiwphEKi6VSnH5d/+odZhkyIkyQYwFXi7YbwvKyq3jwFIzW21mCyKLUmQA8jf10bLcMhRF+aq2kLLixWp6q3Oqu28zs8OA35jZ8+7+eI8nySWPBQATJkwYSLwi/ZZKpfj4tx8j/KU8cLqrnFRTlD2INmB8wf44YFu5ddw9//1V4AFyQ1Y9uPvt7t7k7k1jxoypUOgi5Yuy9+CZNFfctUJ3lZOqiDJBrAImm9kkM2sALgIWF9VZDFwanM10CrDT3f9sZqPN7CAAMxsNnAWsizBWkdjS8JVUS2SvPHdPm9k1wMNAPXCnu683syuD44uAJcC5QAuwB7gsaH448ICZ5WP8obv/OqpYRUSkp0g/mrj7EnJJoLBsUcG2A1eHtGsFZkQZm0glZDIZOjo6yWYyAIwcORKLZjpCZNCp7yoyAC0tLezu2EPD8OF0JhIAjBo1slsdx+nsSFQjPJEBUYIQKUMmk6GlpaVr/5hjjqG+vh6AUQ0jaBgxvGTbjo4EHYlORo4YQWciQTabpa5Oq9xI/ClBiJRQmBRaW1tpb2/n6KOP5sUXXwTgne98Z9mPNXLECEaNHNGtzB06Ozu79huG1fc4WdYdOjo62bRpE6NHj+6WmESipgQhQ1bxp36gX2+wLS0trFu3jkmTJrF582YmTJjA5MmTu44nk0n27NlDNrhGwR06UnuHkkaOHNnjMd0hm81dcf3Grp1kM1lGjgx6FsOHc8CwYd0SR0cygbuxY8cOnn/+eZLJJFOnTsUKJjp6692IDIT6uTJk5d/gd+/eze7du1m3bl2PhNGXSZMmMXnyZMaNG9etPGyF1UQyQSKRIONZdnd2dOsdFNbJZj1IAgnMjFEjRzCiYQQdyQR7Ojp5Y9dOdnd0kPEsnZ0J8Cy3rGqnsbGR63++ucc1EYU/Zzk/YyaTYePGjd2+MsEku0gh9SBkSCkeFir+1B9WD/Z+6i5u39jY2K/nbxjewKiRI3K9iWSCbKaeznSahuENXXXq6oz6OqOhYe+8RT65jGgYSWdnghENucfJT3zXDRsWfA+f68gnskwmQ2tra58/V364DNinITPZPyhByJBSPCyUSCQ47rjjeq3X0tJCa2srRx11VLc3z97a9yWRTJBKpRg2amTQC4ADRo3otU3D8AZGjhxJIrXv9354+eWX2bZtG4cffni3N/6+hstEwihByJCT/zS9ZcuWsuu98MILHH744d3ePEu1z2QytLW1kUqlut6EwzQMb2DUiAaSqfQAfpruz9vR0cnGjRu75hjq6+t79HTGjRvXozdR2Jvq7fei+QwppAQhsVPO8E+p8t6GhYrfMMPeVPtKKpD7lP7SSy/x1re+ldbWVhLJsYwc2dBnu4Fwd1566SUSnQewZ88eVqxYQV1dHX/zN39TsqdT2JsotzdU2NMoNfSkJLL/UIKQ2Cn1JlVOeW9vhPvyhlnK2LFjOfroo3nhhRdg577/rOXyTJrvbaqjYdRwjjnmGLZu3UpdXV2fSa2cxFeqp1FKqb+DEsfQowQhsZQf/ulveV89gP70FHrTfRnuwVlbwyJatK9U4ixMHPmznPJDWmFJpJzeh9QWJQiJhVLDRKWGhXobLhqseK/6n6eY15jA6Xm9Q1Siuj9EWOIsTBxPPPFE6JBWf3sfUlt0HYTEQuG5/Js3b2br1q1A7k3qhRdeKLt8MJnB9zbV5a5+GySezbDg+0+RTldm4rsv+cQxbty4btt5cfg7SHTUg5BB1ds4dalholLDQpUaLhqIqIZ9epO/JiIuwv4O5VyPUVgu8RSvV5oMeRqn3j8UDk+Vus5Ef//4U4KQSJTTU6j2PIJEq7BnEXadicSf5iAkEoVzCs888wxLly5l48aNtLa2dp0RU6vj1+4ezAEM3txD2PNXeqI6SmHzFxJ/ShASmXxPYdiwYSUTQa29cbg7nZ2dLFqbqtobdCbRwW3rsoM2UT0YihcQ1OKB8aAhJhmQcicd4zChXAmpVIrbns1AXXUnVqsxOV5pxUOMYXMTha+vwmsxQBPcg6H2X2VSVb0tejfU5hRSqRTJZBKrH4anU303kF4VX6CXn5solTgKr8XQFdyDQwlCuunvOkhQetG7gSxlIb2rxXmIMH1doFe8eGJ+eZFCOjMuOkoQ+6lSb/jlrHfUW09hqAwlhXF32tvbyaST1Zqf3htLNsOta7Kcfvru6gYSkb5eR7qCe3AoQQxx5SSC4jf8Ul39wk9y+1tPwd1JJBJce+/TuDs2SOsvFctm0rjnblman4dwd1Kp6k2aV0N/14/S/MW+UYIY4nrrfvc1NNTb6qdDuacAuVuKplIpGhoaurYXPZvioNHDc0trWHUSRF42k8YxEokEnZ2d3L7BOOOM/WtepD/rRxVuF34gKk4cSiTdRZogzOxs4GtAPfAdd/9S0XELjp8L7AHmu/tT5bTdH5U6o6P4RQ39vzAtzstZVFM6neYT31vBh4/IxPLMod27d/OttSmGNYyqdiixUfiaLVwSvXA7/4GoMHEAJSfCC5UzKT5UJs4je8WbWT1wK3Am0AasMrPF7r6hoNo5wOTg62TgNuDkMtvWjIHcAKd4meWwMzqKX+Sl5ggqeT+E/UF+IriuLn6JoZDVD+ta5TWbzV0fkUgk9qshp/4KSyJAt/3eljvP/x+W6o2Uc9ou9C9xVOOU3yhf+XOAFndvBTCz+4B5QOGb/DzgHs+9kpeb2SFmdgQwsYy2FbVx48aoHprW1laee+45xo4dy9atWzn++OO73rz7Kn/66aepq6tjxowZPP3004wbN67rZvOlvPLKK6xZs4Zdu3Z1tamvr6etrY26ur3XRra1tbF58+au8qG8nf95y23T0tLCpk2bePDVQ3nLobDxrxvp2HMEls3Q2dGB1Rm7h9Xnto2S2/XmPepns1kyZj3qezbNnj0NfT5m4fbmzZvZ0/4mdfX1/P03H2HuiFZ+vv1QFq1byvsPeYWGhoaK/l6G8nbx7+LJJ5/klVde6fo/Cvs/LP5fK/W/WthzD/uf7+/7SOFzbd26lfPOOy+SM7eiTBBjgZcL9tvI9RL6qjO2zLYAmNkCYEGw225m0b3TD1wjsKPaQeyDWo0bKhT7owOPo4c137y6t8Nlxf2hb3Tff7Rge9k+xFQBtfpaqem4P/OZzwzkMd5R6kCUCSJsFq+4z1uqTjltc4XutwO39y+06jCzZndvqnYc/VWrcUPtxq64B5fiDhdlgmgDxhfsjwO2lVmnoYy2IiISoSgX61sFTDazSWbWAFwELC6qsxi41HJOAXa6+5/LbCsiIhGKrAfh7mkzuwZ4mNypqne6+3ozuzI4vghYQu4U1xZyp7le1lvbqGIdRDUxFBaiVuOG2o1dcQ8uxR3CdCqciIiE0f0gREQklBKEiIiEUoKoIDO708xeNbN1IceuNzM3s8aCsn8xsxYz22hm7xvcaLvF1iNuM1toZlvNbE3wdW7BsdjGHZT/QxDbejP7ckF5bOM2sx8V/K63mNmagmOxiDuIJSz2mWa2PIi92czmFByLRewl4p5hZk+a2bNm9gszO7jgWNXjNrPxZrbMzJ4LXsv/GJS/1cx+Y2abg++HRha3u+urQl/Au4HZwLqi8vHkJtz/BDQGZScAzwAjgEnAC0B9XOIGFgLXh9SNe9xzgd8CI4L9w2oh7qLj/w/4XNzi7uV3vhQ4J9g+F3g0brGXiHsV8J5g+xPAf8YpbuAIYHawfRCwKYjty8ANQfkNwH9HFbd6EBXk7o8Dr4cc+irwv+l+sd884D53T7j7i+TO5JoT0jZyvcQdJu5xXwV8yd0TQZ1Xg/K4xw10LWD5YeDeoCg2cUPJ2B3If/p+C3uvWYpN7CXififweLD9G+Dvgu1YxO3uf/Zg8VJ3fxN4jtwqE/OAu4NqdwMfDLYrHrcSRMTM7APAVnd/puhQqWVG4uQaM1sbdM/z3di4x30scJqZrTCzx8zspKA87nHnnQb8xd03B/u1EPd1wP81s5eBrwD/EpTHPfZ1wAeC7QvZe3Fu7OI2s4nALGAFcLjnrhcj+H5YUK3icStBRMjMDgD+Dfhc2OGQsjidc3wbcDQwE/gzuWEPiH/cw4BDgVOAfwZ+HHwqj3vceRezt/cAtRH3VcCn3X088Gngu0F53GP/BHC1ma0mN4STDMpjFbeZHQjcD1zn7rt6qxpSNqC4lSCidTS5scBnzGwLuSVDnjKzt1PeUiRV4+5/cfeM525fdgd7u6qxjptcfD/znJVAltyCZnGPGzMbBlwA/KigOPZxAx8HfhZs/4Qaea24+/Pufpa7n0guKb8QHIpN3GY2nFxy+IG753/Hf7HcqtcE3/PDqBWPWwkiQu7+rLsf5u4T3X0iuT/gbHd/hdzSIReZ2Qgzm0TunhgrqxhuN/kXYOBD5LrjEPO4gQeBMwDM7Fhy63rtIP5xA7wXeN7d2wrKaiHubcB7gu0zgPzwWKxjN7PDgu91wL8Di4JDsYg76Pl+F3jO3W8uOLSYXFIm+P7zgvLKxj3YM/ND+Yvcp5A/AylyyeCTRce3EJzFFOz/G7lPLRsJzgKJS9zA94FngbXBC++IGom7AfgfcgntKeCMWog7KL8LuDKkfizi7uV3/rfAanJn0KwAToxb7CXi/kdyZwZtAr5EsLJEXOIOfq8e/A+uCb7OBd4GPEIuET8CvDWquLXUhoiIhNIQk4iIhFKCEBGRUEoQIiISSglCRERCKUGIiEgoJQiRMphZe9H+fDP7Zh9tPmBmN/RR53Qz+2WJY9cFV+OLVIUShEhE3H2xu39pAA9xHaAEIVWjBCEyQGY2xszuN7NVwdepQXlXL8PMjg7umbDKzG4s6pEcaGY/NbPnzewHlnMtcCSwzMyWVeHHEmFYtQMQqRGjCm/iA7yV3BXmAF8DvuruT5jZBHL3/ji+qP3XgK+5+71mdmXRsVnAFHJLVvwBONXdv25m/wTMdfcdFf5ZRMqiBCFSng53n5nfMbP5QFOw+17ghNzSOQAcbGYHFbV/F3vX7f8huWWx81Z6sP5SkIQmAk9ULHKRfaQEITJwdcC73L2jsLAgYfQlUbCdQf+XEhOagxAZuKXANfkdM5sZUmc5e+9YdlGZj/smufsUiFSFEoTIwF0LNAV339sAFM8xQO6MpH8ys5Xk7jW8s4zHvR14SJPUUi1azVVkEATXM3S4u5vZRcDF7j6v2nGJ9EZjnSKD40Tgm8FNYP5K7naXIrGmHoSIiITSHISIiIRSghARkVBKECIiEkoJQkREQilBiIhIqP8P/AYjhUmzNNsAAAAASUVORK5CYII=\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.histplot(NHANES_adult.Height, color='gray', alpha=0.1, stat='density', bins=100)\n", "sns.histplot(sampMeansDf.sampleMean, stat='density', bins=100)\n", "plt.plot([NHANES_adult.Height.mean(), NHANES_adult.Height.mean()], [0, 0.3], color='black')\n", "plt.annotate('Population mean', [NHANES_adult.Height.mean() + 2, 0.3])" ] }, { "cell_type": "markdown", "id": "ab1bd251", "metadata": {}, "source": [ "## Figure 7.2" ] }, { "cell_type": "code", "execution_count": 21, "id": "2e7b2c41-8e60-40bf-bf10-fb3af6920032", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[]" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "NHANES_clean = NHANES_adult.query('AlcoholYear >= 0').dropna(subset=['AlcoholYear'])\n", "\n", "fig, ax = plt.subplots(1, 2, figsize=(12,6))\n", "\n", "sns.histplot(NHANES_clean.AlcoholYear, ax=ax[0])\n", "\n", "def get_sampling_dist(sampSize=50, nsamps=2500):\n", " sampMeans = []\n", " for i in range(nsamps):\n", " samp = NHANES_clean.sample(sampsize, random_state=rng)['AlcoholYear']\n", " sampMeans.append([samp.mean()])\n", " return(pd.DataFrame(sampMeans, columns=['sampleMean']))\n", "\n", "sampDist = get_sampling_dist()\n", "sns.histplot(sampDist.sampleMean, bins=100, stat='density', element='poly', fill=None)\n", "x = np.arange(sampDist.sampleMean.min(), sampDist.sampleMean.max(), 0.1)\n", "y = norm.pdf(x, loc=sampDist.sampleMean.mean(), scale=sampDist.sampleMean.std())\n", "plt.plot(x,y, color='red')" ] } ], "metadata": { "Rmd_chunk_options": { "output": { "bookdown::gitbook": { "includes": { "in_header": "google_analytics.html" }, "lib_dir": "book_assets" }, "html_document": "default", "pdf_document": "default" } }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.15" }, "sos": { "kernels": [ [ "SoS", "sos", "", "" ], [ "R", "ir", "", "" ], [ "Markdown", "markdown", "", "" ] ] } }, "nbformat": 4, "nbformat_minor": 5 }