memo.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%reload_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "# ヒストグラムなどの表示のため\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1.804  2.196]\n"
     ]
    }
   ],
   "source": [
    "# Q1\n",
    "import numpy as np\n",
    "n=100\n",
    "ave = 2.0\n",
    "s = 1.0\n",
    "z = 1.96\n",
    "\n",
    "range = 2 + np.array([-z, z]) * s/np.sqrt(n)\n",
    "\n",
    "print(range)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A : (0.57823641544501547, 0.92508848972329294)\nB : (0.043939011276519502, 0.36884859936045405)\nC : (-0.0091018716816653328, 0.25411451392920281)\n"
     ]
    }
   ],
   "source": [
    "# Q3\n",
    "\n",
    "n=20\n",
    "A=16\n",
    "B=3\n",
    "C=1\n",
    "\n",
    "import statsmodels.stats.proportion as sm\n",
    "A_hat = sm.proportion_confint(count=A, nobs=n, method=\"agresti_coull\")\n",
    "print(\"A :\", A_hat)\n",
    "B_hat = sm.proportion_confint(count=B, nobs=n, method=\"agresti_coull\")\n",
    "C_hat = sm.proportion_confint(count=C, nobs=n, method=\"agresti_coull\")\n",
    "print(\"B :\", B_hat)\n",
    "print(\"C :\", C_hat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "48018.2352587\n"
     ]
    }
   ],
   "source": [
    "# Q4.\n",
    "import statsmodels.stats.proportion as sm\n",
    "inf = sm.samplesize_confint_proportion(alpha=0.05, proportion=0.5, half_length=0.01)\n",
    "print(inf * 1/0.2) # 0.2 : 返信率"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3.0
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}