statkclee/chap04soln-kor.ipynb

## chap04soln-kor.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "통계적 사고 (2판) 연습문제 ([thinkstats2.com](thinkstats2.com), [think-stat.xwmooc.org](http://think-stat.xwmooc.org))<br>\n",
    "Allen Downey / 이광춘(xwMOOC)\n",
    "\n",
    "임신 파일을 읽어들이시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import nsfg\n",
    "preg = nsfg.ReadFemPreg()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "정상출산을 고르고 나서, <tt>totalwgt_lb</tt>에 대한 CDF를 생성하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import thinkstats2\n",
    "live = preg[preg.outcome==1]\n",
    "firsts = live[live.birthord==1]\n",
    "others = live[live.birthord>1]\n",
    "cdf = thinkstats2.Cdf(live.totalwgt_lb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "CDF를 화면에 출력하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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pvyW9IyIeyrrQOllOYA9CkAOQUkLd9gpJWyWtl3RQ0gO2d0XE7q5zLpL0iohYa/u1km6U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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xac1e456c>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb13a2f8c>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import thinkplot\n",
    "thinkplot.Cdf(cdf, label='totalwgt_lb')\n",
    "thinkplot.Show(loc='lower right')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "할 수 있다면, 출생당시 여러분이 얼마나 체중이 나가는지 알아내고, CDF(x)를 계산하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.54414693516264656"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdf.Prob(3.4*2.2) # 1Kg = 2.204623 lb (Kg, 파운드 무게변환)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "만약 여러분이 첫째라면, 첫번째 아기에 대한 CDF에서 출생체중을 찾아보시오; 첫째가 아니라면, 첫째가 아닌 아기에 대한 CDF를 사용하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('If I am the other baby, ', 0.56451982580793036)\n",
      "('If I am the first baby, ', 0.5251336898395722)\n"
     ]
    }
   ],
   "source": [
    "first_cdf = thinkstats2.Cdf(firsts.totalwgt_lb)\n",
    "print('If I am the other baby, ', first_cdf.Prob(3.4*2.2))\n",
    "other_cdf = thinkstats2.Cdf(others.totalwgt_lb)\n",
    "print('If I am the first baby, ', other_cdf.Prob(3.4*2.2)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "출생체중에 대한 백분위순위를 계산하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "54.414693516264656"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdf.PercentileRank(3.4*2.2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "p=0.5와 연관된 값을 찾아서 출생체중 중위를 계산하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.375"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdf.Value(0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "25 백분위수와 75 백분위수를 계산해서 사분위수 범위를 계산하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('75 Percentile ', 6.5)\n",
      "('25 Percentile ', 8.125)\n"
     ]
    }
   ],
   "source": [
    "print('75 Percentile ', cdf.Percentile(25))\n",
    "print('25 Percentile ', cdf.Percentile(75))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<tt>cdf</tt>에서 무작위 선택을 하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.0"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdf.Random()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<tt>cdf</tt>에서 무작위 표본을 뽑으시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 8.0625,  8.6875,  1.5625,  7.5   ,  8.    ])"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdf.Sample(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<tt>cdf</tt>에서 무작위 표본을 뽑고나서, 각 값에 대한 백분위수를 계산하고, 백분위순위 분포를 도식화하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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fTwAXAP8DvKeq7ht2zFGrZAx3Sdq8oS2aJDuAa4Bl4ExgT5Iz1u1zIfDyqjodeD/wqWHH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\nhjLgJamhDHhJaigDXpIayoCXpIb6f8VDBg0EdkuRAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xac1d990c>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0xac1d982c>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sample = [cdf.PercentileRank(x) for x in cdf.Sample(1000)]\n",
    "cdf2 = thinkstats2.Cdf(sample)\n",
    "thinkplot.Cdf(cdf2)\n",
    "thinkplot.Show(legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<tt>random.random()</tt>을 사용해서 1000 난수를 생성하고, 난수의 PMF를 도식화하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Wkg4QY4wFChMj68kZkwwWKGJiVaT/3oQFlIM1QnkkNY9JTXclFihM3Wz0yJjqJC2gWKBI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\njDGmLAsUxhhjyrJAYYwxpqz/DzNMI8ecP2OKAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xae8e7a0c>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0xae857a0c>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import random\n",
    "t = [random.random() for _ in range(1000)]\n",
    "pmf = thinkstats2.Pmf(t)\n",
    "thinkplot.Pmf(pmf, linewidth=0.1)\n",
    "thinkplot.Show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "PMF가 잘 동작하지 않는다고 가정하고, 대신에 CDF 도식화를 시도하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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M4cuqKaIx3CmqeAr2rh0aIq51XW7RS5bAcKeosXHLXrw24mOX9nJlS2HpzH5cVydL4a6Q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\n8fLi3fyfAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xae8e0ecc>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0xaeb9f06c>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cdf = thinkstats2.Cdf(t)\n",
    "thinkplot.Cdf(cdf)\n",
    "thinkplot.Show()"
   ]
  },
  {
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