Think Stats 2, 2장 연습문제

chap02ex-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",
    "여성 응답자 파일을 읽어들여 변수명을 표시하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'caseid', u'rscrinf', u'rdormres', u'rostscrn', u'rscreenhisp',\n",
       "       u'rscreenrace', u'age_a', u'age_r', u'cmbirth', u'agescrn',\n",
       "       ...\n",
       "       u'pubassis_i', u'basewgt', u'adj_mod_basewgt', u'finalwgt', u'secu_r',\n",
       "       u'sest', u'cmintvw', u'cmlstyr', u'screentime', u'intvlngth'],\n",
       "      dtype='object', length=3087)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import chap01soln\n",
    "resp = chap01soln.ReadFemResp()\n",
    "resp.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "응답자 가족에 대한 총소득 <tt>totincr</tt> 히스토그램을 생성하시오. 코드를 해석하기 위해서, [codebook](http://www.icpsr.umich.edu/nsfg6/Controller?displayPage=labelDetails&fileCode=MALE&section=R&subSec=7958&srtLabel=609776)을 살펴보시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import thinkstats2\n",
    "hist = thinkstats2.Hist(resp.totincr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "히스토그램을 화면에 표시하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEACAYAAAC08h1NAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0xb495c2ec>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0xaf2f43cc>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import thinkplot\n",
    "thinkplot.Hist(hist, label='totincr')\n",
    "thinkplot.Show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "인터뷰 당시 응답자 나이 변수, <tt>age_r</tt>에 대한 히스토그램을 생성하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "응답자 가구의 가구원수, <tt>numfmhh</tt>에 대한 히스토그램을 생성하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "응답자가 낳은 자녀수, <tt>parity</tt>에 대한 히스토그램을 생성하시오. 이 분포를 어떻게 기술할까요?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hist.Largest를 사용해서 <tt>parity</tt>의 가장 큰 수를 찾으시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<tt>totincr</tt>를 사용해서 가장 높은 임금을 갖는 응답자를 고르시오. 고임금 응답자에 대해서만 <tt>parity</tt> 분포를 계산하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "고임금 응답자에 대한 가장 큰 <tt>parity</tt>를 구하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "고임금과 고임금이 아닌 집단에 대한 평균 <tt>parity</tt>를 비교하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "다른 흥미로워 보이는 변수도 조사하시오."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}