Week10_Lecture1SANDBOX.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# POLISCI 3 Fall 2021\n",
    "\n",
    "## Week 10 Sandbox Notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 6 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>republican</th><th scope=col>incumbent</th><th scope=col>marriage_perception</th><th scope=col>marriage_opinion</th><th scope=col>religexempt_perception</th><th scope=col>religexempt_opinion</th><th scope=col>gunsbanassault_perception</th><th scope=col>gunsbanassault_opinion</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>1</td><td>0</td><td>50</td><td>69</td><td>60</td><td>34</td><td>70</td><td>70</td></tr>\n",
       "\t<tr><th scope=row>2</th><td>1</td><td>0</td><td>10</td><td>48</td><td>60</td><td>49</td><td>10</td><td>46</td></tr>\n",
       "\t<tr><th scope=row>3</th><td>1</td><td>1</td><td>25</td><td>53</td><td>65</td><td>46</td><td>NA</td><td>58</td></tr>\n",
       "\t<tr><th scope=row>4</th><td>0</td><td>0</td><td>50</td><td>67</td><td>30</td><td>38</td><td>NA</td><td>70</td></tr>\n",
       "\t<tr><th scope=row>5</th><td>1</td><td>0</td><td>25</td><td>52</td><td>70</td><td>44</td><td>NA</td><td>60</td></tr>\n",
       "\t<tr><th scope=row>6</th><td>0</td><td>1</td><td>NA</td><td>71</td><td>NA</td><td>35</td><td>NA</td><td>69</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       "  & republican & incumbent & marriage\\_perception & marriage\\_opinion & religexempt\\_perception & religexempt\\_opinion & gunsbanassault\\_perception & gunsbanassault\\_opinion\\\\\n",
       "  & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\t1 & 1 & 0 & 50 & 69 & 60 & 34 & 70 & 70\\\\\n",
       "\t2 & 1 & 0 & 10 & 48 & 60 & 49 & 10 & 46\\\\\n",
       "\t3 & 1 & 1 & 25 & 53 & 65 & 46 & NA & 58\\\\\n",
       "\t4 & 0 & 0 & 50 & 67 & 30 & 38 & NA & 70\\\\\n",
       "\t5 & 1 & 0 & 25 & 52 & 70 & 44 & NA & 60\\\\\n",
       "\t6 & 0 & 1 & NA & 71 & NA & 35 & NA & 69\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 8\n",
       "\n",
       "| <!--/--> | republican &lt;int&gt; | incumbent &lt;int&gt; | marriage_perception &lt;int&gt; | marriage_opinion &lt;int&gt; | religexempt_perception &lt;int&gt; | religexempt_opinion &lt;int&gt; | gunsbanassault_perception &lt;int&gt; | gunsbanassault_opinion &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|\n",
       "| 1 | 1 | 0 | 50 | 69 | 60 | 34 | 70 | 70 |\n",
       "| 2 | 1 | 0 | 10 | 48 | 60 | 49 | 10 | 46 |\n",
       "| 3 | 1 | 1 | 25 | 53 | 65 | 46 | NA | 58 |\n",
       "| 4 | 0 | 0 | 50 | 67 | 30 | 38 | NA | 70 |\n",
       "| 5 | 1 | 0 | 25 | 52 | 70 | 44 | NA | 60 |\n",
       "| 6 | 0 | 1 | NA | 71 | NA | 35 | NA | 69 |\n",
       "\n"
      ],
      "text/plain": [
       "  republican incumbent marriage_perception marriage_opinion\n",
       "1 1          0         50                  69              \n",
       "2 1          0         10                  48              \n",
       "3 1          1         25                  53              \n",
       "4 0          0         50                  67              \n",
       "5 1          0         25                  52              \n",
       "6 0          1         NA                  71              \n",
       "  religexempt_perception religexempt_opinion gunsbanassault_perception\n",
       "1 60                     34                  70                       \n",
       "2 60                     49                  10                       \n",
       "3 65                     46                  NA                       \n",
       "4 30                     38                  NA                       \n",
       "5 70                     44                  NA                       \n",
       "6 NA                     35                  NA                       \n",
       "  gunsbanassault_opinion\n",
       "1 70                    \n",
       "2 46                    \n",
       "3 58                    \n",
       "4 70                    \n",
       "5 60                    \n",
       "6 69                    "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "library(ggplot2)\n",
    "data <- read.csv('broockman_skovron.csv')\n",
    "head(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is an overview of what the columns in the dataset represent: \n",
    "\n",
    "- `republican`: whether the state legislator or state legislative candidate who answered the survey was a Republican (1 = Republican, 0 = Democrat)\n",
    "- `incumbent`: whether the person who answered the survey was an incumbent representative (i.e., currently holds political office) (1 = already holds office, 0 = just a candidate)\n",
    "- `marriage_perception`: what percent of the politician's constituents they think support same-sex marriage\n",
    "- `marriage_opinion`: what percent of the politician's constituents actually support same-sex marriage\n",
    "- `religexempt_perception`: what percent of the politician's constituents they think support allowing employers to refuse to cover birth control for employees if it violates their religious beliefs\n",
    "- `religexempt_opinion`: what percent of the politician's constituents actually support allowing employers to refuse to cover birth control for employees if it violates their religious beliefs\n",
    "- `gunsbanassault_perception`: what percent of the politician's constituents they think support banning assault weapons\n",
    "- `gunsbanassault_opinion`: what percent of the politician's constituents actually support banning assault weapons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "38.3775773195876"
      ],
      "text/latex": [
       "38.3775773195876"
      ],
      "text/markdown": [
       "38.3775773195876"
      ],
      "text/plain": [
       "[1] 38.37758"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the average percent of the politician's constituents they think support banning assault weapons? \n",
    "# In other words, on average, how much support for banning assault weapons do politicians think there is?\n",
    "avg.politician.perception <- mean(data$gunsbanassault_perception, na.rm = TRUE)\n",
    "avg.politician.perception"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "61.150356448477"
      ],
      "text/latex": [
       "61.150356448477"
      ],
      "text/markdown": [
       "61.150356448477"
      ],
      "text/plain": [
       "[1] 61.15036"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the average support for banning assault weapons?\n",
    "avg.constitutent.support <- mean(data$gunsbanassault_opinion, na.rm = TRUE)\n",
    "avg.constitutent.support"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "-22.8541666666667"
      ],
      "text/latex": [
       "-22.8541666666667"
      ],
      "text/markdown": [
       "-22.8541666666667"
      ],
      "text/plain": [
       "[1] -22.85417"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# What is the AVERAGE difference between politicians' perceptions and constituent opinion?\n",
    "difference <- mean(data$gunsbanassault_perception - data$gunsbanassault_opinion, na.rm = TRUE)\n",
    "difference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "-19.986301369863"
      ],
      "text/latex": [
       "-19.986301369863"
      ],
      "text/markdown": [
       "-19.986301369863"
      ],
      "text/plain": [
       "[1] -19.9863"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "-24.6134453781513"
      ],
      "text/latex": [
       "-24.6134453781513"
      ],
      "text/markdown": [
       "-24.6134453781513"
      ],
      "text/plain": [
       "[1] -24.61345"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "Design:  Standard \n",
       "          Estimate Std. Error  t value    Pr(>|t|) CI Lower CI Upper       DF\n",
       "incumbent 4.627144   1.522081 3.040012 0.002464069 1.638163 7.616125 628.3975"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How do we figure out whether incumbents are better at knowing constituent opinion?\n",
    "incumbents <- subset(data, incumbent == 1)\n",
    "difference.incumbents <- mean(incumbents$gunsbanassault_perception - incumbents$gunsbanassault_opinion, \n",
    "                              na.rm = TRUE)\n",
    "\n",
    "nonincumbents <- subset(data, incumbent == 0)\n",
    "difference.nonincumbents <- mean(nonincumbents$gunsbanassault_perception - nonincumbents$gunsbanassault_opinion, \n",
    "                              na.rm = TRUE)\n",
    "\n",
    "difference.incumbents\n",
    "difference.nonincumbents\n",
    "\n",
    "#an alternative way to get the same answer\n",
    "library(estimatr)\n",
    "data$difference <- data$gunsbanassault_perception - data$gunsbanassault_opinion\n",
    "difference_in_means(difference ~ incumbent, data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "“Removed 790 rows containing missing values (geom_point).”\n"
     ]
    },
    {
     "data": {
      "image/png": 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cX0vgsvCI9YRFpXSC8Pka29PJ9eHuUw\nvrjrpzfWl77puPLGWkQy+rj4pM/9pl7OL+2Ge4ex9izlTbFBIrknOkW6HToBfW0+YhHpBqMa\nvyb0yhlXG+WELfLxxV1/ODxXH+WNFUVaAYPlSg296CajZ6xWSdLmZQasnaS8KTZIJPdEpUiH\nfbBH9TUfEkXajU31BoVeewOW35I/gShSA1i6surGWkR6BJ97cuhFR2BZ0uKoMZYlrxCeIZHc\nE5UipeAO1dN8SBRpC5ZfDL32d1geJn8CUaRbYOkKqhtrEaktPrfk3G4oliXtl7A3s7ZQeVus\nkEjuiUqRMsrADjXFfEgU6SS2OP409NrHkqG8SP4EokjdYOkHVDfWItJkVGFH6EXnQzWf5Mzv\nOSjHSMqeIZHcE5Ui+T8xdqh6Qqc7y3uk942ytKHk20a5taSqI4qUcoW+dP6tyhtrudgA789k\nzZf99xvlsZJqOrxC9FDeFBskknuiUyT/57WTyz11SHjAevl75k1JFZ47Kl17ao08FQc4vaxb\nLlhvbVWs0D3r1bZTxyLS4SZxWmIXaa/L4y9VzHPDdOlQe2vn9iU/r74pNkgk90SpSJmgD2QV\nIJHcQyKpQCIpQCK5hkRSgUTikEgAiaQCicQhkQASSQUSiUMiASSSCiQSh0QCSCQVSCQOiQSQ\nSCqQSBwSCSCRVCCROCQSQCKpQCJxSCSARFKBROKQSACJpAKJxCGRABJJBRKJQyIBJJIKJBKH\nRAJIJBVIJA6JBJBIKpBIHBIJIJFUIJE4JBJAIqlAInFIJIBEUoFE4pBIAImkAonEIZEAEkkF\nEolDIgEkkgokEodEAkgkFUgkDokEkEgqkEgcEgkgkVQgkTgkEkAiqUAicUgkgERSgUTikEhA\nlkQ68snohZbb2ltFOvjRmCVintyh1yYh/vzB2GUOg6d8Nn2V+qYt7/bwZ5YHHHf9Y6+0e/mI\nkDdPmizeYf/wgHZDxPuKb/zwk+0Oo617d+ouIdpnafW4aWInzIMfv2eZpW/HTv/JYfDnardY\n61AmkdyTbURaVErTtNopwiMWkebozSzrH2TxkN4Cwme2XZipN7NsKr0t/vv5g+WWqt1O7tVb\nPFQRb2zvJNLc+ODScR/z3DcuGM1WTB8Go5Ywj+fuwRgv7cKZoXceSxzJs22W0vR+Ssnv8jLM\n0gEWU1sEY4FpssG3xoXpukEiuSe7iLS/hNGRpJnwkCjSbqPrq9aWZWheqc3GuDWvEbtIBl+f\naJSfUdu0N+C57hUechApLY+xdDw7Jk2FtVkHicPGzqslsebNY6D8uWS016C8GKN9lvrBc32H\nEWepDSv3MmKeDZLB88PgH0l/FhLJPdlFpPHwS/UJpzGiSLgz58JDUjr2tqyN5YEQ4yXHnN5Q\nLqC2aeVxcOEhB5HGwdK83189iA0xDsHyBMw3QmwhGe0aKD+I0T5LV0B+HCPOUizOUkY+yJL2\ntqyv4dXSn4VEck92EWkw/lZXmg+JIvXF8maIbB+oiGXsmqftCz14ByyrndsVwr1XeMhBpGc1\n685dGWIVjF2xzJoYlbG+ItgpCOXGGO2zlAvifRjZLG2CeAxjx9Bjz8NyEenPQiK5J7uINB1+\nqbl+Nh8SRcLX+cTjmGMgN8KIncULnAw9+EtQLqm2aZVg7SThIQeRZuLuOR7zXRDvwTgay+zi\nRV2I7SWj1YByV4z2WaoIuTdGnKWEY5iLQx4YeuxDuCnXS38WEsk92UWk1KrGL/UJ4SFRpCOw\ny/A25cb7fy2G9cnbX9rIkjbl/j1FjfJItU37DM4jnxUecrrYAHtvYXZtYrER45diTIdjzBVs\n6c9h15d0V/Z/YJSTWRdz+yy9a8SCP2LEWeJbCqd6xSXHaf+VIJL8uh2J5J7sIpJ/8+3Bk/vH\nxJMvy1W79TdrWu4e7C26P/12ffcbz8urgi/d8c9KO0Z+HTzBShygumkvB8+gfG3ER5xE2qyf\nrV1htsKcUkzTSphXztbq1wvKmtfDxwXPHEt/Ih1tRH5NKz/XHNw2S0OSNO0as2u0bZYy+idq\nWlXpxwKp+lusmNfkPwqJ5J5sI5Lf/+PXP1uy7QPZrd8cFOPeCfNEbzK2LDvsMHb6vs3HHcph\nSP1s8iHLA84foW54x/Iif2L1mhNiXvPORsvg23am+eWkfrvBcsJqm6VjK36wvHz8uN4yS0eW\nb5a1nNbZ+OJUhyqJ5IFsJJId+maDAvTNBhLJDomkAIlEItkhkRQgkUgkOySSAiQSiWSHRFKA\nRCKR7JBICpBIJJIdEkkBEolEskMiKUAikUh2SCQFSCQSyQ6JpACJRCLZIZEUIJFIJDskkgIk\nEolkh0RSgEQikeyQSAqQSCSSHRJJARKJRLJDIilAIpFIdkgkBUgkEskOiaQAiUQi2SGRFCCR\nSCQ7JJICF1OkjC1rVO/6rEMiuYZEUuFyEWnxtZqW/w310Ugk15BIKlwmIv0Id+R7T3k0Esk1\nJJIKl4lIz8DtJK9VHo1Ecg2JpMJlIhLc3FaLUx6NRHINiaTCZSLSYyBSKeXRLpJI61oYjA7M\n1f9pSSJlgkRS4OKJtCzeEKmf8mgXSaTftgT5ocPKwIRBwf/YGhUi+X/6JXJjpa+wdoQ8tFnS\nawI4sMWxfPKQUzUc65dYs/Ouv/OVnZY8e44l7hm335KPWK8pH/3BcoNjO4c3WW5wnL5wk6Uc\nRqQws2TDetXubb2FWmuH2yvv2yqv+S/uqd0XrwQCg2ZZHnLxZNlUpJ87xGq5ux4Jv6ArHozR\ntCTzztRb7wzGAdK75P9QX9PyvSodbE1tTSs0UnVTRiVoWmx38REnkVYZrS+X8tzOp2k+s0XR\nKr25YCFzl/ugtKZVXsDjvlYxWlwv6cc1u5r7tIS+5s5sm6UwIoWZpUzYPkfa+d6olbJF/f4l\nVTXtiikOo11EkTI6nAwEnlx5+lRUiHS3Y6cfj0DXxhh2N/rj0M/kFcnSh6GfyQhJeX8pozxR\nbVMWQVuXwcJDTiJB869YFrGZIO8SCydIyXxwiOy2+un1jfy4PzRpNxtl3oLPNkt+Z5HCzFJm\nvHyzYWsBY/C58iUuokijJwUCF+7ve2+LHnv0mLpnz56U38JxKnA27DLu+etMpEZaiX2rtkZk\nNNjftDoYJ0NMOhl66VFQLvx/ocuDoFxWbVOqwdp5hYfOy5d+GaehG+YEiIkYseeZ9h7mRhA7\nY5wPMUayG3yCV86OYrbNUpA//pVvWphZysypgPu940kYvJZ8ib9Ohx3kDzWRUtv8Egj80mrK\nb/4RHX4P5gE1a9a8w5OJ2Qn8JWsLIzIaDlYWI9s9D4ReGpvEahmhy12wfEZpU4rgzu1uaewZ\nq9XAjN1ufRibYLkD5nIQ62KchOXVoQcfieVtmG2zFIYws5Q1sDNh4SwNcp7/lyeRxo9g/3Wm\nzYrg/389duzY9/8Ox+nAubDLuOfsv5EaaT7bByIyGva2rIoR96CYk6GXfgVfqX8LXca+rvnU\nNgX39TjhoQvypR/EabgLM7Z5zYXxISz3x4zt2e/F+DEzJfTgzLOfMdtmKcjp8/JNCzNLmTkT\ncL934M99rXyJs/+EH0VJpLPtN/H/7jGX/ZeL88js+R7pOOxwlb1cFpJTE34vozFuz2vE5pKl\nNyYaZdn7s+/gFEj2ziMMA2BT7hAecniPtB/3dXbh7laIt2PcA0co31HM2P32Q4wHSxjxJsng\n+6AxdAOWbbPkd36PFGaWMuPlPRL08NReli9x0d4jrWt3Lvj/a3sETwz/as2dcvFk2VMk/7KS\nwYksJ+9I6olDxglVC55n6K3ub0iRLT4pKViufVBWflt/p9LgmKwcBuNsrYx4Jc3pYsPTxg7V\nhWdj3y/M44uGR2+ymGG8kpv9aefr7W6v3iwbfLY+WpUdLNpnKcxVuzCzlAlPf0bxUlxw8Acc\nXkYvmkjvvqL//6lOg7btGtiHnx26eLJsKpL/yIzhH2ahwaSNN+5pv1CIe8cN+lR69dvv3zV2\n8OcOTR63T3xrvvqmzH7g7tGWBxw/R9pco/B1G4Q8+Lrrhghxa+OKTfcIedk7764T4oFJL89w\n+CDppwmvzBQ/ynmjaVtxlsJ8jhRmlux4+3ukDW+9utSpftFEeuIT45+M1zs9PMa8AO7iybKr\nSPTNBiUuk282ZBn6rp1rSCQVSCQOiQSQSCqQSBwSCSCRVCCROCQSQCKpQCJxSCSARFKBROKQ\nSACJpAKJxCGRABJJBRKJQyIBJJIKJBKHRAJIJBVIJA6JBJBIKpBIHBIJIJFUIJE4JBJAIqlA\nInFIJIBEUoFE4pBIAImkAonEIZEAEkkFEolDIgEkkgokEodEAkgkFUgkDokEkEgqkEgcEgkg\nkVQgkTgkEkAiqUAicUgkgERSgUTikEgAiaQCicQhkQASSQUSiUMiASSSCiQSh0QCSCQVSCQO\niQSQSCqQSJzLVqT93Spf2UZ6x3bPOIqU/s5NJevN8jDapRPp4FNVyt63Xlre361SeessWXb9\n9ZXjcl8p3PW6hk/zVTHvz72zU8WrHt7FY8aEWiXrTDeXftmnabFm88q0dkmxBV40y+Pz+HxF\nV5nl4TeWaviF/CdxFun4S9XLNF3msICNLIn0cd2SN48R79YexSIdvdZoG7QlUuM5igQt3ca4\nH+2SiZRaQ9+yPOsk5RCzJIq03eiAFMO7qxY1fs4CLO4zGrWU5H00njfKw1h8HbqhLGK5uhEf\nZHEiNIHhzZ07GVlsGmvDSaSMO4y1F8iXsJEVkd42nqun8EgUi4R9GGVdhzzjJNJqeK4k982a\nL5lI2KOovqQcYpZEkbBHUQWMM7E/0tuYH4XYFeNWiHFMLGzoF4fxA4i+vZixt2VFjEsgFpK3\nq3ASaTqsfY18CRtZEOlQHngy4dUpikW6E37YYpEaz0mk0biDLXY92iUT6QHYskRJOcQsiSLl\ng3JujLfjz1kDM3agrY5xCpZnY8aoYWyPcZS1zDwbhnm19GdxEqknrr1fvoiVLIi0CJ9LOAOJ\nYpGgD7lWKlLjOYn0Ls7sctejXTKR2sGW5ZeUQ8ySKFIB677eGH/OWpixt2VNjHjI0b7EbBOp\nM8YJ1nICxjcwi+2XrDiJhD1kfYfli1jJgkhf234Qf1SLhJ1ZH4rUeE4ibYOzlBIOTbRsXDKR\nsDPr/ZJyiFkSRbrTegRizd3nYO4L8QWM+5KMWJCd4WKL2bwY8dwthpXxcHczxvUQy8ubhTmJ\nNA/WvkW+hI0siJRaDF4BfjQfimKR0hvqP2wF14f6cDhebDBeTePnyBewc8lEymiub1rJPZJy\niFkSRTpitLeNZ+9q8BBUicXjxuWDGrxxpnFkjvuARTwF2sfyfUZ8hcUVxnuoOL620d09weH0\n2PGqXVd97QLyw5mdrFxsmK13wtRGCo9EsUj+k6MfaD7Q/dv/cDh/jrS4c6PHN3oY7dJd/s6Y\ncH/TfvLWqidH39fMOkuWy9/H7r+iRNMDZn4q3hff1YyprzVvPlxoQLv84UZd1phxXZLPV3Cf\nmUddXbia8Gqz6cr4xFuEtb/q2OjJrfKfJMznSB+2vaP3XqcFrGTp8veGro06W1phRrNI9IGs\nGvSBrAIkkmtIJBVIJA6JBJBIKpBIHBIJIJFUIJE4JBJAIqlAInFIJIBEUoFE4pBIAImkAonE\nIZEAEkkFEolDIgEkkgokEodEAkgkFUgkDokEkEgqkEgcEgkgkVQgkTgkEkAiqUAicUgkgERy\nwdiKBa+ZJj5AInFIJIBECk8H4w+OegmPkEgcEgkgkcKCf+Pq220+RCJxSCSARArLU/iX6EPM\nh0gkDokEkEhh6Y4iDTAfIpE4JBJAIoWF3aZK+Jt7EolDIgEkUnjqGh61EB4hkTgkEkAihSf9\n8XyxBfqIj5BIHBIJIJFUIJE4JBJAIqlAInFIJIBEUoFE4pBIAImkAonEIZEAEkkFEolDIgEk\nkgokEodEApxFWt+73UuyG9UHWfVMu5dTxAeyItKhoe17LRHyl888+uYx5dFmdu08Jk18ICu7\n/ua+7V4QejSkdq5c7Sn3a9tmaWfp3ImNhPKypzsPPpBpJRn2WbLjLFLKgHa95Y2aMpMFkf54\nrGwRgETyT9LbE+RbKiu/rZcLir+YLIi09Qrr13B6Gc1Q9jms4UQrfe3rjwqPZEGkj/T2NnlY\neyT/gWSj2U260yoCtlmCRi0JvPyqHou67VRgn6VMOIq0Um8MFeehlWkWROqq3dSlqwGJtDsZ\nWvucDF3ekmCUKwsPZUGkBvA9HNbU7AuI96kNNgHWflJ4SF2knwsag5U4jrk2DN7G3dr2WcoN\na9+KcU28pZtSOGyzlBknkTIqGSsnOrXGsJIFkYq3dS9QtIs0Eb9ktjJ0Gbt5aZvMh9RFOhwD\ngz2H+XGIcW5f9600h7XLCg+pi8RazM7HjE1iC7tb2z5LGFnbzVcwu+vcYp+lzDiJtBGfa5R0\nCTvqIv2jTSGRGG/jxEuaZA3FsnBupy5SCg7WEzP0Atd8qU4rScFmlkWEh9RFeh837TPM2LEv\nn7u17bOEMRbj85jdHSXss5QZJ5G+w7WHSZewoy7S+aK9SCTGcjwqSN4KfwXl5OPmQ+oiZZSG\n0d7DPAJiFbXR+sDajYWH1EXagLs++8O+KyBXd1yJY58l3JmLYvwIlZecPtuwz1JmnEQ6Bj08\ntQXuttyfpVO7WQnvnyeREGjYPVRWbmGU3xYeycJ7pA+NweqwHSr1OiPPUxvs5zL6yolCl72s\nXGyA08znWZxj9LaMcduO0jZL2EZ6M8aMhmHMsGKbpcw4XmyAV6eWLp/LnyWRWlbQkqvW0CGR\n/KkDysVVHidtI3y0b9m4qpZdICuXvz+pGVeym3nwS3m4ROItX6kOtq11oeQGlrfkWRDpxNAr\n464eab5bm1bY5ys132EFC/ZZuj/oYW7ekNZ/qFfpuBofhFgvNLZZyoTz5e+JVeLKPu/hM4Us\niHQXh0TyDn0gqwB9IEsi2SGRFIhWkS4cWr70oKf3SS6ejETyDomkQPYRadn1+huy61aQSAqQ\nSApEp0ib40oO+eKrYSXjtpFI3iGRFIhOke4q59f/+aXcPSSSd0gkBaJTpOL94d8BJUgk75BI\nCkSpSC+hSMVJJO+QSApEp0jNyv2i//NL+WYkkndIJAWiU6QtcaVem/fVa6XiNpNI3iGRFIhO\nkQLLq+uXv6t9494jEolDInOxVzIAACAASURBVCkQpSIFLhz4+usD9IGsEiSSAtEqkndcPBmJ\n5B0SSYFsIdId9wX/x3Ev0plwnA2cC7uMe/6J5GD/Bv6N4Gjn/ongYOcDZyM42oUIjnUmEMnR\nzp6P5GAR3dX+dbFzhBDppgaBwC0c9yL9Ho5TgbNhl3HPX2ciONjfgb8iONrZ/0VwsH8Cf0Rw\ntPMRHOv3C5Ec7dS/ERzsz4juan+fDrvIqRAiqeLi8Eendt6hUzsFssWpnU6nvfDv6p4kkndI\nJAWiUKQ/f/lFm/eLTsZLeUgk75BICkShSI9oJg1JJO+QSApEoUhL3npL6/6WwXu/kUjeIZEU\niEKRgjTY7l4gEskOiaRAdIoUCGTMHDLgg1QSSQUSSYEoFWm4cRe9xKEkkgIkkgLRKdIMrc7i\nk/5lt2vTSSTvkEgKRKdItaud1v85U93DNxtcPBmJ5B0SSYHsItKF+IHwH4PzkkjeIZEUiEqR\n/sndDf6jx00kkndIJAWiUqRAzwTjjnYrE6dfpiLtnPa++0ZS/rRFM5Z4aEG0cfIMp0Y+66bP\nEjth7u7faZJYHlb3/lVCXNv6tiFieeW7nx4U4ub+T84Uyy/WeVD8wcaUKNjWYVPGXlnqaSGe\nqFeiptC80j+7aeOpQvz5luK1xeaAL5ctJ/Y+2VE2sYJ4v+15T/cVe0ZtuaF4wxNCts3S/gGd\nRoubtm7iR5Z+oTaRVo//+GchHpj1rjhp9lmy4yxSxpJxnx93qNvJgkiTS2n1evWqp5UaGGTB\n5SfSqwmaFtfH7VDr9R5u17sVL6NrcOmk0bLyyQ7Bcn5TnaGxwVx4F4v78+iXQ+/h5bZ6TOAd\nao82C8Zis3m5p97zodwRvqVGp7sneDm/Hn2HZNtiNNnLxffuN40vq7Tj5cp6LMXjC0a5O89G\nk71EHpsa5Yd5rqnH5jwabTY1Pi0wS+/w8jt6P6X8m1i0z5JNpNQHguVC5k31Py2iPxff+e2z\nlAlHkVLq6HP6tXwBO1kQSRNx2SvJxZNdKpE+hw2f4G6kE8YOpd0s7TdhZbixdLysp+wAo5zA\nOmqthe5yFVi5BGzaeIwfQCzEyl2MWIAdNmZDuTYrY2sf1vMMO4mxvnd2oFeKVoBl/H2uw9gR\n4u0Yj2CZNUC6EuLVGLdgme3N2ANtMMbvsGybJdYxeWuskUtIZslvE+kZo5z0A8Zt+YzcVTJL\nmXEUqZmxdmmnI5qVLIh0TsTlH5y7eLJLJRL2fHTZkvRL3AdWuFv8Wli6o6RcCsrdMLbEwfGQ\ndBIjOw5chRlPmVLjrbtnLYg+jGtx6Rsw+2x7rw1buTvGazFDW1feNQ8nTbsFs2ZduyzGmpjR\n6ZIYr8YyO5PEWeqA8REss/Mz2yz5bSLlh3JfjC9DTDgRepYy4yTSTtyUSdIl7GTpmw2nvvkk\n7X8X3CmU7US6GaaqrHwJkUk4s5+4W7wALN1YUsaWkKx/8i04OPYK246RdYwsghmPMXswsv7J\nFTHjydt4jKWxbNvX7djKbFNY21c4SHBLr3UeHMXhTfbw50zGWBDLt1lzI4xNsPx+6FnyW0U6\nhkuzF6tumPeFnqXMOIm0AtceIl3CTlZEmhSct+9mlpl9eYrUGqaqnruRFuPMrgu/qE51WLqr\npIxnRL0xdsDB92PGeCXGqpiPQkzLC/ENLNeDyA4aTEO2t8Y4ixRrLePruv2YkgsjnulpzTDj\n8Yx5VgnLd2DGg0Z566xor2O+HuJjGHtimbXos82S33ZEKgblARhfh5j/ZOhZyoyTSCk4Le7b\nmmVBpAVag1nad7uv9C25LEVaAcf+z92NlH67sfTdLp94qrF0kqzn41ijXGAbxl3G5QHzLLMK\n/BZZM8sVVq/8/Y1Ymmm3ElThL9zFYd9m10XwZC2/ZFMetQ2OarALcy9B7Ggrs2sTt0FsiPGA\nTVrYUn6I2WfVzj8NZul7tjb8RngzXNss+W0igTlF2TWYn0pavLLPUmYc3yM9Yqxd1X2D6yyI\nVLfGuYD2XeCva+pdliL5ZwTf0xcc63ao3fqJx33yX4uN14MviGXkl4wG5tG0imZLyA/1F/5q\n/LrbSf3dgc+8oDhQV6UE/6We7BkUr/p3vDwqLliuyy/N7y8UjDEjeNk4TMRJN6WasbfyOM9Q\nxbyifbceb+Fxul72mbNm7L2leYSLeubVynbBxWPNQ4pxvPMt4nm4dZbm6keRa8yr57ZZsomU\n8VxQvErm9Zxvgz9J3NN8GuyzlAlHkY52Cs55nc3yBexkQaS8QwK6SIH+BS5Pkfyp3y330CTU\nv2/NTx6WPvLN6hMO5UOrf0gTYtqXIzeJ5bVPvXNUiKnjn7J8QvLz4h/Ej7RSF7y/Syyv6DlZ\n7EG8+75bv3TYlN0dm1l2t7GNXhbj/sH9dor5zXri50b+jfffv0XM3a961rL2h58eFvOAepbL\npLZZSp8/wnIQP7R0nThL9s+RDiz5Xvw5039YLH6sZJ8lO2E+kE1ZuMWpbCcLIpXtDyI9U+Yy\nFckj9M0GFeibDRyZSG1L/6aLdKB4KxLJOySSAtEp0qF85V/TBg4qkXc/ieQdEkmB6BQpsMP4\nVLyJl784d/FkJJJ3SCQFso9IgcBv32/9w4NGJJIJiaRAlIr06+jvAoGJI38nkRQgkRSITpF+\nKa+NDwSe0codJZG8QyIpEJ0iPZr/g3+D/6wt2JFE8g6JpEB0ilTxOfi3X2kSyTskkgLRKVKh\nwfDvqwVJJO+QSApEp0hNqv2l/3P6+sYkkndIJAWiU6T1ua97//tNH9WM+ZZE8g6JpEB0ihRY\neI3x1d9Z7j0ikTgkkgJRKlLg3x8+nr72tAePSCQOiaRAVIr0V4UpXhQikayQSApEpUiBGx4h\nkdQhkRSITpF2lnnvHImkComkQHSK1LqRllT5Jh0SyTskkgLRKVIDDonkHRJJgegUSQUXT0Yi\neYdEUiAbiXRZ3yDSMySSCiQSJ0pvEOkZEkkFEokTpTeI9AyJpAKJxInWG0R6hURSgUTiRO0N\nIj1CIqlAInHoBpEAiaQCicShG0QCF1WkY9utd9fdYbnRr52MH49Y8i/HHUU6sMup6t+8xhLT\nDlpvHb9pvePaKZbmlP4T2yw3GfafdG7Ntttyk2H/8W3WaVixwxLtInmbJRvZRiS6QWRWsIj0\n490xWv5B5i43qrDmayBrZeH3v1ZQi7nT7MK5/nZNKypts+lfVUvTrpB3zBqXR9NyPcVj6tMJ\nWq4OZrOAEQmalrufdO05V2taJfPO4gcfzq3FP2netvzj8pp23eJQKxpML61pNZfzuKdlrJb0\nonk774djNC2f2FnFKtLbwVmq73qWMpFtRKIbRGYFUaTU64wmDkNZnmDEcgdCrRdkhFGuxHbX\nn8sY+T3J0nuhj5CsQ9pSaNTyGsuPG/EOJvUcKI+TrL0Kesjy7pTQ0a8Ti0uMRi15N0nW/sJY\nuhA76qTVNvLzrNzbiDGCKhaRJnqapcxkH5HoBpFZQBQJ2wEms1Oq0pAl7eLSC0H5bcyDIJaT\nPFFfKFeVlKtBOS/G3diXbAFmbAdYRLJ2Cyi3xPgtRN4qDBvUdpasjU0TWWvnjyHGsb7R2Lyy\njrmCRaQynmYpM9lIpIyZQwZ8kEoiqSCK1Ne6/7Gmjp1Cr7lXs+5/rN+fpCnWvbh7SrajMJRZ\n86/5mnX/S4aYS7I2tKjmvcEm49qzMOO+XluyNu7rrEHoYFx7JWaMZkt1i0jHvc1SZrKPSMON\nvoiJQ0kkBUSRXoPfeQy+8c5IhPx06DWPQX8/3puuF8Rkybv6R6BcInSV7evMs9W4/03HXBRi\nHsnadaDMmp5jg3WNdf/CXpeyPofY27ItxjG4NmtEHmO11G8VKSOPp1nKTLYRaYZWZ/FJ/7Lb\ntekkkndEkbYlW/e3h40YL+s218ooJ27E+C2cAj0mWXoh7FDPSMrYnZI1r8yAvq4lDmLGxpn3\nStYeDWX2FuoYaFmJXS8YBuUZkrX7QflzjHsLWqz03wjlUeYKllO7RzzNUmayjUi1qxm3azhT\n/RYSyTuWq3bTdJOqsb6t/sN6b/GEUSHWMth/g36MmMjzm7pJt0nfVQ/WO2M2lnZDNQ4qV/Dy\nhvLBWMTsN1lDL1eQdr4znO/C41K9gW0Zfu0hvY3DMcPvT7tHPxaalwRn6c3gr2UHJP8B49Sv\nmbCCRaTDt+oeuZ6lTGQXkS7ED4T/GJyXRPKO9XOkXe+89JHQxTFj9oC3HC7cpn88YNSPQt48\n7vU5Dh/XbHhzoFPryw9b3DFCiMenDB4nfrgz9Z4m8kvrfv+yoa+uEOKh8f0mi0ovefPtVfZV\nBBa8MlzsE79vTP/pYivMwY1azhEXt17+9jhLdrKLSP/k7gb/0YP+QlYB+maDAtH5zYaeCSv0\nf1YmTieRvEMiKRCdIk0updXr1aueVmpgkAUkkjdIJAWiUyRNpBeJ5A0SSYHoFOmcwAvnSSRv\nkEgKRKdIIiXceUQicbKxSJH8DZBIJiQSkDNEOjm8jFa877FIDUcimZBIQM4QCb5t0CZSw5FI\nJiQSkCNESsGvqH0TofFIJBMSCcgRIi3Aq7DvRGg8EsmERAJyhEjsL4rej9B4JJIJiQTkCJFO\nwl/yFUgJv6g7SCQOiQTkCJH8y/SvXCd+EH5Bl5BIHBIJuIgiHX66bMKNM12v+9lNiWW6H+Qx\n5dFSyXXmOyzviZ9efXKAw3eqvWIRKXVghYQq7zrfV8gJEolEsiOKlNHYOJ+a4nLVmcbSt7G/\nEUqFv8WLmEkX8ZsN8Ffxw5QHi06ROu2Ff1f3DAQ+IJE8IooEZmhFT8oXF8jAvw5ntw0aCbFq\nxDbtoom0ArY0Xnbjn7BEoUh//vKLNu8XnYyX8ri0iEQSEEV6Hi+VuTujSsGle2LuBNEn/RtY\nr1w0kd7GLZff6C4MUSjSI8I3vxuSSN4RRXoFJ3KffHGBw3CrOe05zHAnOi1O+ufgXrloIk3A\nn3OlfHFnolCkJW+9pXV/y+C930gk74gi4a17bna5an1YfBnGuRBl9yfxzkUTaZdx2ymtnLtT\n2BBEoUhBGni5xSqJZMNy1W6wvn8Vkd/wxspW/Q4jWn+ejTv9lNsbsU27eBcbJuj3Ycm7RHmw\n6BRJBRdP5iTSnLpFqw708F7gchHJ/3XP1oN+li2aiYND2nYX3mcceqBgnkqLIrZlF/PvkdY9\n07rfbvXBok+kWyxcKpFmeD2HuWxEygppxp1/47+O1Hj0h30qKIpU18IlEukk3A6e31AwPDlC\nJLxJY41IjUciqXA5ndptwYs+/aVL2MkRInWGWYk5EX5Rd5BIClxOIu1AkQa5/ulyhEhdL5vL\n31kmOkWqxglhzNwWQVoGAhdmPvbo1HOREclfFXaZ1fIlbOQIkT6FWbkrUuORSCpkQaTmOs2q\naEnPhBBpwqAtW7ZsDQQ+7bD+h4emRkik7/Lqe4y8v0AmcoRIcG5XYkf4BV1CIimQ9VO7lUmd\nQjw6aJbxz7mHlgYCq9qdjoxI/t19mj08z8NP50mkj+qXrzfNjHu6VK7SVfyugaNIGe/WKd9o\njrScWjPWF9fNzHPKxeWpY/7Nz6Fqsb7458zy8ERfTMU90tH0/l3x5m2t18Vpmq+jWe4d74ut\nfohHo7PdTWb5tSK587U3G70eeKr6tR22mWW910oB8yOGUfr3KITb4JcMxqJmXFM5PqGq0GS2\nW/5cBYUfRP/gKNH8jZ28LdaXW2hotLBCXOJN5itA+qhbKjRZ4JeRNrzWVc2Ei5O9YzWtkLnl\nqYNrVmwh600RguwmUmCA5s/84JMrT58K/nO4RbD2Z4vdERLJK15EgiZFA1lM0fcYrYzZTNVZ\nJGhSNF5WLmCUed8W6E2XzO/VA61+uAtwA5Lcsg/MoFGmxuIRiPx+Je1gcBZXQfk6lnsYkTcd\nOm70CivA98d8RjmWxY9s13cSYNNY3BhrLM069PnrGeX7WHwf1ua30Tc+SdbqsrjQ+LJTAv8O\n6yNGWdYEBhu1fM5iFyP62CRm3GW8U3T/Pb5sJ9J031+ZHrtwf997W/TYE9h6r37nyNZrs79I\nKXGwi7AXenwL/4S5hJNIa2HpvJLeKs/hZRK2y0AjIO0BjA9hmX11Bjts1ZM8GS7NOtkV1yxi\npWJk/ZJ81jL7pt4EzAMgtsCI3ZR48y/b2qwX2AuYq0CshnEJltl3NHLhtGB8E8vbMZeAeAfG\nbyAWllx+xK9ClWF/zoSDVcL4gTWGJ7uJdK5F6cwP/tJqym/+ER1+X9VGT50XB/9vWMOGDe+/\nEJaghP8Ji/H38jnmGyDWFBZx2DJ86dXWhy7jMUQbgxljeYwVMH8F8ReMBUMPhq1WtVjMqJ2W\nCnEOxiutz6VdsJYfwAztk7UrMNbCcr7Qa2OPPa0EZuwtmAdjHyy/Zl3bhxH7+2n9rVteHCP7\ncvjO0D/3YCwfhpiBMR7L7MXq19Brh+BS72rmNbcQFxua31NR6xPyQBUInGmzYvO9F/Qj0qrg\n/43v1KlT93/DcS5wPuwy7jnnfrCl+HuYi7kmxFrmEucD56RrT8W1N4Qu18DyJMz4Ol8RI3Y8\n1pZC/A1j4dCDfcFEwhyL+ReI8zBejWWmAsYvMbbFjC1my2Csi+WCodeuhLEUZmw/mYSR/T3I\nCOvaPoz1MA+ybvkVGNnhbnfon/tVLB+ByI5ICVh+AZ/r19BrZyayu9r58IP9IxGpBnDrwDMS\nkQI95h5oETye/d1iB3vExeHvPzq1OwhvDvKwKwDQm14T3jg7ndpthfaTxSRva/Cchv/JEJ7T\ndMWIzZhZQ2Q/3lvufsmT4R7E3uYwDVkZLWWN8GKt5VQ83frMumns/dn3uPTT1rXZps3C8hjM\neAC7BSOe4frY1+ngHRW/OMFebtgbTzwSt7KuXVbygdjXUK5s+zlvxYivL26/Qp/9Tu1CsrbH\nH4HAX603neu0IhBY3zZSV+284uViA5ydsW6o/qPGm/DrjpsLOF5sMLqlxn0mK5czBueX7ZYb\nJzUl+B4D3316iUXjOpuWJBvsHqt2uEfxDpJwjsObL+O1iNaWLeU9Y/0nb9djmZ9YLmuUE1hE\nsT5iGZqg52MxxXgBSeCXZNob5R4swmHexy9PQhP0dixuMDQtyK8gGhdZ4qWX7Xrq5cTlLA41\nBjP7rRtdOPOuC7lqKLKdSMubZn7sVKdB23YN7HM+8Mmj+356fAp/3MWT/Wd/RvFtp9s6CBdX\njw1q0mSI4FGYz5Hmtav7iMMv8cGkXIWEa3qbahcq2cG8BO1vmSdXYeHOPfOK505sKP+rnX5B\nD4ub8cQVPi1uspmHxvtibzLvMLJXF+15szyncoFyr5jxYNPC+W7aZOYWPuESX9Ck4OExVvjI\noaFP891qxv13Fi3aVPjT8SfyxCYLz7WuYEzMFcKtvbom5yog9NncXrdQiVbCfcZnt7n9sR8y\n/7yMma0aPSFcqJ+Z5IutLEzitJb1euyUr20n+4j02eOddK4sFsKujNc7PTzmVPDt3IePPTrF\n7Pni4sly4t8jZRXL7bi+Mq4/PuJy1VTjqkrRXcJDWfgIFd7HjBUeoQ9kOdKOfVq+PFq50r4S\nH4U8UIXExZORSN4RRcqA00jN5R8oDbG+T9FR3/V3wGcIeYQ/rSKRODKRrq91Ni1he2BNkWMk\nkncumkjb8B39Sw7LCzTVrG+p/FkRaRo+9+fmQyQSRyZS8uuBQM2pgcATHUgk71w0kbbjzuzy\nK4ko0hXCQ+q7/nR8buG7UiQSRyZS0eGBQOvnA4GpZUkk71y8Uzv80NTlnRHw05m2wkPqu/4u\n+BQg2bwLLIlkIhOpXu1fAwNvCgReKEAieefiXWxYaLxR6Spf2sKJm/Sli4vfkM3Crj/cEEn8\nyiGJxJGJtEjL/78ffN1eLtCMRPKOF5EyJja/tet2hwWsN9Ff9+CNTSe7vsH28Vfq1+ppaT6R\nlV1/bosaLS3fGyWRONLL3zOa/BkYmlursJdE8o4XkToan886/D0jdTVXIPuIZHBq1z8hHiWR\nwuFBJPyeaU35EiSSAtlLpH++Wvg/EkkBDyI9jdfCDkqXIJEUyDYi/a9LtcCFRppW6QSJ5B0P\nIvVCkeR3kCSRFMg2IvXVmgW+0fp8kb8HieQdDyJh15cq8iVIJAWyjUjlmwcCTxU6E+h8FYnk\nHS8XG4w/votfKl+ARFIg24iU8GogUKNVIDAygUTyjheRTrx26zWt1jgsEEmRNjze7KHI3f6Y\nRDKRiVSxTeCob0Ig8Dh9s0GB7NqMebbxce6oSA1HIpnIRHoxd+/r4lJPjYvrTCJ5J5uKlAp/\nY5jwY/hF3UEicWQinbrXFzsmsFm75hCJ5J1sKhLeyYffZCjLkEgc+edIv/8vEPhl5d/uPSKR\nONlUpEUo0pjwi7qDROLQB7JAjhDpEN4XyP2tD8JAInHoA1kgR4jkf8t6+5IsQyJx6ANZIGeI\n5J95W8maoyPWIoZEMqEPZIEcIhJ9IKsEfSDrGhJJBRKJQx/IAiSSCiQShz6QBUgkFUgkDn0g\nC5BIKpBIHPpAFiCRVCCROCr3/r4cRdo5oEN/4Q4jGdO6Pj5DvIWIVaT0yY89+bF8sLR3H+k5\nW14+3K5yzWEets3KkeEP9V4u5IV9u70ta++XmU1Nrrp1lpA/7fHoBMt9xh13/RCzNF2Ypa39\nOgwQb3/sLFLau4/2cJilTFhFOj7y4afdN+jLRPYRyene35efSF8m6zfb5f0k0hrpH0w2EfYw\ni0ipt+rllrJ79RwxOiJ1klSxC0x19xtnYXtpfe1BPBsdaK5KcVhDZIbRvKIzz0YDiZrCnewd\nRQo5S3fyWfpE7zyWd76wgpNIR437jneUL2DHItI+4wZ+fd2vbSPbiBRd9/4+Dj2LCrMmxoPg\nqzKvmktYRMKWRu9IRnsCylMkZWxp1E9SDkMjWPtbjF9BfMBxHU463MNRY38mOEnL9FUGh11f\nMktDMR4oZMSSwuHRSaRusPb77rbcbxPpPlhb3rw5DNlGpOi69zdrdMdOem6GWNtcwiISdPrR\nGktGKw3llpIy9si6yvXWiRzBjpGsewpKG+/u2wjYiZXfWrUFxLLCIg67vmSWamFkXTmFndtJ\npDKw9H3yJWyIIqXDDfu1J12vbSPbiBRd9/5mvejYQQTbDAudgiwiQT8u7VZ/aOCVWWsiKeNz\nlXG9dSL7cO2emDtB9Ll7l8S65rEO640hFhEWcdj1JbPEmjGzVrqfmms4iYSzdKerDdcRRWJN\npx9yvbaNbCNSdN37+0ds8sgacreD2MFcwiISdM0Tm55bwG6pshP4JK97kEhGKVh7EuY3IFZ2\nXImTgvvfa5ixxWcjYRGHXV8ySw9iXA8xVmj35SRSfVj8WXdb7red2l0La490vbaNbCNSlN37\n+xnj1/I4i1vz67Gg8JeiFpG+N/7coNheyWDfGt1Ty8huoDXSeK442dphgJ4PtVmvuuNwWPjC\n5dpwLse7T+w3tEwQb+PqdLEh9Czxy3iPGeU+wgpOIq10nqXMWET63Hiu69xfrrSRbUSKsnt/\np71WPqbsoBM8r26clHznWmEB6+XvFfXz5L1H3qZxcZ2E/PdvlZaHJWu+8ivcb5yVD6/LXbQr\n79vq39OxcFzNz92unN4pToutZV7j23Jv/oS6lrudOF6wdp6l1JfLxlQYLl5Md7z8vSQ4Sy3l\ns5QJ6+Xv2TfGFeqs+GLkz0YiRd+9v21v1zOsF7ftH8iGeXMfpvxnlj6QtQ1+9rynD2TTbNk2\nWpiPUJ1nyV4O84Gst7/XsH8gm6W/9sg+IhnQvb/VoG82KBDd32zwgosnI5G8QyIpkG1E+uOx\nskUAEsk7JJIC0SlSV+2mLl0NSCTvkEgKRKdIxdu6F4hEskMiKRCVIv2jTSGR1CGRFIhKkc4X\n7UUiqUMiKRCVIgVmJbx/nkRShURSIDpFallBS65aQ4dE8g6JpEB0inQXh0TyDomkQHSKpIKL\nJyORvEMiKZDtRIqWezaEg0RSgUTi5JB7NoSFRFKBROLkjHs2hIdEUoFE4uSMezaEh0RSgUTi\n5Ix7NoSHRFKBROLkjHs2hIdEUoFE4uSQezaEhURSgUTi5JB7NoSFRFKBROLknHs2OEMiqUAi\nceieDQCJpAKJxJGLdGT6gKGzfg14wMWTkUjeIZEUyD4i9Tfuvpx/LImkAImkQHSKNFG7dfFJ\n/ze3aXNIJO+QSApEp0g3VTV69Z2udjuJ5B0SSYHoFCnvQPh3UD4SyTskkgLRKVLt7vBvz+sv\nnUgrJ8095lS34UmktFGPjhDvyL6i11MrhXjy65nLxbvzbpv+0R4hHhn26DjxDrrzuj+/QYiH\nhjw6SYj+OT0HbBbi7MLxNcTyiEYPrhfX/nzyGrH8dJVGq4T488JZG8Vyq1I114k/SNs7xovl\negUric+9/rnuC4WY1rFqC7H73wuF8ncX4pGGJeuJd723z9KCiYvFWXr5qkpjhXjiq4nfiOX5\n1llK/WKi4w3RsyTSgdnvfS/mbCPSx0mr9H/W5Bl0qUQ6dKfevGCR+5/Oi0iL9P4SiXN5htaX\nPG6oGow1ze6pz8ZpWp43eZymX3jJx/f29OrB6DNbX47LpTdt4Ltv2jV6uRsvX2E0VuAtaQ8Y\nbV/MLmWzi+uRS77N6K1i9jj7sHAwtuc39F5ktDGrz8sNjYYRfO1xxnPV4+X2+uI38vi+sXZv\nnnPrMYbHAcbaT1tnyWxPY58l43JUAR5XXR2Mt/LXn/TrrbP0TflgbmB2B8hEVkSyzVI2EWmw\nTlWtUe/ejXzJUy+VSEa7U624226pnkRKSzYGT2QHPOwbxNrinagKvVTYy+kEKH+Fcb+xv2mF\n2WgtoTwO4w5oK1SKlbG714cYn4eosXJJiJMx/ljAiNy7BGv5B+i29BwrY0O/6RiHQbyGlfG5\n5mB8B2IbVsZmgtswYuvBZIxHcO191lliz22fJXiB4G0Pj0HLT/4ScL91lg7Ckzk08MuCSDhL\nQseqbCGSZuESiXQAIHdWuwAAIABJREFUu1y97fqn8yASmqENx4zd5Jga2KiVN27Fno/sl94H\ny19ixkatrLflo1hmRyz8QapbI9v3T2IsjeVXICZiM5U9WC5qfe5CGFl3SrblhTFbB+OLV4CY\nYCuzVoSadW1slKnVcTdLGH0YP8K8yTpLFTFOxKXFM2YrWRDpWRi8oPlIthDpnIVLJNJG/D08\nL13CjgeRcKJ5D6146w6GPYu1TzBj+1PWPPUBLL+B2Wfdwe7EMms7jLGUNWr3QNyOMR+WsWcx\nOwx8gDERyx0w48nb0xjjsZxoVaGBrVzIuq9jJ0KtnG3TMGKXPO54vHUw+yzZ1h6JkbWYtc0S\ndnbWxPdcVrIgUkcc/Dh/JFuIxPnnq4X/c+9R1kQ6gu13x0mXsONBpBk40aMxF4VYHONiLLOe\nWnUgsjOi/lhmvcJx72XtKLtjeRNmOBHUamLMheV5mDFWwIgnZ/mwf9d+LLOmey9CLIFxOZaL\nYS5mNWWMZv3BroGYB+NbWGatMG0qMGnZe8ei1ueyz5Jmfe7PMLP3UDhLlTBie9vYn/wysiBS\nP+uP7c9GIv2vS7XAheCbzUonLpFI/idh/zrs+qfzcrEBToHys3ejuPeOwJh+q2UH8n9ixHh2\njekI7BO8u3JXWJtdPtgPLwH8fUpb2L/YxbLx1r2Vve6ztzEpJYzYj5XzQZm9P9sBBxXWFJZp\nya7JTIbI27PjYYCdZX4IsQcr42kme8df3bb/4ZYesc4SOxDbZwl7NbMT4BPXG7EVKz9unaVj\n8HM/7JeSBZF2wiwNMx/JNiL11ZoFvtH6fJG/x6USKbVzcCquXyNfwI4XkdbrL92FzdOKTsE9\nzvcIjzv1i193m9c5RgR352LTeJyv792ld/DcRH9pfZHHz/S3uhXMtesGY64hPNYwfsm8j2uq\nbo6vJy9/U0nTcj/JG0ruN642mJu24Mqg0n34VeUtxtWGjrxsnNRU4HGh8VzmpbI+QXV8d/O4\nSDfJ9xbPeY0XDB4nGx6aZWOWzF3fPkvGZZLyPG7RD+T3H+S5qT5L5pn69zcFc/ujfilZuWq3\nMDhLcb2Fa+/ZRqTyzQOBpwqdCXS+6lKJFHyjPW+9l3aH3j6QXTRsvhhTxo61XB/ctdLyLvjw\nkmXHxTx32HIx7hg1STxyps8eZjn13zp2+hEh7r+1hKW394puww4J8eSa+ZZNmd2it1hO27z6\ngFgee0tXcfADA3uKvXD9Ayp3Ej8vOzRp1C6x/O59Q8W4pEblWZa1a78gRvssbflqmxiXNmtp\n+Yjrh692iNE2SxkbvrJsip0sfY6UtmqB5cp6thEp4dVAoEarQGBkwqUTySP0zQYV6JsNCmRB\npIptAkd9EwKBx+meDQqQSApEp0gv5u59XVzqqXFxnUkk75BICkSnSKfu9cWOCWzWrjlEInmH\nRFIgOkUKBH7/XyDwy8q/3XtEInFIJAWiVSTvuHiyKBHp4OJvU53qJJIC0SnSH4+VLQKQSJkY\nkkfTSs1yWIBEUiA6Reqq3dSlqwGJZOc941PPPOvkS5BICkSnSMXbuhcop4l0HXz5pYt8CRJJ\ngagU6R9tCokkA/6CSPjju0yQSApEpUjni/YikWRU0mzfaMsEiaRAVIoUmJXw/nkSKTRvGh7F\nL5MvQSIpEJ0itaygJVetoeNepD/D8Vfgn7DLuOd0JAc7EzjtetlTvYIe5ZvksMQ/f2d9izj/\nBv4XwdHOR3CsPy9EcrS/zkVysIjuamfOhl3E/MM9q0h3cdyL9Hc4TgfOhV3GPWf/jeBg/wTO\nelh678wvjjvV//UyWDjOBU5HcLQLERzr70AkRzt9PoKDnQlEdO/4J/wyEpFUcHH4i4pTu/DQ\nqZ0C0XlqRyJlBRJJgegUqRqHRPIOiaRAdIrUXKdZFS3pGRLJOySSAtEpErIyqROJ5B0SSYGo\nFikwQPOTSJ4hkRSIbpGm+/4ikTxDIikQ1SKda1HatUckEodEUiA6RTIuNjS/p6LWh0TyDomk\nQHSKVAO4deAZEsk7JJIC0SmSCi6ejETyDomkAInkHhJJBRJJgayf2tW4uXGfI9lFpF0nLNGb\nSOm7TjqV7SLtP2SJabsyLDnliCUesTUr2W5tBbD/S2t5z3G/B/5It4q00vrcKRss0f++tVXb\n7k2WmL7FS3dR/4EDjuWte70MFoboFKlrCS1/jRsLaldWT4pflh1EOjkgnxbXXtxJvIh0rFei\nltDtiHwBq0izr9G0ml/zuL9znJb3eVPjD8trvlu+43F9OU3zNTJvK/RELk0rwFtd+mfrzSyq\nmBqPLaHF3rHJ7Zb/0DBWK2l2iU2/y6dppc0eszPza1ousw3soYLB58o9m+fJycHI2/35D98S\nXPsas3llGOZV0bTrFkjLDwYHi+krLXslOkWanWvyP4HAv1ML/3CqfekL2UAk6CB5u3CXfS8i\ndTbWbi1fwCLSMqPFVv6tGDOgldhTrAxt84qwO8KnQicW3rgVtjR2E8b90K2yKivDrVMqWI94\nUg6WMxbnnTHuMmISe0nYAI1a+rMybIqPHXWWQ5sX1r7GD51XirlsVbAm0fEmL9i6aaq7wcIT\nnSLVxrsHdWsSOKgd+O9FOoh9yD4zH/Ig0iZY2eytkgmLSNgF9iGM8yHGst6qtSD3xMiaxDKx\nsAtsXYwNscyaJWA7wFfdbfkQWJo1TzmEDZBYy1lsicZaDy7D52JSYwMk1h1wDZZHunvu+2Dp\n+yVlbKiW391g4YlOkfIPhX9fLxD4Q/v2vxfpW9wHhKYkHkT6GNd+X7qERSTc11n7LtbojrUO\nKwjxDoxNNOtLM0bW+rK09bmPYXS444MIa+qIJ45fYmRtXkthxogt0HiTPWwxy/qWD8dyW3fP\nXRmWriIp42Cx7gYLT3SK1LCG8Sd/p2vWCXyTHY5IW/HXJnTG9CDSIlz7c+kSFpHwflt3YZyC\na7M+ROUhss6Y7bHMOmNi43HW8xF3R9bDOB1bQvITRWd6wNJJeK2DddptjuVrrKa8iWXWJxpf\nEeIwzsByT3fPDR36tNskZfw54yVlz0SnSKvjqoxesnhMtVyrVuar686ji/seCc6nCgqXiTyI\ndOJKY+0y8itWFpHwfIodYvYXMWJ1duHuOSizs8xVcLrFzp/Y+RR7YzLVujPjMSae9QYPA56s\n8bZ5cIzxLcH4GpRvYGU885uJEc86b8eYDmedMS6vNoyCtUdLytjDs4mk7JnoFCmwoqY+S5WX\nByY3OJ4dRNqit7rP94nwiJeLDSv0fpNFl8gXsIiUbrw7eJLnz/U72ZX5nsUTd+hl81pYH333\nzc3auvr359fLd/Cy8SbJx3ox+w/qLSDj3vC75HX9zWEtfjl9pfFesRsvNzBeXvhF6uG2Y8jN\neizGXz8+1lvQ+syunM5kPKivLT0HTTWOrUVcDhaeKBUpEDjw9YK95wIBl5fsLrZI/tTJfd+y\ntKf09DnSoXF9xzh9JmL7HGn+gEErhJjydt8J4tFszktDxOsWq1rd8rjwyVF6vwbNPxbKH9Uo\n1VS4SJc+84XXf3C/5RveHvKJ8CHWke63PCC24ZzZrN4AIe6skrfMB0Ke2qS+6E3Kw7e3tXSr\ndGbxyy8vdSg/cXWll9wPFo6oFckzLp6MvtngHfpmgwIkkntIJBVIJAVIJNeQSCqQSBwSCSCR\nVCCROCQSQCKpQCJxSCSARFKBROKQSACJpAKJxCGRABJJBRKJQyIBJJIKJBKHRAJIJBVIJA6J\nBJBIKpBIHBIJIJFUIJE4JBJAIqlAInFIJCBaRJp2Q96rB6Y6LEAiKUAiuSZKRBpt/D1SG4cl\nSCQFSCTXRIdIx/PCX60uki9CIilAIrkmOkT6Dm/KMEy+CImkAInkmugQaQOK9JZ8ERJJARLJ\nNdEhUsZVhkcJW+SLkEgKkEiuiQ6R/MuMN0kjHZYgkRQgkVwTJSL5dz/fsrvjnb5IJAVIJNdE\ni0hhIZEUIJFcQyKpQCJxSCSARFKBROKQSACJpAKJxCGRABJJBRKJQyIBJJIKJBIn+4p0rN9N\nlTtsNfOiZlfXe1fs5GoV6YsmVzeYIh/t08ZXN/zIjClPVL+++09mntG4UhOzYaR/d5dqNZ4x\nbxWe3rVgXNHXzPLSqxKSbpW3T30tt+YruJnH1Pvzx5WcbJbb6jfRN8u782qar7NZ7uDTtHz7\neDzUOG98uTlmuUWwXNjs4WmfpZHF4wp0NjvyHe5zY9WHd5jloUXjCpp34M9Ev8JxhfqYcWnh\nmJgiwj3Q787ti3tQXN4iUsbk+lc3ned3y+b2lW9+ybyh+skRda+9d4XD8t4gkRhpRh+XvPxu\n8zM0axsGm0jvGmVpQ9M3jPJgFvcbjYPKcVUGWr9Ys6eYHq89yrLR00HrwuISo3lKorXhsskA\n6LzCb5tf3si8Qxq2A+R/6uCzNkeBBn8+Pg3Q1WwGyzdAYxZets3SU0b5OhZTq+mx0I8sP2yU\nb5FsOLbo45sCzd18vGFtRSPfIKxgEam3UZ4kG9zGhiRjU3hr3XbG2l+4XDssJBJjBOxvjTCe\nwOZzwoeNokhHkqFs6/DNSDGawmpx7LX5cViaNW7ZDl0cE1h3ygehzBq3zILoY+UrIDeVbDn2\nKCqHcSjEXOwwgV+HK4Txasx+a5m1yXsEYjKbBiyzjn22WTqCzb/Y8e9liPdh3IubJhx7RVgX\nM9bsAqecNW75SMv0KxBFWg/VfC67pmNH0FEYsRVh2QzHldxDIjFawczmwbgaf4uvm0uIIrGW\nfGNDD/YZlqdjxpZ8NTBO06w7WAWIrAsseqW9gxn31uKSLcelc2G8HTP2R9mMkR1zclufeybG\n3FjGlnwa7p4DMCaGnqUZWGYN/ZpYtxQ7h2kdQm94fyz3tP6c7PDXFMvCyZ0o0hgsOzShEsFO\nu+xPp/rh2tvcrR0WEonRBiY2L8a1ONFCgy5RpCVYfjf0YJ9jmXUOgu7eWk2M07E8FzN89VOr\nj7ETllnbTdzBSki23CZSfcx4/v+jRCT8E6K5GFmDv0qY8UxwmE0k2ywxDdkhCHqgayUxjsay\n8I5MBI9f2tPWn5OJ1AzLD5lriCKNw/I3kmmxkQRLt8f4Eq69w3El95BIDPy9sNfWk9h2WOhV\nL4p0vBDsflv9ITkAf/CWyN7DPw2DsffVe+DlMR97W9MFyi9jxK7mMexNUTnIsm7fuP9di/Ed\niLzVqmbduW/AbCvXwtgLYiFbuVnoWUqNhczanA237q2sJ7rk7/62Y3k95hLWLZ2Hzy00KhNF\n2gJ954s4/Z27wN0w2ASMS6yTlmVIJEaG0V+yCH+Fmmv8nvoJS1guNnxo/B6kf9A20SjzbqhH\njP6nVfjpPPQt5z3PfzZUqcl3CThDep7FtcbuWkC2x8Drfkway3AeybtId7KKg951ZBHedPOr\nCf6SevR9yaIxK/zEL9MsDTbKrGesP83op1wqheU+RvluyYb7H7Vo599qiOXjHWfB+cbCCpaL\nDcZzx4nNSZ3YbrwDa8rfE3XTY8LXLtcOC4nEOTnyrrpPpZh5XefaLT8VF7Be/v7uwdoPfOmX\n8k272m0Wm/HogIYNXxbeFi9sV7eD0FDy0Av1Gw8VRBlcJm/FGWbcXKtA0XvNS9B2ZiX5YsoJ\nvS57lsxbWbgsPCBGOPj5/SdK+bRY4RXg5VjNV/oEj2kPlihw/Sqz3DtYvtKM9ln6+Oq8pYRX\nmxOv31nv2Z/NPLVivjJD/VLGlc9bbpQZt1fInbviTjP3SIpNFl/KbJ8jzX2gdkexI6gz+3rV\nvWvUSTNPv69ul83yxT1CIrmHPpBVgT6QVYBEcg2JpAKJxCGRABJJBRKJQyIBJJIKJBKHRAJI\nJBVIJA6JBJBIKpBIHBIJIJFCcOyVO5sMOe6wAInEIZEAEikzRyvrH5JWc/gWKonEIZEAEikz\n8HcR2rPyJUgkDokEkEiZqQEi3ShfgkTikEgAiZQZ/GOT6+VLkEgcEgkgkTLTFUR6Qr4EicQh\nkQASKTM/Gd88L71fvgSJxCGRABIpBHsfq1yl6z6HBUgkDokEkEgqkEgcEgkgkVQgkTgkEkAi\nqUAicUgkgERSgUTikEgAiaQCicQhkQASSQUSiUMiASSSCiQSh0QCSCQVSCQOiQSQSCqQSBwS\nCSCRVCCROCQSQCKpQCJxSCSARFKBROIoiXR24hPtBh4MBOa2CNKSRMoEiaRADhRp6KMb9g1+\n6M/AhEFbtmzZeolEOvB6lwE/iA9YRdp4V+VGDq159gzu8spOefn1pNhkoTtlxrTuT4vduBY2\nrHy3cF/q1IZFSnQVyrPrV24h9CNJG9+rr3CfcX/v/AllhA5o+2sXKvWiUF75XNd3hDuM7KxZ\nqMwQoTz2tus7CfcZ39uyyu0fC+URtao9KtxVYWmJ+IKDhfIjJYo0Fm5ivqlZNcss9b+xxlNm\no8xws5QJq0i2WbKz4aUuww86DHYxRVrY+4mJabJlw3ORRPK3+DEQON16ZWDQLOvj4Z9MXaQ1\nRTVNixd2dqtI443OCb1lay/IF6wmz5GVqxt/wcb6IflP1NNjW94pweit4uPPvdPoRlGQr/2I\n0T9iFosHjX6TT/Gy0WbT7Ku51NjScrxsNHGosJvF2Ua5Mi/X0WP8JhbnGc/dlpeNPwdP5GvD\nbRaq8HJ+PcbuYXGCdZbSjU0rxDUNM0uZsYhkmyU7E/R2IsXXy8oXVaQexl/6ynqVhuciiXSg\nz+lA4EKnLwNPrjx96lKJZOydWtKP5iOiSKnQr8snaX15HLorFZVMJev8wwZ/ESJr/7cW+gbF\nsZe0YlC+CyO29mG9v/wPQWZHNOyDx7vC5oHMRPvWOpgfugzxdrfQ/Nb0Lh9ktrNjo7tKrIw/\nCOu3hv1qWUs0+yxBCxn+AhJmlkIgimSfJRvb4Od2+Lv1iyfSp/BzPqo82sW82LCxxU8X7u97\nb4see/Q068UXXxx6JhxnA+fCLiNhD+4iE82H/hUG+xDLPUOvvRzL80KXq2G5oTXfhbE7lj/B\njDEPRtYZczlm6HmmdcGI2mkLIJ7CWAzL2Mwy9jeIKVguh2W8AYn2N8RtGJtjGTvQ+jBiS1nt\nSsyJ1jLrAstmqQjEBHezFILABfO/7bNkYzyW90kHO3ve9fOGx7KrPQJPXVh5tH9d7LdqIl34\n+oHJgV9aTfnNP6LD78E8oGbNmnd4M9EbbA96O3R5LJYfCl1eiOXPQpfLYvl6zNhD9naMrPXl\nRMwY4zC2wPw5ZjymtMeYH8sTIKZhLIDlPph/gbgOY3Essx6yf0L8DmMD25ZjxE6EWgnrprDy\nu7ZZwsNbbnezFAb7LNl4C8s/Kg2eNfDIm3Axn+M8/y8vIp18sd1i/M8zbVYE////jh8/fuLX\ncPwROBt2GQnH8cV1nvnQ/06b/81aHE8IvfYOLP8QuvwYlt/AjG0Zn8DIuqNuw5wLYimMg7F8\nEDM2sxyE8UZbGftLXo8RX6lL/R9EdnJWD8v3Qoxj04Br98GMvcGTMG7AtZthxuaVuSWzVBni\nFe5mKQQXzpn/bZ8lG9i2PI98L/n9X9fPG55TgTNmGAjPXVN5tL/+DrvI7yoipbQbYa7XYy77\nLxfnkervkV6FPUR4xHKx4TajXM6+FsN4t6l1kZWh/SRvKLnWsLYIfwtf2ig3YBHfQn2LMb2o\nEVuwMrScvZK90zgG+/5VrNzaiD52AeAEiMb6rWNvy1jW0W9/vJEHsHJ7IxZgb0R2gdQjWbm4\nEXnjzG9gSweyXNc6Sytg0/hlkjCzlBnLxQbbLNnIgP6hw+WDXbz3SIfKG88taZ3rgov0Hunc\nI+8b/67t8Ucg8FfrTZdEpIxRFXyFe4nvgy0ipTbPpcXUlt7w5sQrpbQSL0n7BG/RuzEnm7f5\nWHprXOKd5gWmlFoxWq77zHfRT8QGzxPMy1O7asRoudubV5E/r5EruSXvvOqfpw/OLwf4/S19\nlktj+zoWiK083Sw3CZbzL+VxRTmflihcLe8cp/mqmj2nF5XyaXnM691pevfbJLNT5vigh7E9\neUxtYZ2lmYWDzzWexzCzlBmLSPZZsnGoR2FfhdEZsvJFvWq39b7k3DfMlS4closk0qZ71+0M\n8n+nOg3atmtgH3526OLJsvSBrO03bP9A9pDfEef948+D1g9k09KtddvgB046lv/43Zptn82k\nWKN902zls39YP5C1PVe67SKb7blSD1jzr9aYZruztweL/Jk/kM3Sr+CifiCb4e0Hs3GRRPqy\nhcHCQMbrnR4eY14Ad/Fk9M0G79A3GxS4PL7ZIMHFk5FI3iGRFCCR3EMiqUAiKUAiuYZEUoFE\n4pBIAImkAonEIZEAEkkFEolDIgEkkgokEodEAkgkFUgkDokEkEgqkEgcEgkgkVQgkTgkEkAi\nqUAicUgkgERSgUTikEgAiaRClkRa+ub4H8VMIpFIdkiksJxormla4ijhERKJRLJDIoXlWeNv\n7eKXmY+QSCSSHRIpLPC3vJpwe0ASiUSyQyKFBW980dJ8hEQikeyQSGHB2yP1NR8hkUgkOyRS\nWN43PCqyy3yERCKR7JBI4RlRQNOuE641kEgkUiZIJBekfb/DkkkkEskOiaQAiUQi2SGRFCCR\nSCQ7JJICJBKJZIdEUoBEIpHskEgKkEj/jUibB7+4XMzfTl16Uras358+ofs48bbUa158UWwe\nl/riPa+Ia++aOVu8cfD+NjWeFEf7pvfLW4WYumjaarG86PlXhc9H/ClP3CV+OdP/5VND9gpx\nXvGkO8TymGZdxdsOb3ri/ili+eEKt20R4vZXnrZ0/Ly76I3id6rfu7JkP7FsEynls493CzHt\nkes7ifcwts1S+tdTV4g37941b7E4S2mLp33nd8/WD+ZabnFsE2nzjC+O+JUhkdzSWe+kUJvH\nPXqjharrZEsvTdZbiszn+S7908B7eJyot6OI/ZTnfnGalvw2j0ZDSZ/ZVLamHs2mDSuuCuY7\n+T2206rqDSHM1pdP6VuawG+qf6yiXu7Py9DLgouYksf6FbRWesx/lMXlRgMJU7weer6O36j8\nPWOwO3kZWl+KM2ERaWSSpsXzThf+0T5rwwjbLG3Su57VNq9Z22Zpjd4lpr79vuYy0rsGly48\nQ3jEIlJax2C5+Kf2tVxDIrkEu/E8yHIjI1aS3Co9Pa9RzsPKz8HabG8+BG1dYtkxCXZHbQFG\nbHLGm6W0gTyJrQ3dvh5g5aZQZh2TsbVKfla+1Yi+hRhZbyZWxi56X2KcDJF3YoEt1WZixE6F\nd7OyZl27DsS8wlSIImHLz6kY07D5EjtO4CyxI1ra9Uasw45Jtlk6Dl/6aeJ3xxBj6UThpc8i\n0vOw4VszrecSEsklFeG3mIBxI+5Bs0IvPQnLIzBjd8oiGLtimbVHuRki+0LlLVhmL9XQski7\n2jq4j52u4dcxWbdU7DumbcKMe2sdjGiGtg3ifoysDUwpq2eLMBbGfB3EXBiH2so+69o6okjY\nxYwd17vg0vdbZ4kNxjrtstM32yzNxLJ43ukAtKjWupuPWEQqCOXn3Q2WGRLJJfhLZi2Ov8Lf\n4qjQSz+L5ccxowpMw/pYboUZf8m1rFG7F7PPuoMNwvJKzBhLYWQqYD8l1iS2onVptsuwvZU5\nnhcznjGx3pbxWC5pNaWBraxZyzqiSKhCGYzsBaOqdZbYYOzV6JPQszQSy+wIFQZ8ubnPfEQU\n6RgO1tHdYJkhkVyCXYhZK/EtOPGzQy89DcvvYMbzp2IYe2KZHXJwj2qN8XYss7cDCRDZQWMK\nxFj27gB3kRsx4t6qsTdJeAiqZ40aXl84YNuZWZNYjKxfMtty7NXMeg2+ZSuHOSLdD9XbMPbA\npdtZZ6koRnY0XBN6lrB1ODu0hqM8LG2+lbQekfC5+2dazyUkkktQDXaI8Tc34vUnQi+dDgew\nfOy63WBY+zWMR2Mtu6Mfun/Hf4MRO6rz9+yPQP6QrQ1Sd2Jl2D198zCute6O/sZQZlccn7ft\n63gAYy37PoHIG/7Blmps8LmgShtWRnNYV058u1ZImApRpKVwzGGHGHyP5GPX7XCWhmE8WcuI\njSWzlAqnmcIfGDkCDdiTN5uPWER6BTZ8R6b1XEIiuaWX/lJuXp76SW+gXFt6fr6mcLBc0Lxc\n3i64z/g68PiRfhSJW8zz60nBM7f3eByq72GxZgtSvQVyTB8e1+rHhdb8Wm16bX1p81rYQH3t\nfPxqlvGePZd5aay89XX8UAF9Xzb/TOcxfe3i/NL8xhiLOP7+ull1eISWx215Nv4ONU6cCctV\nu0nBF5jkN3j8QH8u3wSebbO0Xb8yeqfZINQ2S5v0Y2/zn/3uyHg2TtNKi2cQFpHSe+TWtPLz\n7Wu5hkRyzf7xb1iu6WyZvd6hQan/y/6W075dI0aKH6D4Jzz0vhgPzF8sfoiR9lyDN8Xy5qFj\nxXa16atnbxfLG9+YLH5CcnRIR8tzrx08SRx8W9XCPcXynE6vHBXi/kFPWD4oer1GO3FnPTB+\nyCax/PSVLcTn/rZ2peli2fY50pHF8w+KeWi9AWK0z9KGzyzPdeC7teIPkrFutperbClfLLNc\nZLV9jrR37grJ+YUbSCT30DcbVKBvNihAIrmGRFKBROKQSACJpAKJxCGRABJJBRKJQyIBJJIK\nJBKHRAJIJBVIJA6JBJBIKpBIHBIJIJFUIJE4JBJAIqlAInFIJIBEUoFE4pBIAImkAonEIZEA\nEkkFEolDIgEkkgokEodEAkgkFUgkDokEkEgqkEgcEgkgkVQgkTgkEkAiqUAicUgkgERSgUTi\nkEgAiaQCicQhkQASSQUSiUMiASSSCiQSh0QCSCQVSCQOiQSQSCqQSBwSCSCRVCCROCQSQCKp\nQCJxSCSARFKBROJcxiId22/N+9Kt5UN+D5zKyIpIJ2196lKsDc+ObbKW91vvxbt7pt+JP3+1\nipRi7fC5f5XfqXz8oLWcZp2l/bv8Thyxdp/M2Gct20RK2+A4WBhIpP9EpGn5NC3e7Ppxol9+\nLU9Xc6dZdnPm04j3AAAgAElEQVSMr9pXbgc70j2Plq+vpN1fWFI6xmuFh5g7aM/cmlZ4Do+r\nympaTEuzPKGMlruZeZPsYT6xV0UmNjfJrZUz71SfMbyoFtfObEH7TvC5fPfweHJQIS2h80/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GSHqUEl4lXqQDpLFXSYzzPrF8SUtJscnE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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the relationship between constituent opinion (x-axis) and politician's perceptions (y-axis)\n",
    "plot.gunban <- qplot(gunsbanassault_opinion, gunsbanassault_perception, data = data)\n",
    "plot.gunban"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "`geom_smooth()` using formula 'y ~ x'\n",
      "\n",
      "Warning message:\n",
      "“Removed 790 rows containing non-finite values (stat_smooth).”\n",
      "Warning message:\n",
      "“Removed 790 rows containing missing values (geom_point).”\n"
     ]
    },
    {
     "data": {
      "image/png": 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Tt27Ni9e3dWsWXLlgMGDGAVo6Oj9XNOX8DkyZOZO64MBQcHGw1SXPPmzRMI2E9s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OnO8aEgAAANDiIbu61x8V1sdYEK5OWb56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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Now, add a regression line and make sure the x-axis goes from 0 to 100\n",
    "plot.gunban.with.lm <- plot.gunban +\n",
    "geom_smooth(method = \"lm\") +\n",
    "xlim(0, 100) +\n",
    "ylim(-50, 100) \n",
    "plot.gunban.with.lm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "Call:\n",
       "lm(formula = gunsbanassault_perception ~ gunsbanassault_opinion, \n",
       "    data = data)\n",
       "\n",
       "Residuals:\n",
       "    Min      1Q  Median      3Q     Max \n",
       "-61.377 -15.248  -1.111  13.712  72.915 \n",
       "\n",
       "Coefficients:\n",
       "                        Estimate Std. Error t value Pr(>|t|)    \n",
       "(Intercept)            -45.61548    5.57700  -8.179 1.18e-15 ***\n",
       "gunsbanassault_opinion   1.37170    0.09027  15.196  < 2e-16 ***\n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1\n",
       "\n",
       "Residual standard error: 20.51 on 766 degrees of freedom\n",
       "  (790 observations deleted due to missingness)\n",
       "Multiple R-squared:  0.2316,\tAdjusted R-squared:  0.2306 \n",
       "F-statistic: 230.9 on 1 and 766 DF,  p-value: < 2.2e-16\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Let's compute the bivariate regression.\n",
    "summary(lm(gunsbanassault_perception ~ gunsbanassault_opinion, data = data))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "57.13"
      ],
      "text/latex": [
       "57.13"
      ],
      "text/markdown": [
       "57.13"
      ],
      "text/plain": [
       "[1] 57.13"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How do we find the predicted level of politicians' perceptions of constituent support for the ban on assault weapons \n",
    "# when constituent support is at 75%?\n",
    "predicted.perception.75 <- -45.62 + 1.37*75\n",
    "predicted.perception.75"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "69.5298569932586"
      ],
      "text/latex": [
       "69.5298569932586"
      ],
      "text/markdown": [
       "69.5298569932586"
      ],
      "text/plain": [
       "[1] 69.52986"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "49.6359040807643"
      ],
      "text/latex": [
       "49.6359040807643"
      ],
      "text/markdown": [
       "49.6359040807643"
      ],
      "text/plain": [
       "[1] 49.6359"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How do we find the predicted level of politicians' perceptions of constituent support the ban on assault weapons\n",
    "# when constituent support is one standard deviation above the mean?\n",
    "mean.plus.sd <- mean(data$gunsbanassault_opinion, na.rm = TRUE) + sd(data$gunsbanassault_opinion, na.rm = TRUE)\n",
    "mean.plus.sd \n",
    "\n",
    "predicted.perception.mean.plus.sd <- -45.62 + 1.37*mean.plus.sd\n",
    "predicted.perception.mean.plus.sd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "0.481248376620639"
      ],
      "text/latex": [
       "0.481248376620639"
      ],
      "text/markdown": [
       "0.481248376620639"
      ],
      "text/plain": [
       "[1] 0.4812484"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# How do we find the correlation?\n",
    "correlation <- sqrt(0.2316)\n",
    "correlation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
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   "language": "R",
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