diff --git a/Some_Pig_Homework.ipynb b/Some_Pig_Homework.ipynb
new file mode 100644
index 0000000..05039c1
--- /dev/null
+++ b/Some_Pig_Homework.ipynb
@@ -0,0 +1,822 @@
+{
+ "metadata": {
+  "name": "",
+  "signature": "sha256:cab5e03789ef97115ec44019a57a07d3c84780d6a5a851a4fea1495f56ceb3c4"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+  {
+   "cells": [
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "import random\n",
+      "import matplotlib.pyplot as plt\n",
+      "import seaborn as sb\n",
+      "import statistics as st\n",
+      "import math\n",
+      "from numpy import mean"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 11
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "%matplotlib inline"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 12
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class Player:\n",
+      "    \"\"\"Player something something\n",
+      "    \n",
+      "    Responsibilities:\n",
+      "\n",
+      "    * Plays one turn\n",
+      "    * Parent class only rolls once per turn\n",
+      "\n",
+      "    Collaborators:\n",
+      "    * Interacts with Game Class\"\"\"\n",
+      "\n",
+      "    \n",
+      "    def __init__(self, roll_num = 0):\n",
+      "        self.roll_num = roll_num\n",
+      "       \n",
+      "    def dice_roll(self):\n",
+      "        return random.randint(1, 6)\n",
+      "    \n",
+      "    def play_turn(self):\n",
+      "        \"\"\"rolls only once per turn\"\"\"\n",
+      "        turn_score = 0\n",
+      "        roll_num = self.roll_num\n",
+      "        while roll_num < 1:\n",
+      "            roll = self.dice_roll()\n",
+      "            if roll != 1:\n",
+      "                turn_score += roll\n",
+      "                roll_num += 1\n",
+      "            else:\n",
+      "                turn_score = 0\n",
+      "                break\n",
+      "        return turn_score\n",
+      "    \n"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 13
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class Agro(Player):\n",
+      "    \"\"\"Player rolls until score is 12+\"\"\"\n",
+      "    \n",
+      "    def play_turn(self):\n",
+      "        turn_score = 0\n",
+      "        #roll_num = self.roll_num\n",
+      "        while turn_score < 12:\n",
+      "            roll = self.dice_roll()\n",
+      "            if roll != 1:\n",
+      "                turn_score += roll\n",
+      "                #roll_num += 1\n",
+      "            else:\n",
+      "                turn_score = 0\n",
+      "                break\n",
+      "        return turn_score"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 14
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class SuperAgro(Player):\n",
+      "    \"\"\"Player rolls until score is 20+\"\"\"\n",
+      "    \n",
+      "    def play_turn(self):\n",
+      "        turn_score = 0\n",
+      "        #roll_num = self.roll_num\n",
+      "        while turn_score < 21:\n",
+      "            roll = self.dice_roll()\n",
+      "            if roll != 1:\n",
+      "                turn_score += roll\n",
+      "                #roll_num += 1\n",
+      "            else:\n",
+      "                turn_score = 0\n",
+      "                break\n",
+      "        return turn_score"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 15
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class Dummy(Player):\n",
+      "    \"\"\"Player rolls until turn score is 50+\"\"\"\n",
+      "    \n",
+      "    def play_turn(self):\n",
+      "        turn_score = 0\n",
+      "        #roll_num = self.roll_num\n",
+      "        while turn_score < 50:\n",
+      "            roll = self.dice_roll()\n",
+      "            if roll != 1:\n",
+      "                turn_score += roll\n",
+      "                #roll_num += 1\n",
+      "            else:\n",
+      "                turn_score = 0\n",
+      "                break\n",
+      "        return turn_score\n",
+      "    "
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 16
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class FiveRoller(Player):\n",
+      "    \"\"\"Player tries to roll 5 times each turn\"\"\"\n",
+      "    \n",
+      "    def play_turn(self):\n",
+      "        \"\"\"rolls only once per turn\"\"\"\n",
+      "        turn_score = 0\n",
+      "        roll_num = self.roll_num\n",
+      "        while roll_num < 6:\n",
+      "            roll = self.dice_roll()\n",
+      "            if roll != 1:\n",
+      "                turn_score += roll\n",
+      "                roll_num += 1\n",
+      "            else:\n",
+      "                turn_score = 0\n",
+      "                break\n",
+      "        return turn_score"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 17
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class SevenRoller(Player):\n",
+      "    \"\"\"Player tries to roll 7 times each turn\"\"\"\n",
+      "    \n",
+      "    def play_turn(self):\n",
+      "        \"\"\"rolls only once per turn\"\"\"\n",
+      "        turn_score = 0\n",
+      "        roll_num = self.roll_num\n",
+      "        while roll_num < 8:\n",
+      "            roll = self.dice_roll()\n",
+      "            if roll != 1:\n",
+      "                turn_score += roll\n",
+      "                roll_num += 1\n",
+      "            else:\n",
+      "                turn_score = 0\n",
+      "                break\n",
+      "        return turn_score"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 18
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "class Game:\n",
+      "    \"\"\"Runs the game according to player strategy\n",
+      "    \n",
+      "    Responsibilites:\n",
+      "    * Keeps up with Player turns\n",
+      "    * Keeps up with final score\n",
+      "    \n",
+      "    Collaborators:\n",
+      "    * Players\"\"\"\n",
+      "    \n",
+      "    def __init__(self, player):\n",
+      "        self.player = player\n",
+      "        \n",
+      "    def play_game(self, player):\n",
+      "        \"\"\"Runs the game for seven turns and returns total score\"\"\"\n",
+      "        turns = 7\n",
+      "        turn_score = []\n",
+      "        while turns > 0:\n",
+      "            turn_score.append(player.play_turn())\n",
+      "            turns -= 1\n",
+      "        \n",
+      "        #print(turn_score)\n",
+      "        total_score = sum(turn_score)\n",
+      "        return total_score\n",
+      "    "
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 46
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Five_Roller Data for 25,000 Games\n"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "player = FiveRoller()\n",
+      "game = Game(player)\n",
+      "\n",
+      "game.play_game(five_roller)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 49,
+       "text": [
+        "43"
+       ]
+      }
+     ],
+     "prompt_number": 49
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "five_roller_list = [game.play_game(player) for _ in range(25000)]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 50
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.mean(five_roller_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 51,
+       "text": [
+        "56.62044"
+       ]
+      }
+     ],
+     "prompt_number": 51
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.pstdev(five_roller_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 52,
+       "text": [
+        "30.420758277965394"
+       ]
+      }
+     ],
+     "prompt_number": 52
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "plt.hist(five_roller_list, bins=50)\n",
+      "plt.xlabel(\"Scores\")\n",
+      "plt.ylabel(\"Games\")\n",
+      "\n",
+      "\n",
+      "ymin, ymax = plt.ylim()\n",
+      "mean = st.mean(five_roller_list)\n",
+      "stdev = st.pstdev(five_roller_list)\n",
+      "plt.vlines(mean, ymin, ymax, color=\"red\")\n",
+      "plt.vlines([mean - 2 * stdev, mean - stdev, mean + stdev, mean + 2 * stdev], ymin, ymax, linestyles=\"dashed\", color=\"red\")\n",
+      "plt.title(\"Player Holds @ 5 Rolls\\n Mean: {} \\n Standard Deviation: {}\".format(mean, stdev))\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEwCAYAAACZoyciAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJBMFEBERyUQBREREMlEAERGRTP4fkOeK/x5LGYEAAAAASUVORK5CYII=\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10e2766a0>"
+       ]
+      }
+     ],
+     "prompt_number": 53
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Seven Roller Data for 25,000 games"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "seven_roller = SevenRoller()\n",
+      "game = Game(player)\n",
+      "\n",
+      "game.play_game(seven_roller)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 54,
+       "text": [
+        "58"
+       ]
+      }
+     ],
+     "prompt_number": 54
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "seven_roller_list = [game.play_game(seven_roller) for _ in range(25000)]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 55
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.mean(seven_roller_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 56,
+       "text": [
+        "52.36484"
+       ]
+      }
+     ],
+     "prompt_number": 56
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.pstdev(seven_roller_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 57,
+       "text": [
+        "36.26210876072157"
+       ]
+      }
+     ],
+     "prompt_number": 57
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "plt.hist(seven_roller_list, bins=50)\n",
+      "plt.xlabel(\"Scores\")\n",
+      "plt.ylabel(\"Games\")\n",
+      "\n",
+      "\n",
+      "ymin, ymax = plt.ylim()\n",
+      "mean = st.mean(seven_roller_list)\n",
+      "stdev = st.pstdev(seven_roller_list)\n",
+      "plt.vlines(mean, ymin, ymax, color=\"red\")\n",
+      "plt.vlines([mean - 2 * stdev, mean - stdev, mean + stdev, mean + 2 * stdev], ymin, ymax, linestyles=\"dashed\", color=\"red\")\n",
+      "plt.title(\"Player Holds @ 7 Rolls\\n Mean: {} \\n Standard Deviation: {}\".format(mean, stdev))\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEwCAYAAACZoyciAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkUSUQEREJJH/D1xfFm+KU477AAAAAElFTkSuQmCC\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10e3d4cf8>"
+       ]
+      }
+     ],
+     "prompt_number": 58
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Standard Player Data for 25,000 Games"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "standard_player = Player()\n",
+      "game = Game(player)\n",
+      "\n",
+      "game.play_game(standard_player)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 59,
+       "text": [
+        "32"
+       ]
+      }
+     ],
+     "prompt_number": 59
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "standard_player_list = [game.play_game(standard_player) for _ in range(25000)]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 60
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.mean(standard_player_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 61,
+       "text": [
+        "23.41216"
+       ]
+      }
+     ],
+     "prompt_number": 61
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.pstdev(standard_player_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 62,
+       "text": [
+        "5.232938384349658"
+       ]
+      }
+     ],
+     "prompt_number": 62
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "plt.hist(standard_player_list, bins=50)\n",
+      "plt.xlabel(\"Scores\")\n",
+      "plt.ylabel(\"Games\")\n",
+      "\n",
+      "\n",
+      "ymin, ymax = plt.ylim()\n",
+      "mean = st.mean(standard_player_list)\n",
+      "stdev = st.pstdev(standard_player_list)\n",
+      "plt.vlines(mean, ymin, ymax, color=\"red\")\n",
+      "plt.vlines([mean - 2 * stdev, mean - stdev, mean + stdev, mean + 2 * stdev], ymin, ymax, linestyles=\"dashed\", color=\"red\")\n",
+      "plt.title(\"Player Holds @ 1 Roll\\n Mean: {} \\n Standard Deviation: {}\".format(mean, stdev))\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAY4AAAEwCAYAAACgxJZ5AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nUBq6owAAAABJRU5ErkJggg==\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10e4a5128>"
+       ]
+      }
+     ],
+     "prompt_number": 63
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Aggressive Player Data for 25,000 Games"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "agro_player = Agro()\n",
+      "game = Game(player)\n",
+      "\n",
+      "game.play_game(agro_player)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 64,
+       "text": [
+        "51"
+       ]
+      }
+     ],
+     "prompt_number": 64
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "agro_player_list = [game.play_game(agro_player) for _ in range(25000)]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 65
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.mean(agro_player_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 66,
+       "text": [
+        "51.53208"
+       ]
+      }
+     ],
+     "prompt_number": 66
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "st.pstdev(agro_player_list)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 67,
+       "text": [
+        "18.263036189900077"
+       ]
+      }
+     ],
+     "prompt_number": 67
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "plt.hist(agro_player_list, bins=50)\n",
+      "plt.xlabel(\"Scores\")\n",
+      "plt.ylabel(\"Games\")\n",
+      "\n",
+      "\n",
+      "ymin, ymax = plt.ylim()\n",
+      "mean = st.mean(agro_player_list)\n",
+      "stdev = st.pstdev(agro_player_list)\n",
+      "plt.vlines(mean, ymin, ymax, color=\"red\")\n",
+      "plt.vlines([mean - 2 * stdev, mean - stdev, mean + stdev, mean + 2 * stdev], ymin, ymax, linestyles=\"dashed\", color=\"red\")\n",
+      "plt.title(\"Player Holds 12+ points\\n Mean: {} \\n Standard Deviation: {}\".format(mean, stdev))\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEwCAYAAACZoyciAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XmYHGXV9/HvTCCBkEkkOixCAAl4RNmj7LIoLoCCoCyC\nEEGCArLoI/gQWRRBQAyyCChECIuCBkFAHiK8qBCiyB5B8LBoIChCICELgazz/nHuJj2d7llqprfK\n73NduTJdVd1931M9fereTrV0dHQgIiLSW631LoCIiDQnBRAREclEAURERDJRABERkUwUQEREJBMF\nEBERyWSlehdAVhxmtgHwPPC3os0twEXufrWZfRn4vLt/tsbl+hNwibv/pmjbBsAT7t7W2+em7R8G\nJrr7+zKU50xgdXc/Lj1uBc4F9gSWAs8CX3X313r72r0sxyjgf919/26OOx143N1vq2Z5pPEogEit\nzXf3rQoPzOy9wJNm9jBQr0VJHX147748txMzWxe4ENgD+HnRriOArYCt3H2RmZ0HjANG98f7VuLu\njwBdBo/kY8Dfq1kWaUwKIFJX7v4fM3sWeH/xdjPbDjgPGASsDdzt7kea2XeAD7r7Iem4HYkWwNZm\ntgNxpb4acaX+XXe/I7VsvgIMBt5w94+XKUpLV+U0s9OAg4DFwDPA1939lZJjjgZOBGZT9IVqZh8g\nAsKg9D7j3f3yMm9zBHAv8BSwetH2J4GH3X1RevwIcEzJe08A/uju11Qo/3eBTYF2YC1gKvAVd59r\nZh8CfgIMJ4LhOHe/zsx2JX63m6XXnw1sBowA/pF+H18GRgHnm9kS4DUiuA1Ir3WOu99crkzS/DQG\nInVlZtsDGwEP0PlL/HjgNHffDvgQsLeZbQVcAexlZu9Kx30VuNzMVgeuBr7k7qOAfdL2Eem4DwK7\ndBE8zjezxwr/gDtILQszOxz4NPBhd9+C+EKfUFKPLYEzgI+6+zbAmyxrmZwE3ObuHya6oXY2s+UC\nlruf6e6XEMGvePsD7v54ep/VgdOBX5c8vSetoO2JFsUHgEXA6WY2ALiN6Ebcgmj9/CAF8FJbA58C\nNgHeC3zB3S8FHga+5e6/Bb4LXJDqegSwWw/KJU1KLRCptVXTFzTE5+814GB3/7eZFR83mggUpxBf\nWIOBIe4+w8x+BxxmZtcBnwS+BuxKXFnfWvQ6S4kr5g7gb+4+r0KZOogvwHeulM1sfSJQQHypXuXu\nb6XHFwPfMbOV0+MW4OPA79391bTtZ8Be6eebgWvNbBvg/wHHu3tXX/hl95nZSOC3wH3uflna9gDR\nslkP+JiZnQjcXxg/KXnNiYXymdnPie6yq4BB6csfd3/ZzH5DBMw/ljx/UqEVZGZPEC2WUr8GLjWz\nz6a6fqeLekqTUwCRWnureAykC/cDjwGTiC+lbVjWQrkUuJzoTrrJ3eenK+mnU4sFADNbB3gF+BJQ\nKXhU0lLyc/HjVuJvp3jbUjq36JcUfkjdaBsDnyACzRlmtoO7/7OnhTGz3YAbgfPc/YKi194u7b+a\n6MK6touXWVL084D0uFwvxADKfze8XfRzB2W6/dz9CjO7nQjsnwa+a2abu/ucLsolTUpdWNJwUvdU\nYQbQb4F1iW6uAQDu/hfiC/tbRCCB6ALb2Mx2Tq+xOdFPv3Y/FOn3wOFmNjg9Ph64190XpscdwN3A\nJ1PQghgbKNTnl8CB7v4r4FhgTqpTJZ2+mNPYzi3AocXBo5daiG7AYWlW1xii68qBhWa2b3qv9wL7\npfqUBtFKFgMD0/OnEIP91xDdi+9K/ySHFECk1rrruulw9zeAc4BHzex+4BDg/4ggUjAB+Le7/x3A\n3WcAnwd+aGaPA9cTX7jTyT5TqvCcnxPdMQ+a2VPAlqlM73D3J4GTgXvM7CFiIL/w/DOBQ1K5HgBu\ndvf7unnf4vJ+Nz0+r2icptO0YXc/vJvWRwfwX2Js52liQPwH7r4Y+BxwgplNJQLH99z93pLfQVe/\nw9uBH5nZoel3cKaZPQr8gZjI8GIX5ZIm1qJ07tJszGwl4or8WnefWO/yNIM0C2tNdz+63mWR/FAL\nRJqKmX0QeJWYjqvg0XP9tl5FpEAtEBERyUQtEBERyUTTeCUXUk6qnYGR7v6vou27EOsZTnL3cTUu\n03HAWGLwGmCOu+9StP9dwH3A4SltSLnXeARYBSjM+Lre3celWWaXE+tjOoCx7j4pPedLxAy1DmA+\nse7kkTTV+QJiiu1KwI/c/WfpOZsBPy16vf9197v65zcheaUAInnRAbxArPn4ftH20cRakHr01W4P\nfMPdbyzdYWZ7Egv51qPywsHVgA2B97j7kpLd1xEr9W9LqUj+YmbDgZHAD4mptK+Y2R7EQsb1iWm1\nI4mV/UPTcx5194eIYHSlu09Iq+r/ZGbD3X0pIhUogEie/IKYXvt9gLRuY0diCm5L2rYOcAnxxb0y\ncKO7n5P2jSVSoKxCTMP9lrv/Ns1g2oBY6b4+MINY1/GymX2VSHEypkx5dgTazOxkYuD/W2m6L8Bx\nwGHADV3UZxtiAeT/mdnaqR5j3f1tIkAUvtw3AmYRCwPfJnJcFfJ0PQKslVbN7wv8ND3vDTO7kQi4\nDxFrUwory4cChVX3IhVpDETy5DFiUdw26fF+xGK5xSy7yr+OSEvyYWBb4BNmtr+ZrUesEt855YQ6\nlVi/UbATkftpE+LL+qsA7v6zcsEjtR6eAs52962JtSR3pu24+x7u/kA39RlCrKX4PPARIuidk56/\n1MxazOx54DfECvUOd3/B3e9MZWghuqxuTSlI1gWmF73+v1m2oHEscIqZTSfWghyt1od0RwFE8uZa\n4qoa4gp/QmFHapHsAnw/5eP6C/EFukVa7DYaONTMziECxGpFr/vHolxaj1E+D9Q73P3N4iCRphzP\nIgJBj7j77e4+2t3nufsC4AdEK6Kwv8PdRxItkFNSupNCXVcjUsBsCByZNpf7e19iZkOAO4HR7j6C\nGEu6IqWXF6lIAUTypIPoxvqCxQ2hhhZWqieFLtvt3X2rlJNrB+AcM9uaCChDiNQl59H576PbPFDF\nzGy9NIherIVlg+HdMrPPmtlHiza1AovMbGUzO6iQ0dfdpxHdW1sW3hv4M5Fxd7eiPFQvEll0C9Yh\nWiQfABa4+/+l1/srkY5+G0S6oAAiueLuLxN3PLyKaI1A+rJPX6QPAP8DYGbDgMnEuMdHgYfc/cK0\nbV9S7q0yugweyXyipfOR9F57AqsCD/aiOusQKUJWSTOovkmM2SwixnkOSq/9XiJt+r1pIP1eIsnk\nwanlUnArcISZDUgzwA4ksvs6MMQitX4h6+8mREtLpCINokseXUuMOeyXHhfPcjoY+ImZ/Y1IAPhL\nd/+lma0BfN7MngReJzLffjF175Su4n7nsZl9DRhVOg7i7q+Z2QHAz8xsIJF7at+Ue6qikkH5nxFd\nUI8Sf6t/YNm4zL5E2vSTSYkl3f1RixturQvsZ2b7Fb30x4iZViOJm0kNJAbUJ6f33Re40MxWJVou\nRxVPhxYpRyvRRUQkE3VhiYhIJgogIiKSicZAmpCZtRHz+7cl+r+XApe6+8/T/iOBld398sqv0qv3\n+wJwrLtnvr+1mb0HeNXdl7toMbNpxCynt4gB6pWI9RunlVmB3dP3+x7wnLtf18Uxw4Bb3P1j6fFj\nxH3Tq3L3PDMbBPyOGHv4TVEZfg4YcUF3VbmUK2bWToyJjCR+P3cA33b3jjTr6jJihtVKxHjIXWns\n5RJiDQvEVN2T0xqSdmKsaD3i83NUulEXZvZ14jbBHcDzwJh0vxXM7BjgK8SEgEeIRYvvzCwzsyOA\nz7n73kXbjgWOIdbj/Cs95/U0U+6nxJjN28RalonpOQcApxGLI/9NrEt5Me0bCxya6nq9u3+v6HdU\nqU57EdOgBxGTLL7i7nPNbCKd7zOzIZH65hTgl0XbBwCbAvulm5wJaoE0q3OJvEqbu/uWxL23Tzez\n3dP+nYicRs2ig7gv+lapPtsQs4B+nPUF3f2MroJHsjpF6zLS+1creGxPzADbkc4D8icB89x9M2A7\n4sZOHy7zEj8GnkyLHLcmLh6+nPbdDtyeFiweBvwqBauvA+929w8BmxNTlg9Iz7mUuKvih4h1MxPN\nbFUzG0XMUts+lelZlq3s3y+95seJdCirsmxG23Az+ylxv/jiem8MfA/YKZV9WnoMcA0w2d03JW73\ne5aZbZ6eczmwf/o8XEEslizMZvtC+h1sCuxmZvt3UadVUmC5ivjy/wDwT+JvCHffv2hK91HATOJi\n6enC9rTvbmLChYJHEbVAmtNawCtmtrK7L0opNfYFZpnZ54DPArub2XwiD9LPgDXS814ADnD3GenK\n/2riC2E94Ffu/m0AMzuTmLH0OvBc4Y3N7P3EH+pqxBXv40RajwVmtoCYFroFkVJkfeAsYkpr2WSB\n5Xjc4/zrwPNmNtbd55nZV4CjiYue14kvsv8SaxveX0jdYWYPEHfwOwh4wiPx4BHEl8NAYgHgue7+\n01T3VS3unvdh4gr5Pe4+08xOS6+xGHgG+HrKLfUnYo3Fjul3NplYgNdhZlcCD3tKUFiikFjx5JLt\nc4h0JwOIoN8KLGB5NxP3iSf9rv8OrJfyVq1eeE93f9ziFrhL3f0CMyt8ob+HuLXs6xY35Nor/T5x\n96lm9izwaXe/xcw2cvclZrYK0Tp4Pr3GYUQCxjfS7/pr6XcKsD/RUvhWeu2CwvqZoWY2m/jcvJG2\nbU1a9Onusyxuh7sv8CQw1d3/kY67HbjJzNZP+3/h7m+lMlwNfMnMbq5Qpz3S7/VBdy/U43JiJtqx\nhUKm1to1wInu/u/iX3xai/N5ImBJEbVAmtN3iS/918zsTjM7FZjr7v9KV0i3ARekLqwDgSnuvoO7\nb0h8mR+aXqcDWM3ddyauTo8zsw3MbB9iCuwWaXvx7VmPBK529x2Ipv/7gD3TvpWB29JV3kukqbQe\naUOe7U0F0x/xHMAsMuoeBnw0XWWfT9wWdjZxZ8IvEQduQgTJ36fydqQV2UcCe6TnHkQkG4S4gn/L\n3bf2orQdZnY48GliOu0WxBfahKLibeiRVXczYnrsLqnMYyoED9KajDvL7PopkWfrP8TV+Q3u/kSZ\n59/s7q+m8m0FfDHV/f3ANDMbZ2YPWNwC+L1prQjuvthiZf1zRMC9nwgmre7+etFbvERKa5KCx+eI\nRYY7FdV9Y2DN9JmbSnwO30jP+Zm7f5/OCy7xuKXwxcRak/8Qq9x/kHY/SGpFWeQo+xhx/h4DNrPI\nEAxxMTKAuL99pXQsXdVp3fRz8XOGpinaBV8BXnL3W1nej4gcZPPK7FuhKYA0IXd/wt2NWDx2F/El\n/zcz+0zRYYXFcxcDD5jZN83scuIqqjhFx63puP8QCf+GA7sDv/FIx7GECASFxXPfJq5iTyK+/N5L\nrN4umJz+34loARSuIq/IUNVCOvK9iGD15zROcR6weloMdyWRggTgcGIMoRDsWtz9TeAzwGdTq2ps\nUf3LLQhsIa5arypc5RJfgB+3SEjYQVwRk75QniO6wrK6Efi9u69JBOM9StZvdGJmnyIC5Nfd/W9E\n0N4R+JO7bwd8g+jCWrvwHHc/JZXxBeLqu9JCyMVFz/mtu7cT3U2/t1j1PpD4bOxPtNiGA2d3Vbk0\nlvEF4kt8beLzdk3aPRrYPK3J+TExrrPI3f8JjAHGm9nDLGs5L6RCOpYK23uyr+BEorVcWv4diG7A\nX5buEwWQpmOxini8mb3L3R919x+7+57Eh/+rRYcWFrqdR3wJvEJ0Zd1F5y+Qt0qe00IMQBZ/Nor/\n0G4k/rinEQP5j5a8XuEqbWnJ9i4X0JVK3RVDiP7qVuC6ov7orYHt3P0Nd58CrGSRQPGLRF/3O/Wx\nyOc0FRhBBLdT6X4leUvJMa1Ed29hW7nfWVY7E+cFd/8vMJG4MFiOmX2TGCQ+yN1/kTb/h7i9byGo\nPUT8zrYwsx3SeAIeCxivIX53hZbMu4pefh3gJTMbaWY7FW2/muiKXJ24cr/FIzfXIiJtzPY9qN/N\n7v5aCuyXFdVvFaL7b3N3P4AISM+m7qR/uPu2qfV6GRF8/kXldCyV6jQ9PWftku2zirrBtgJWcvf7\nypT/QJYFPCmhANJkUotgJHBGuiIm/b8xy8YZFrOsb/qTwIXpC2cGMVhZKUUHxBfiJGB/MxtmZq1E\nl1fhqv6TwJm+7H7k21Z4vfuBD1nc+AiWDfhW8s6XcPoSuAS4xCMVx13EqvC10iFj0raC8en4qe5e\n3FXRAowiZn+d7e53E+NDhUy1i8uUvYO4wj/cIvkiwPHE4GxhtlFfAkbp8x9gWUqS1Yius7+UPiEF\nj2OAbd39D0W7/gy8XWh9mtkHWLba/GPAj9NFRyvRFXRP+gzdQbrgSOfog8CfiC/nG8zs3en1DyFa\nkjOBm4AD0sB0C/A5uk/N8gCwV6obxFhCoX5nksYszGwL4rN5MzE4/+fUrQUxI+oud59FtGAOMbPB\naaLAaOC33dTpbmA7MyvMtvoaMVZXsAuxyr+cXYB7uqnjCkuD6M3pC0Q//jNm9iZxIXAzy9Jc3Emk\n6+hI235kMfXxVeJLYKPlX3IZd78z9T8/TGSQnQqsmXaPBW4xs1eIK7vfFL1eR9FrzDCzg4FfpMH1\n++j6pk6/MLO3iNbOACKX09npte5KLam7zWwpKS1I0XOvIfrVDyp5zQ4i0BxhZp7qfyvwcirz88Cj\nZvYU0eVWKN/PiRbLg+mL91nii7T4dZfTzSB6abkKDgcuM7PDiFbbjYXukvR6DxGtgDOJc3GLmRWe\n+2t3Pyd1a12Sxjog7nD4cvqdXUicv6VEC+yUdMwxRBfRE6k8X3L3ucBkMzubuKHUYqLV8bn0nMuI\nVsIjxDl6hOgyK61b8efgejPbEHgkfQ6msexi4iTgWjMbTZz3LxYGsM1sDDApXRw9WXiOu/8ufTYf\nJC6SfuvLZttVqtPcNK51U2rdPEeMqRVsRLRuytkolVnKUCoTERHJpGotEItpiVcSs0Q6iGbjAmJG\nx1LiquLYNP1xDDHNcjFwlrvfYZHU7XqgHZhL9JW+Vq3yiohI71RzDOQzxFz0nYiByx8A44jpcDsT\n/cD7pH7t44iZRJ8i7s0wkOgbnZqOvTa9hoiINIiqBZA0n7owK2gDov92VNFMhzuJKYEfIdYpLPJY\nBfwcsWp2R2Iwl/R/YZW1iIg0gKrOwkoLkiYAFxFT/opnn8wFhgFDiUHRctvnlGwTEZEGUfVZWO7+\nZTNbk5g1sUrRrqHEKtY5QFvR9rYy2wvbutTR0dHR0tLXGZayQtpgg/h/2rR6lkKkXjJ9cVZzEP1Q\nYF13P4dYeLUEeNjMdnH3e4nVvvcQgeXsNKd7FSKJ3pPAFCJFxkPp2HKLfDppaWlhxoy51ahOvxk+\nKtLpzHzkyV4/t729raHq15e6lKp33YYvjdmIM6tUhlrWrz/PS09Vo371qEcl9f58Vlt7e1v3B5VR\nzRbITcAEM7uXSLdwAvAP4Mo0SP4UMde/wyLh22SiS22sR7K4y4FrzGwyMXvr4CqWVUREeqlqASSl\nCTiwzK5dyxw7nlhNXPr8A0qPFRGRxqBUJiIikokCiIiIZKIAIiIimSiZYo01woyS/pKnuuRJXs5L\nXuqRZ2qBiIhIJgogIiKSiQKIiIhkogAiIiKZKICIiEgmCiA1NnzUpu/k+Gl2eapLnuTlvOSlHnmm\nACIiIpkogIiISCYKICIikokCiIiIZKIAIiIimSgXVo3lKb9PnupSycKFC5k+/YWy+0aMWJ+BAwfW\nuETdy8t5yUs98kwBRKQL06e/wAnn38bgYWt02j5/9qtcdNLejBy5cZ1KJlJ/CiAi3Rg8bA2GrL5O\nvYsh0nA0BiIiIpkogIiISCYKICIikokCSI3lKb9PnuqSJ3k5L3mpR54pgIiISCYKICIikokCiIiI\nZKJ1IFIXpSu8Z80awsyZ84DGXeEtIp0pgEhdaIW3SPNTAKmxPOX36WtdtMK7OvLyGctLPfJMYyAi\nIpJJ1VogZrYycBWwPjAIOAt4Cfgd8Ew67DJ3n2hmY4CjgMXAWe5+h5mtClwPtANzgdHu/lq1yisi\nIr1TzS6sQ4AZ7n6oma0OTAW+B4xz9wsKB5nZWsBxwChgVeB+M7sbOBqY6u5nmtmBwKnAiVUsr4iI\n9EI1A8hE4Kb0cyuwiAgSZmb7AM8SAWEbYIq7LwIWmdlzwObAjsB56fmTgNOqWFYREemlqo2BuPub\n7j7PzNqIYPId4EHgW+6+C/BP4AygDZhd9NS5wDBgKDCnZJuIiDSIqs7CMrMRwM3Ape5+o5kNc/dC\nsLgFuAS4jwgiBW3AG0TwaCvZ1q329rbuD6qnDTaI/6dNy/T0hqpfH+oya9aQivuGDx9S+3q2tgDL\n/377s5w1q1MfP2NZ9Xv96lSPShrqb69BVHMQfU3gLuAYd/9j2jzJzI5394eA3YGHiVbJ2WY2CFgF\n2AR4EpgC7Ak8BOxBBJpuzZgxt1/r0d+GL+0AYGaGcra3tzVU/fpSl8KiwUr7al3PSnXpr3LW8tz1\n5bxkVY361aMelTTa315/yxocq9kCGUt0O51uZqenbScCPzazRcDLwFGpm+tiYDLRpTbW3ReY2eXA\nNWY2GVgAHFzFsoqISC9VLYC4+wnACWV27VTm2PHA+JJtbwEHVKd0IiLSV1pIKCIimSiAiIhIJsqF\nVWN5yu+Tp7rkSV7OS17qkWdqgYiISCYKICIikokCiIiIZKIAIiIimSiAiIhIJgogNTZ81KYMH7Vp\nvYvRL/JUlzzJy3nJSz3yTAFEREQyUQAREZFMFEBERCQTBRAREclEAURERDJRLqway1N+nzzVJU/y\ncl7yUo88UwtEREQyUQAREZFMFEBERCQTBRAREclEAURERDJRAKmxPOX3yVNd8iQv5yUv9cgzBRAR\nEclEAURERDJRABERkUwUQEREJBMFEBERyUS5sGosT/l98lSXPMnLeclLPfJMLRAREclEAURERDKp\nWheWma0MXAWsDwwCzgKeBiYAS4EngWPdvcPMxgBHAYuBs9z9DjNbFbgeaAfmAqPd/bVqlVdERHqn\nmi2QQ4AZ7r4z8GngUmAcMDZtawH2MbO1gOOAHYBPAeeY2UDgaGBqOvZa4NQqllVERHqpmgFkInB6\n0fssArZ29/vStjuB3YGPAFPcfZG7zwGeAzYHdgQmpWMnpWNFRKRBVK0Ly93fBDCzNiKYnAr8qOiQ\nucAwYCgwu8L2OSXbml4ht08eZpjkqS55kpfzkpd65FlVp/Ga2QjgZuBSd7/BzH5YtHso8AYRJNqK\ntreV2V7Y1q329rbuD6qn1hYgezkbqn59qMusWUMq7hs+fEjt61mhLv1ZzprVqY+fsaz6/f3qVI9K\nGqUcjaSag+hrAncBx7j7H9Pmx8xsF3e/F9gDuAd4EDjbzAYBqwCbEAPsU4A9gYfSsffRAzNmzO3X\nevS34Us7AJiZoZzt7W0NVb++1GXmzHld7qt1PSvVpb/KWctz15fzklU16lePelTSaH97/S1rcKxm\nC2Qs0e10upkVxkJOAC5Og+RPATelWVgXA5OJsZKx7r7AzC4HrjGzycAC4OAqllVERHqpmmMgJxAB\no9SuZY4dD4wv2fYWcEBVCiciIn2mhYQiIpKJcmHVWJ5mlOSpLnmSl/OSl3rkmVogIiKSiQKIiIhk\nogAiIiKZKICIiEgmCiAiIpKJAkiNDR+16Ts5fppdnuqSJ3k5L3mpR54pgIiISCYKICIikokCiIiI\nZKIAIiIimSiAiIhIJsqFVWN5yu+Tp7rkSV7OS17qkWdqgYiISCYKICIikom6sESazMKFC5k+/YWy\n+0aMWJ+BAwfWuESyoup1ADGzoe4+pxqFEZHuTZ/+AiecfxuDh63Rafv82a9y0Ul7M3LkxnUqmaxo\nug0gZvZZ4KPA94EHgTXM7Ax3/0m1Cyci5Q0etgZDVl+n3sWQFVxPxkDOAK4CDiQCyPrA4dUsVJ7l\nKb9PnuqSJ3k5L3mpR571aBDd3f8B7AXc7u7zgJWrWioREWl4PQkgr5jZT4CPAJPMbBzwYnWLJSIi\nja4nAeSLRNfVrqn18WzaJiIiK7BuB9HdfY6ZLQEON7NzgLfcfW71iyb9SVM/RaS/9WQW1nnAOsAo\n4EfAl81sC3f/ZrULJ/1HUz9FpL/1ZB3Ip4CtgUfcfZaZfQJ4AlAAyaCe+X36e+qnchU1prycl7zU\nI896MgaypOTxoDLbRERkBdOTADIRuBEYbmbfACYDN1S1VCIi0vB6Moh+rpl9mpi6OwI43d1/V/WS\nidRQR0cHSxYv5vnnn+20/cUXy088EJGe58L6D3B74YGZ7ezu91WnSCK1t2TxYl6fM59Trnig0/bX\nX3qad6+7SZ1KJdLYejIL60ZiEP3fJbt268kbmNm2wLnuvpuZbUUEosJl3mXuPtHMxgBHAYuBs9z9\nDjNbFbgeaAfmAqPd/bWevKc0r6VLFle86q/2dOPW1gHLTTKYP/uVqr2fSLPrSQtkC2ATd+/1wLmZ\nnQx8CZiXNo0CLnD3C4qOWQs4Lu1bFbjfzO4GjgamuvuZZnYgcCpwYm/L0GgKuX3yMMOkGnV5e97r\njPvVTAYPe7nTdk037rm8fMbyUo8860kA+SuwMfCPDK//HLAfcF16PAp4v5ntQ7RCTgS2Aaa4+yJg\nkZk9B2wO7Aicl543CTgtw/tLE1KmWZHm0JMA8gfgSTN7mehiAuhw9w27e6K732xmGxRt+itwhbs/\nZmZjiUy/jwOzi46ZCwwDhgJzSrZ1q729rSeH1U9rC5C9nFmfN2vWkIr7hg8fku11+1CXrspTSeZy\n9sCiAb2/OWdvy9NfZe/uXA7o42csq35/vzrVo5JGKUcj6UkAOQv4GP2TQPEWdy8Ei1uAS4D7gOIz\n0wa8QQSPtpJt3Zoxo7GzrAxf2gHAzAzlbG9vy1y/mTPndbkvy+v2pS5dlaer51Tr/A5dsrTXz+lN\nefpy7sq9b1f7lvThvGTVn/Ur6Mvnq79Vo36NJGtw7EkAeRW43917/xe2vElmdry7PwTsDjxMJGo8\n28wGAavsDJbyAAARbUlEQVQAmwBPAlOAPYGHgD2IQCMiIg2iJwHkb8Bf0sD2orStw93P7MX7dKT/\nvwZcamaLgJeBo9x9npldTCxQbAXGuvsCM7scuMbMJgMLgIN78X4iIlJlPQkgL7Ks+6qlt2/g7tOA\nHdLPU4GdyhwzHhhfsu0t4IDevl+jy9OMkjzVJU/ycl7yUo8868lK9O8WPzazVuB91SqQiIg0h54s\nJDwOOBtYjWUtkKeBD1WxXCIi0uB6Mnfxf4AtgV8DGwJHUJTWREREVkw9CSCvuvs/ganAZu4+Afho\nVUslIiINrycB5E0z2424idTeZrY2sFZ1iyUiIo2uJwHkOGBv4E5gODH+8ZNqFirPho/a9J0cP80u\nT3XJk7ycl7zUI8+6DCBmdgywsbt/A3iAyMr7GhoDERFZ4VUMIGZ2CpEI8am0aRVgV+BC4JSql0xE\nRBpaVy2Q0cC+7u7p8RJ3fwG4HNi+6iUTEZGG1lUAWeLuxdnDzgZI9wVZUNVSiYhIw+sqgLSY2dDC\nA3e/CcDMhrEst5WIiKygulqJ/gsimeGXCynYzawNuDrtkwzylN8nT3XJk7ycl7zUI8+6CiDnAZcB\n/zGzp4hWxweJuwte0MXzRERkBVAxgLj7YuAoMzuTuO0swCNpIF1ERFZwPcnG+xLwUg3KIiIiTaQn\n9wMRkRJLlyzmxRcrN8ZHjFifgQMH1rBEIrWnACKSwdvzXmfcr2YyeNjLy+2bP/tVLjppb0aO3LgO\nJROpHQWQGivk9snDDJM81SWLwcPWYMjq69S7GMvJy3nJSz3yrCfJFEVERJajACIiIpkogIiISCYK\nICIikokCiIiIZKJZWDWWpxkleapLnuTlvOSlHnmmFoiIiGSiACIiIpkogIiISCYKICIikokCiIiI\nZFL1WVhmti1wrrvvZmYbAROApcCTwLHu3mFmY4CjgMXAWe5+h5mtClwPtANzgdHu/lq1y1ttecrv\nk6e65Elezkte6pFnVW2BmNnJwJXAoLTpAmCsu+8MtAD7mNlawHHADsCngHPMbCBwNDA1HXstcGo1\nyyoiIr1T7S6s54D9iGABsLW735d+vhPYHfgIMMXdF7n7nPSczYEdgUnp2EnpWBERaRBV7cJy95vN\nbIOiTS1FP88FhgFDgdkVts8p2dat9va2rMWtjdb4FWQtZ9bnzZo1pOK+4cOHZHvdPtSlq/JUkrmc\nPbBoQP9eS5Ura3+VvbtzOaCPn7Gs+v396lSPShqlHI2k1ivRlxb9PBR4gwgSxWemrcz2wrZuzZgx\nt++lrKLhSzsAmJmhnO3tbZnrN3PmvC73ZXndvtSlq/J09Zxqnd+hS5Z2f1AvlJa1L+eu3Gt3tW9J\nH85LVv1Zv4K+fL76WzXq10iyBsdaz8J6zMx2ST/vAdwHPAh81MwGmdkwYBNigH0KsGfJsSIi0iBq\n1QLpSP//D3BlGiR/CrgpzcK6GJhMBLSx7r7AzC4HrjGzycAC4OAalbWq8jSjJE91yZO8nJe81CPP\nqh5A3H0aMcMKd38W2LXMMeOB8SXb3gIOqHb5REQkGy0kFBGRTBRAREQkE90PRCQnli5ZzIsvvlB2\n34gR6zNw4MAal0jyTgFEpEEtXLiQ6dOXDwiVgsTb815n3K9mMnjYy522z5/9KhedtDcjR25clXLK\niksBpMbylN8nT3VpRNOnv8AJ59/G4GFrdNr++ktP8+51Nyn7nMHD1uDG33wXgCOPvLLaRawqfb4a\nnwKISAMbPGwNhqy+Tqdt82e/UqfSiHSmACJV1dtuGBFpHgogUlVZumFEpDkogEjV9Uc3jGYYiTQe\nBRBpCpphJNJ4FEBqLE8zSmpdl3ItGVles8++KsjT30peaSW6iIhkohaIrFAqzQrbbMniOpRGpLkp\ngMgKpdKssOvnvs2AlVauU6lEmpMCiKxwyo2ltLSqN1ekt/RXIyIimSiA1NjwUZu+k+On2eWpLnky\nfvwYxo8fU+9i9Jk+X41PXVgrOC3QE5GsFEBWcFqgJyJZKYCIFuiJSCYaAxERkUzUAskZpU8XkVpR\nAKmxauf3qWX6dOUqakzKhSW1ogCSQ7qLnYjUggKIiPTJwoULeeaZZ5g5c95y+zQVPN8UQET6Wbm1\nNbNmDWHmzHm5/EKt1G2qqeD5pwAi0s9WxLU1mgq+YlIAEamCRvpCVbYBqRYFkBor5PbJwwyTPNUl\nTwp5sAqzsZq1RaTPV+OrSwAxs0eB2enhP4FzgAnAUuBJ4Fh37zCzMcBRwGLgLHe/ow7FFWl6jdQi\nkvyoeQAxs1UA3H23om23AWPd/T4zuxzYx8weAI4DRgGrAveb2d3uvrDWZc6i0oK+oYsWMWAlNfxE\npPnV45tsC2Cwmf0+vf93gK3d/b60/07gk8ASYIq7LwIWmdlzwObAw3Uoc69VmpnyiznzeffQwXUq\nlYhI/6lHAHkTON/df25mGwOTSvbPBYYBQ1nWzVW8vWmU6zZobR1Qp9KIiPSvegSQZ4DnANz9WTN7\nHdiqaP9Q4A1gDtBWtL0NmNXdi7e3t3V3SE3MmjWk4r7WAa2Zy9nd87p6394aPnxI1+/X2tJtmfqz\nPJV0W84itShPV8qVdeHChUybNm25Y2fPnlGX8vRWV7/TPr1+Dz5ftdQo5Wgk9QgghxNdUcea2XuJ\nwHCXme3i7vcCewD3AA8CZ5vZIGAVYBNigL1LM2bMrVrBe6PcqlyAL+7/fc45ajtGZihne3tbt/Wr\n9L5ZzJw5r+v3e+iJ+L+LY/qzPF29R0/Pey3K0937l5b1+eef7df8Zb3JhdWb311Xr1GV1+/B56tW\nevK318yyBsd6BJCfA1ebWWHM43DgdeBKMxsIPAXclGZhXQxMJtLOj22WAXSR3lL+MmlGNQ8g7r4Y\nOLTMrl3LHDseGF/tMomISO/phlIiIpKJAoiIiGSiACIiIploSXSN3TDxNFa/cxBz/ub1LkqfKVdR\nYyrNhVUvfU3iqM9X41MAEZGqaNYkjtJzCiAiUjVK4phvGgMREZFMFEBERCQTBRAREclEYyA19k4u\nrHoXpB80wuwY3a51efWefdVfGuHzJV1TAJGm1kwzfSoFu0oBsNoUfKWvFECk6TXLTJ9KwS5r1t1q\nladS8K10l816BUCpPwWQPtIflfRGo2Xd7U3wrXSXzd4GQLV88kMBpI/6649KpBn0RwBspm5H6ZoC\nSD9otKtKabzxBumsWbodpWsKIDXWLLmwetLN0Mi5ihptvKGWGiUXVl818udLggKIlJWHbga1DLNR\n6016SgFEKlI3w4ppRW69Se8ogIjIctR6k55QKhMREclELRARaQilYy9DFy0C4Pnnn9X6kAalAFJj\nyoUl1dass6+WG3vZ41QA5p9/W9NM3FjRKIDUmFbhilSmiRvNRQGkxvIwPVZEBBRA6iKPV1nKCSay\n4slVAPncmHNYsmRpp23zZ77AjVeOq1OJVhzKCSaNotLFDKibuL/lKoAsGfrB5battHhpmSOlGrR2\nQKqht+OGlS5m1E3c/3IVQJrBLZMuorV1AGOOuqreRekz5SpqTHnJhVWox967H1123HDerJc56Ytb\ns95663fa/uKLL5S9mNEElv6nACIiDa9S63bcr6b2OOVKpQkslQIRKLB0p6EDiJm1ApcBmwMLgCPd\n/fn6lmrFVnwVV7zQS4PlUg+97TbtTSAqDiyzZg1h5sx57+xTYAkNHUCAzwED3X0HM9sWGJe2SZ0U\nX8XdMG8BAKdc8YAGy6WpZQ0spVa0wNLoAWRHYBKAu//VzD5c5/IIy/7YWloHADBk9XU0WC65pMDS\ntUYPIEOBOUWPl5hZq7uXnVrVMvvvLCmZdbXwjRd4/vlnq1bAF198gfmzX11u+1tzZwIty23vWLqU\npcC8Wf/utH3+7Fe77QYqbUb3R3n6sr1j6RIg6lKN16/l9krnpbevU886FLYXn5dGKE/W7YV6NEp5\nirev2vbu5bYvePMNzrryblYZMrzT9rfnzeTUMZ8oG1iafUZYS0dHR73LUJGZjQMecPeJ6fF0dx9R\n52KJiAiNn859CrAngJltB/ytvsUREZGCRu/CugX4hJlNSY8Pr2dhRERkmYbuwhIRkcbV6F1YIiLS\noBRAREQkEwUQERHJRAFEREQyafRZWN3KY74sM1sZuApYHxgEnAU8DUwAlgJPAse6e1PPgDCzNYBH\ngI8T9ZpATupnZqcAnwVWBn5CTEmfQA7ql/7mxgPvJ+ozBlhCk9cvpUs61913M7ONKFMfMxsDHAUs\nBs5y9zvqVuBeKqnflsDFxHlbABzm7q/2tn55aIG8ky8L+F8iX1azOwSY4e47A58GLiXqNTZtawH2\nqWP5+iwFyZ8BbxL1uYCc1M/MdgW2T5/JXYENydf5+ySwmrvvBJwJ/IAmr5+ZnQxcSVywQZnPo5mt\nBRwH7AB8CjjHzJoiP0mZ+l0IfN3ddwNuBr5tZmvSy/rlIYB0ypcF5CFf1kTg9PRzK7AI2Nrd70vb\n7gR2r0fB+tH5wOVAIaFQnur3SeAJM/stcDtwGzAqR/V7CxhmZi3AMGAhzV+/54D9WJa7pNzn8SPA\nFHdf5O5z0nM2r3lJsymt30HuXliYvTJxTrehl/XLQwApmy+rXoXpD+7+prvPM7M2IpicSudzNY/4\nw21KZvZlooV1V9rUQuekQ01dP6AdGAV8Afga8EvyVb8pwCrAP4hW5MU0ef3c/Wai26aguD5zifoM\nBWaX2d7wSuvn7v8FMLMdgGOBH5Ohfk39RZvMAdqKHldMtthMzGwE8AfgWne/geiLLWgD3qhLwfrH\n4USGgT8CWwLXEF+6Bc1ev9eAu9x9sbs/A7xN5z/EZq/fycSVqhHn71riKrag2esHnf/ehhL1Kf2u\naQNm1bJQ/cnMDiR6AfZ099fJUL88BJDc5ctKfZF3ASe7+4S0+TEz2yX9vAdwX7nnNgN338Xdd039\nr48DhwGT8lI/4H5i7Aozey8wGLgnR/VbjWWt/lnEZJzcfD6TcvV5EPiomQ0ys2HAJsQAe9Mxsy8R\nLY9d3X1a2tzr+jX9LCzymS9rLHHFerqZFcZCTgAuToNaTwE31atwVdAB/A9wZR7q5+53mNnOZvYg\ncZF2DDCNnNSPGL+62swmEy2PU4jZdHmoX2Hm2HKfxzQL62JgMnFex7r7wjqVM6uO1MV/EfACcLOZ\nAfzJ3b/X2/opF5aIiGSShy4sERGpAwUQERHJRAFEREQyUQAREZFMFEBERCQTBRAREckkD+tARKrO\nzL5AJOtcibjwutbdf1TfUonUl1ogIt0ws3WAHwGfcPctge2Bg8zss/UtmUh9qQUi0r33ECuuVwNm\nufubZjYaeNvMdieCSyuxsvdgIkX9hcDHiJXN17n7D1Oa9x+mY58Avk7cy+ZDwADgPHe/0cw2J5IU\nrkTk0Trc3Z+rVWVFekotEJFuuPtU4Fbgn2b2VzM7l/jCfwm4nrgZz+ZEHrbRRAbedYHNiBTZnzez\nPdPLbQzs5u6HA6cBD7v7h4FdgO+Y2fuAE4Fx7v4R4BJguxpVVaRXlMpEpIfMbG3iRjufIm6YdAZx\nX4VRJcdNJMZIbk+PjyfuLnkb0crYLm1/GFiVuJ8GRNbX44lU6ZcCv0v/bstDhmnJH3VhiXTDzPYC\nBrv7ROI2pxPM7Eiiu6r4uKFEEGil8/0kWln2t/ZWyfZD3P3x9Py1gNfdfZGZ/QX4DNEa2ZO4zahI\nQ1EXlkj33iRu77keQLoT34eIDLTvMbNN0nHfBr5K3MdltJm1mtlgItD8gc5BhbTtmPSaawOPASPM\n7JfANu5+BXFnyq2rWTmRrBRARLrh7n8i7v39OzN7GniaCAanAIcC15rZVOADwDnEAPhLwFTgUeBW\nd781vVxxn/H3gFXN7AngHuL+L/8EzgXGmtkjROr0b1S3hiLZaAxEREQyUQtEREQyUQAREZFMFEBE\nRCQTBRAREclEAURERDJRABERkUwUQEREJJP/D4OlQ23p5LszAAAAAElFTkSuQmCC\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10e324390>"
+       ]
+      }
+     ],
+     "prompt_number": 68
+    },
+    {
+     "cell_type": "heading",
+     "level": 1,
+     "metadata": {},
+     "source": [
+      "Super Agressive Player Data for 25,000 Games"
+     ]
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "super_agro_player = SuperAgro()\n",
+      "game = Game(player)\n",
+      "\n",
+      "game.play_game(super_agro_player)"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "pyout",
+       "prompt_number": 69,
+       "text": [
+        "70"
+       ]
+      }
+     ],
+     "prompt_number": 69
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "super_agro_player_list = [game.play_game(super_agro_player) for _ in range(25000)]"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [],
+     "prompt_number": 70
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "plt.hist(super_agro_player_list, bins=50)\n",
+      "plt.xlabel(\"Scores\")\n",
+      "plt.ylabel(\"Games\")\n",
+      "\n",
+      "\n",
+      "ymin, ymax = plt.ylim()\n",
+      "mean = st.mean(super_agro_player_list)\n",
+      "stdev = st.pstdev(super_agro_player_list)\n",
+      "plt.vlines(mean, ymin, ymax, color=\"red\")\n",
+      "plt.vlines([mean - 2 * stdev, mean - stdev, mean + stdev, mean + 2 * stdev], ymin, ymax, linestyles=\"dashed\", color=\"red\")\n",
+      "plt.title(\"Player Holds @ 20+ Points\\n Mean: {} \\n Standard Deviation: {}\".format(mean, stdev))\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEwCAYAAACZoyciAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nIiIimfx/CCqlywxHU9AAAAAASUVORK5CYII=\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10e5f4e80>"
+       ]
+      }
+     ],
+     "prompt_number": 71
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "plt.boxplot([standard_player_list, five_roller_list, seven_roller_list, agro_player_list, super_agro_player_list])\n",
+      "ymin, ymax = plt.ylim()\n",
+      "plt.ylim(ymin - 30, ymax + 30)\n",
+      "plt.title(\"Game Scores\")\n",
+      "plt.ylabel(\"Scores\")\n",
+      "plt.xticks(range(1,6), [\"Standard\", \"Five Rolls\", \"Seven Rolls\", \"Agressive\", \"Super Agressive\"])\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAYYAAAEKCAYAAAAW8vJGAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10e4fc2b0>"
+       ]
+      }
+     ],
+     "prompt_number": 73
+    },
+    {
+     "cell_type": "code",
+     "collapsed": false,
+     "input": [
+      "sb.violinplot([standard_player_list, five_roller_list, seven_roller_list, agro_player_list, super_agro_player_list])\n",
+      "sb.despine(offset=10, trim=True);\n",
+      "plt.ylabel(\"score\")\n",
+      "plt.xticks(range(1,6), [\"Standard\", \"Five Rolls\", \"Seven Rolls\", \"Agressive\", \"Super Agressive\"])\n",
+      "plt.show()"
+     ],
+     "language": "python",
+     "metadata": {},
+     "outputs": [
+      {
+       "metadata": {},
+       "output_type": "display_data",
+       "png": "iVBORw0KGgoAAAANSUhEUgAAAZAAAAEMCAYAAADqG+D0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\ngg==\n",
+       "text": [
+        "<matplotlib.figure.Figure at 0x10e342e80>"
+       ]
+      }
+     ],
+     "prompt_number": 74
+    }
+   ],
+   "metadata": {}
+  }
+ ]
+}
\ No newline at end of file
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..7e52311
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,4 @@
+ipython[all]
+matplotlib
+seaborn
+numpy
\ No newline at end of file