Linear Regression (penguins).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "83edbedc",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7c5da48",
   "metadata": {},
   "source": [
    "## Importing included dataset in seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b3fbbc01",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rowid</th>\n",
       "      <th>species</th>\n",
       "      <th>island</th>\n",
       "      <th>bill_length_mm</th>\n",
       "      <th>bill_depth_mm</th>\n",
       "      <th>flipper_length_mm</th>\n",
       "      <th>body_mass_g</th>\n",
       "      <th>sex</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.1</td>\n",
       "      <td>18.7</td>\n",
       "      <td>181.0</td>\n",
       "      <td>3750.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>39.5</td>\n",
       "      <td>17.4</td>\n",
       "      <td>186.0</td>\n",
       "      <td>3800.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>40.3</td>\n",
       "      <td>18.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>3250.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Adelie</td>\n",
       "      <td>Torgersen</td>\n",
       "      <td>36.7</td>\n",
       "      <td>19.3</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3450.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   rowid species     island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
       "0      1  Adelie  Torgersen            39.1           18.7              181.0   \n",
       "1      2  Adelie  Torgersen            39.5           17.4              186.0   \n",
       "2      3  Adelie  Torgersen            40.3           18.0              195.0   \n",
       "3      4  Adelie  Torgersen             NaN            NaN                NaN   \n",
       "4      5  Adelie  Torgersen            36.7           19.3              193.0   \n",
       "\n",
       "   body_mass_g     sex  year  \n",
       "0       3750.0    male  2007  \n",
       "1       3800.0  female  2007  \n",
       "2       3250.0  female  2007  \n",
       "3          NaN     NaN  2007  \n",
       "4       3450.0  female  2007  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url='https://gist.githubusercontent.com/slopp/ce3b90b9168f2f921784de84fa445651/raw/4ecf3041f0ed4913e7c230758733948bc561f434/penguins.csv'\n",
    "data=pd.read_csv(url)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62afe9f8",
   "metadata": {},
   "source": [
    "## cleaning and subsetting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a4857e3b",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rowid</th>\n",
       "      <th>species</th>\n",
       "      <th>island</th>\n",
       "      <th>bill_length_mm</th>\n",
       "      <th>bill_depth_mm</th>\n",
       "      <th>flipper_length_mm</th>\n",
       "      <th>body_mass_g</th>\n",
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       "      <th>year</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>276</th>\n",
       "      <td>277</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>46.5</td>\n",
       "      <td>17.9</td>\n",
       "      <td>192.0</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>278</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>50.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>196.0</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>278</th>\n",
       "      <td>279</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>51.3</td>\n",
       "      <td>19.2</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3650.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>279</th>\n",
       "      <td>280</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>45.4</td>\n",
       "      <td>18.7</td>\n",
       "      <td>188.0</td>\n",
       "      <td>3525.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>280</th>\n",
       "      <td>281</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>52.7</td>\n",
       "      <td>19.8</td>\n",
       "      <td>197.0</td>\n",
       "      <td>3725.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
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       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>340</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>55.8</td>\n",
       "      <td>19.8</td>\n",
       "      <td>207.0</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>341</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>43.5</td>\n",
       "      <td>18.1</td>\n",
       "      <td>202.0</td>\n",
       "      <td>3400.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>341</th>\n",
       "      <td>342</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>49.6</td>\n",
       "      <td>18.2</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3775.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>342</th>\n",
       "      <td>343</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>50.8</td>\n",
       "      <td>19.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>4100.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>343</th>\n",
       "      <td>344</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>50.2</td>\n",
       "      <td>18.7</td>\n",
       "      <td>198.0</td>\n",
       "      <td>3775.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "<p>68 rows × 9 columns</p>\n",
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      ],
      "text/plain": [
       "     rowid    species island  bill_length_mm  bill_depth_mm  \\\n",
       "276    277  Chinstrap  Dream            46.5           17.9   \n",
       "277    278  Chinstrap  Dream            50.0           19.5   \n",
       "278    279  Chinstrap  Dream            51.3           19.2   \n",
       "279    280  Chinstrap  Dream            45.4           18.7   \n",
       "280    281  Chinstrap  Dream            52.7           19.8   \n",
       "..     ...        ...    ...             ...            ...   \n",
       "339    340  Chinstrap  Dream            55.8           19.8   \n",
       "340    341  Chinstrap  Dream            43.5           18.1   \n",
       "341    342  Chinstrap  Dream            49.6           18.2   \n",
       "342    343  Chinstrap  Dream            50.8           19.0   \n",
       "343    344  Chinstrap  Dream            50.2           18.7   \n",
       "\n",
       "     flipper_length_mm  body_mass_g     sex  year  \n",
       "276              192.0       3500.0  female  2007  \n",
       "277              196.0       3900.0    male  2007  \n",
       "278              193.0       3650.0    male  2007  \n",
       "279              188.0       3525.0  female  2007  \n",
       "280              197.0       3725.0    male  2007  \n",
       "..                 ...          ...     ...   ...  \n",
       "339              207.0       4000.0    male  2009  \n",
       "340              202.0       3400.0  female  2009  \n",
       "341              193.0       3775.0    male  2009  \n",
       "342              210.0       4100.0    male  2009  \n",
       "343              198.0       3775.0  female  2009  \n",
       "\n",
       "[68 rows x 9 columns]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset=data[data['species']=='Chinstrap']\n",
    "subset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "dafbc3b6",
   "metadata": {},
   "outputs": [
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     "name": "stderr",
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     "text": [
      "C:\\Users\\lenovo\\anaconda3\\lib\\site-packages\\seaborn\\axisgrid.py:88: UserWarning: The figure layout has changed to tight\n",
      "  self._figure.tight_layout(*args, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x1e3f79aefa0>"
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     "execution_count": 25,
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\n",
      "text/plain": [
       "<Figure size 1500x1500 with 42 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(subset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "801871b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rowid</th>\n",
       "      <th>species</th>\n",
       "      <th>island</th>\n",
       "      <th>bill_length_mm</th>\n",
       "      <th>bill_depth_mm</th>\n",
       "      <th>flipper_length_mm</th>\n",
       "      <th>body_mass_g</th>\n",
       "      <th>sex</th>\n",
       "      <th>year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>277</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>46.5</td>\n",
       "      <td>17.9</td>\n",
       "      <td>192.0</td>\n",
       "      <td>3500.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>278</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>50.0</td>\n",
       "      <td>19.5</td>\n",
       "      <td>196.0</td>\n",
       "      <td>3900.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>279</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>51.3</td>\n",
       "      <td>19.2</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3650.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>280</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>45.4</td>\n",
       "      <td>18.7</td>\n",
       "      <td>188.0</td>\n",
       "      <td>3525.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>281</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>52.7</td>\n",
       "      <td>19.8</td>\n",
       "      <td>197.0</td>\n",
       "      <td>3725.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>340</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>55.8</td>\n",
       "      <td>19.8</td>\n",
       "      <td>207.0</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>341</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>43.5</td>\n",
       "      <td>18.1</td>\n",
       "      <td>202.0</td>\n",
       "      <td>3400.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>342</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>49.6</td>\n",
       "      <td>18.2</td>\n",
       "      <td>193.0</td>\n",
       "      <td>3775.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>343</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>50.8</td>\n",
       "      <td>19.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>4100.0</td>\n",
       "      <td>male</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>344</td>\n",
       "      <td>Chinstrap</td>\n",
       "      <td>Dream</td>\n",
       "      <td>50.2</td>\n",
       "      <td>18.7</td>\n",
       "      <td>198.0</td>\n",
       "      <td>3775.0</td>\n",
       "      <td>female</td>\n",
       "      <td>2009</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    rowid    species island  bill_length_mm  bill_depth_mm  flipper_length_mm  \\\n",
       "0     277  Chinstrap  Dream            46.5           17.9              192.0   \n",
       "1     278  Chinstrap  Dream            50.0           19.5              196.0   \n",
       "2     279  Chinstrap  Dream            51.3           19.2              193.0   \n",
       "3     280  Chinstrap  Dream            45.4           18.7              188.0   \n",
       "4     281  Chinstrap  Dream            52.7           19.8              197.0   \n",
       "..    ...        ...    ...             ...            ...                ...   \n",
       "63    340  Chinstrap  Dream            55.8           19.8              207.0   \n",
       "64    341  Chinstrap  Dream            43.5           18.1              202.0   \n",
       "65    342  Chinstrap  Dream            49.6           18.2              193.0   \n",
       "66    343  Chinstrap  Dream            50.8           19.0              210.0   \n",
       "67    344  Chinstrap  Dream            50.2           18.7              198.0   \n",
       "\n",
       "    body_mass_g     sex  year  \n",
       "0        3500.0  female  2007  \n",
       "1        3900.0    male  2007  \n",
       "2        3650.0    male  2007  \n",
       "3        3525.0  female  2007  \n",
       "4        3725.0    male  2007  \n",
       "..          ...     ...   ...  \n",
       "63       4000.0    male  2009  \n",
       "64       3400.0  female  2009  \n",
       "65       3775.0    male  2009  \n",
       "66       4100.0    male  2009  \n",
       "67       3775.0  female  2009  \n",
       "\n",
       "[68 rows x 9 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subset.reset_index(inplace=True, drop=True)\n",
    "subset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ecf757c9",
   "metadata": {},
   "source": [
    "## modelling data for model ols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f1931db7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>bill_depth_mm</th>\n",
       "      <th>flipper_length_mm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>17.9</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>19.5</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>19.2</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>18.7</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>19.8</td>\n",
       "      <td>197.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>19.8</td>\n",
       "      <td>207.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>18.1</td>\n",
       "      <td>202.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>18.2</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>19.0</td>\n",
       "      <td>210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>18.7</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    bill_depth_mm  flipper_length_mm\n",
       "0            17.9              192.0\n",
       "1            19.5              196.0\n",
       "2            19.2              193.0\n",
       "3            18.7              188.0\n",
       "4            19.8              197.0\n",
       "..            ...                ...\n",
       "63           19.8              207.0\n",
       "64           18.1              202.0\n",
       "65           18.2              193.0\n",
       "66           19.0              210.0\n",
       "67           18.7              198.0\n",
       "\n",
       "[68 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "olsdata=subset[['bill_depth_mm','flipper_length_mm']]\n",
    "olsdata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "742144d8",
   "metadata": {},
   "source": [
    "## formula  (Y ~ X)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d6c800e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "olsf= \"flipper_length_mm ~ bill_depth_mm\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b45abcd6",
   "metadata": {},
   "source": [
    "## constructing model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2a765703",
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.formula.api import ols"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6d8bfacc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>OLS Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>    <td>flipper_length_mm</td> <th>  R-squared:         </th> <td>   0.337</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>                   <td>OLS</td>        <th>  Adj. R-squared:    </th> <td>   0.327</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>             <td>Least Squares</td>   <th>  F-statistic:       </th> <td>   33.48</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>             <td>Sat, 30 Sep 2023</td>  <th>  Prob (F-statistic):</th> <td>2.16e-07</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>                 <td>14:37:08</td>      <th>  Log-Likelihood:    </th> <td> -215.62</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>No. Observations:</th>      <td>    68</td>       <th>  AIC:               </th> <td>   435.2</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Residuals:</th>          <td>    66</td>       <th>  BIC:               </th> <td>   439.7</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Df Model:</th>              <td>     1</td>       <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Covariance Type:</th>      <td>nonrobust</td>     <th>                     </th>     <td> </td>   \n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "        <td></td>           <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Intercept</th>     <td>  128.6967</td> <td>   11.623</td> <td>   11.073</td> <td> 0.000</td> <td>  105.492</td> <td>  151.902</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>bill_depth_mm</th> <td>    3.6441</td> <td>    0.630</td> <td>    5.786</td> <td> 0.000</td> <td>    2.387</td> <td>    4.902</td>\n",
       "</tr>\n",
       "</table>\n",
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "  <th>Omnibus:</th>       <td> 1.350</td> <th>  Durbin-Watson:     </th> <td>   1.994</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Prob(Omnibus):</th> <td> 0.509</td> <th>  Jarque-Bera (JB):  </th> <td>   0.837</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Skew:</th>          <td>-0.255</td> <th>  Prob(JB):          </th> <td>   0.658</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Kurtosis:</th>      <td> 3.190</td> <th>  Cond. No.          </th> <td>    303.</td>\n",
       "</tr>\n",
       "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                            OLS Regression Results                            \n",
       "==============================================================================\n",
       "Dep. Variable:      flipper_length_mm   R-squared:                       0.337\n",
       "Model:                            OLS   Adj. R-squared:                  0.327\n",
       "Method:                 Least Squares   F-statistic:                     33.48\n",
       "Date:                Sat, 30 Sep 2023   Prob (F-statistic):           2.16e-07\n",
       "Time:                        14:37:08   Log-Likelihood:                -215.62\n",
       "No. Observations:                  68   AIC:                             435.2\n",
       "Df Residuals:                      66   BIC:                             439.7\n",
       "Df Model:                           1                                         \n",
       "Covariance Type:            nonrobust                                         \n",
       "=================================================================================\n",
       "                    coef    std err          t      P>|t|      [0.025      0.975]\n",
       "---------------------------------------------------------------------------------\n",
       "Intercept       128.6967     11.623     11.073      0.000     105.492     151.902\n",
       "bill_depth_mm     3.6441      0.630      5.786      0.000       2.387       4.902\n",
       "==============================================================================\n",
       "Omnibus:                        1.350   Durbin-Watson:                   1.994\n",
       "Prob(Omnibus):                  0.509   Jarque-Bera (JB):                0.837\n",
       "Skew:                          -0.255   Prob(JB):                        0.658\n",
       "Kurtosis:                       3.190   Cond. No.                         303.\n",
       "==============================================================================\n",
       "\n",
       "Notes:\n",
       "[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.\n",
       "\"\"\""
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "obj = ols(formula =olsf, data=olsdata)\n",
    "model=obj.fit()\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "646d81b9",
   "metadata": {},
   "source": [
    "## seeing models prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "295f620f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     193.926443\n",
       "1     199.757037\n",
       "2     198.663801\n",
       "3     196.841740\n",
       "4     200.850273\n",
       "         ...    \n",
       "63    200.850273\n",
       "64    194.655267\n",
       "65    195.019679\n",
       "66    197.934976\n",
       "67    196.841740\n",
       "Length: 68, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Xval=olsdata['bill_depth_mm']\n",
    "fittedval=model.predict(Xval)\n",
    "fittedval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "027bc44a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     192.0\n",
       "1     196.0\n",
       "2     193.0\n",
       "3     188.0\n",
       "4     197.0\n",
       "      ...  \n",
       "63    207.0\n",
       "64    202.0\n",
       "65    193.0\n",
       "66    210.0\n",
       "67    198.0\n",
       "Name: flipper_length_mm, Length: 68, dtype: float64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Yval=olsdata['flipper_length_mm']\n",
    "Yval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "e3cd0da9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>flipper_length_mm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>193.926443</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>199.757037</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>198.663801</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>196.841740</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200.850273</td>\n",
       "      <td>197.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>200.850273</td>\n",
       "      <td>207.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>194.655267</td>\n",
       "      <td>202.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>195.019679</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>197.934976</td>\n",
       "      <td>210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>196.841740</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             0  flipper_length_mm\n",
       "0   193.926443              192.0\n",
       "1   199.757037              196.0\n",
       "2   198.663801              193.0\n",
       "3   196.841740              188.0\n",
       "4   200.850273              197.0\n",
       "..         ...                ...\n",
       "63  200.850273              207.0\n",
       "64  194.655267              202.0\n",
       "65  195.019679              193.0\n",
       "66  197.934976              210.0\n",
       "67  196.841740              198.0\n",
       "\n",
       "[68 rows x 2 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.concat([fittedval,Yval], axis=1)\n",
    "df\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "2572474b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>predicted_val</th>\n",
       "      <th>observed_val</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>193.926443</td>\n",
       "      <td>192.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>199.757037</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>198.663801</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>196.841740</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>200.850273</td>\n",
       "      <td>197.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>200.850273</td>\n",
       "      <td>207.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>194.655267</td>\n",
       "      <td>202.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>195.019679</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>197.934976</td>\n",
       "      <td>210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>196.841740</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>68 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    predicted_val  observed_val\n",
       "0      193.926443         192.0\n",
       "1      199.757037         196.0\n",
       "2      198.663801         193.0\n",
       "3      196.841740         188.0\n",
       "4      200.850273         197.0\n",
       "..            ...           ...\n",
       "63     200.850273         207.0\n",
       "64     194.655267         202.0\n",
       "65     195.019679         193.0\n",
       "66     197.934976         210.0\n",
       "67     196.841740         198.0\n",
       "\n",
       "[68 rows x 2 columns]"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns=['predicted_val', 'observed_val']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "d2bf0ec0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.scatterplot(x='predicted_val', y='observed_val', data=df, color='blue', label='Observed')\n",
    "sns.scatterplot(x='predicted_val', y='predicted_val', data=df, color='red', label='Predicted')\n",
    "\n",
    "plt.xlabel('Predicted Values')\n",
    "plt.ylabel('Observed Values')\n",
    "plt.title('Predicted vs Observed Values')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "65f0ca09",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FPseOHdPu3bvdP+fm5ionJ0eJiYlq06aN7rvvPv3+979X586d1b59ez388MNq2bKlRo8ebV6lAcCGKob4gXBjqcBn48aNuuKKK9w/33///ZKkCRMmaNmyZfrNb36jn3/+WbfffruOHDmiSy+9VFlZWYqLYwUBAACQHIZhkELzLEVFRXI6nXK5XEpISDC7OiFTWmbQLQ0AsCxfr9+W6vFBcLChIADALiJmVRf8w4aCAAA7IfCxMTYUBADYDYGPjbGhIADAbgh8bIwNBQEAdkPgY2NsKAgAsBsCHxur2FDQ26J1h8pXd7GhIAAgUhD42BgbCgIA7IbAx+bYUBAAYCckMAQbCgIAbIPAB5LYUBAAYA8MdQEAANsg8AEAALZB4AMAAGyDwAcAANgGgQ8AALANAh8AAGAbBD4AAMA2CHwAAIBtkMAQQJVKywyyeQOIOAQ+ACrJ2pavOau/Ur6r2H2shTNOmSPT2L8NgKUx1AXAQ9a2fGUs3+QR9EhSgatYGcs3KWtbvkk1A4C6I/AB4FZaZmjO6q9kVPFcxbE5q79SaVlVJQAg/BH4AHDbkHu4Uk/P2QxJ+a5ibcg9HLpKAUAAEfgAcDt41HvQ4085AAg3BD4A3JIbxwW0HACEGwIfAG592yeqhTNO3hatO1S+uqtv+8RQVgsAAobAB4BbdJRDmSPTJKlS8FPxc+bINPL5ALAsAh8AHoZ1a6FF43orxek5nJXijNOicb3J4wPA0khgCKCSYd1aaHBaCpmbAUQcAh8AVYqOcii9Y1OzqwEAAUXgA6BK7NUFIBIR+CDicMGuO/bqQl3xPUS4IvBBROGCXXcVe3WduylFxV5dTHBGTcz+HhJ0oToOwzDYdOcsRUVFcjqdcrlcSkhIMLs6qAVvF+yK0x0X7JqVlhm6dP4HXretcKh8ddcnDw3iQoIqmf09NDvognl8vX6znB0Rgc01A4O9ulAXZn8PK4Kuc/+GK3ors7blB+V9YS0EPogIXLADg726UBdmfg/NDrrsrLTMUPaeQr2V84Oy9xSG/f8xc3wQEbhgBwZ7dfmOeSSVmfk9rE3QRZqGwLHi0CKBDyICF+zAqNirq8BVXOWdc8UcH7vv1WXFk30omPk95OYn9Ky6EIKhLkQENtcMDPbqqhnzSLwz83vIzU9oWXlokcAHEYELduCwV5d3Vj7Zh4KZ30NufkLLyvMqGepCxKi4YJ87BJHCEEStsVdX1ZhHUjOzvocVQVfG8k1ySB7BKTc/gWfloUUCHwSNGZM/uWAHDnt1VWblk30omfU95OYndKw8tEjgg6Awc/InF2wEi5VP9qFm1veQm5/QsPJCCOb4IOCY/IlIxTwSa6gIukb1aqX0jk0JeoLAyvMqCXwQUEz+RCSz8skeCDSrLoRgqAsBxeRPRDrmkQBnWHFoMaICn9mzZ2vOnDkex7p06aIdO3aYVCP7YfIn7MCKJ3sgWKw2rzKiAh9JuvDCC/Wvf/3L/XO9ehHXxLDG5E+EkpnbRljtZA+gXMRFBfXq1VNKSorZ1bAtK8/0h7WYvW0Ee3UB1hRxgc+uXbvUsmVLxcXFKT09XfPmzVObNm3MrpZtkEQMoWD2HkFmB10A/BdRq7r69eunZcuWKSsrS4sWLVJubq4uu+wyHT161OvvlJSUqKioyOOBurHqTH9Yg9krB0nXAFibwzCMiF1XfOTIEbVt21ZPPvmkJk2aVGWZqiZES5LL5VJCQkKwqxjRGApAMGTvKdTY59bXWO6fU34R8Dk4pWWGLp3/gdeVixVDuZ88NIi/dSDEioqK5HQ6a7x+R1SPz7maNGmi888/X7t37/ZaZubMmXK5XO5HXl5eCGsY2UgiFhilZYay9xTqrZwflL2n0PY5kMxcOWjljRkBlIu4OT5nO3bsmPbs2aPx48d7LRMbG6vY2NgQ1so+6PGpO+aSVGbmykHSNQDWF1GBz4MPPqiRI0eqbdu22r9/vzIzMxUdHa2xY8eaXTXb4YJdd2ZP4DVTdUGzmSsHSdcAWF9EBT7ff/+9xo4dq8LCQiUlJenSSy/V+vXrlZSUZHbVbMXOF+xAqWkCr0PlE3gHp6VEXC9aTUGzmSsHSdcAWF9EzfF5+eWXtX//fpWUlOj777/Xyy+/rI4dO5pdLVsxe8VNpLDrXBJfV0yZtXKQvboA64uoHh+Yj726AsOOc0lq28tl1rYR7NUFWBuBDwLKjhfsYLDjXBJ/gmazto1gry7Augh8EFB2vGAHgx3nklgtaGavLsCaImqOD8xXccH2dt/rUPlE1Ui6YAeDHeeSEDQj1MiRZU/0+CCg2KsrcOw2l8SOvVwwDyk37Cuit6zwh68pr1E9TiqBY6dEkBWruqSqg2ZSISAQvKXc4O/M2ny9fhP4nIPAJ3DsdMFG4BA0I5jYby1y+Xr9ZqgLQcPkT/iDFVMIJn9WD3ITF1kIfACEHYJmBEttVw/SAxl5WNUFALCN2qwe9DWTOKyFwAcAYBu+pty4uO15bL8ToQh8ACBMkFcm+HzNkfXF3p9suV+eHTDHBwDCAHNJQseXHFlv5fzg02uFSyZx+I7ABwBM5i2vTMVcEvLKBF5NqwfJJB65CHwsiuWVQGSo7a70CJzqVg+SSTxyEfhYEF3iQOTwJ68Mgo/tdyIXk5sthuWVQGSx2q70dlIxFyjF6TmcleKMY/jRwujxsRC6xIHIw1wS35g1vE8m8chD4GMhdIkDkYe5JDUze3ifTOKRhaEuC6FLHIg8vuaVsWsPA8P7CDQCHwuhSxyITMwlqVpNw/sS2ZNRewx1WQhd4kDkYi5JZQzvIxjo8bEQusRRHbY7QKRheB/BQI+PxfiSah32Y/bkTxJq1p3Zn2E4YngfweAwDIPbwrMUFRXJ6XTK5XIpISHB7Op4xYUGFbxtd1Dx1xDsOSJcsOvO7M8wXJWWGbp0/gc1Du9/8tAgzn/w+frNUBdgYWZP/mTFTd2Z/RmGM4b3EQwMdVkQd9ioYObkTxJqBgYTeKsXzOF9es7ticDHYtjFGWczc/InF+zAYAJvzYKx4o0bSPtiqMtC6BLHucyc/MkFOzCYwOubiuzJo3q1UnrHpnUOehiitS8CHwupzR027KEit5O3S4BD5XexwcjtxAU7MMz8DO2IG0gQ+FgId9g4l5mTP7lgBwYTeEOLG0gQ+FgId9ioilnbHXDBDhy2rAgdbiDB5GYLYcsK39hxpYZZ2x2QUDNw2LIiNLiBBIGPhVTcYWcs3ySH5BH8cIddzs4rNSomf4ZapF2wzQyczfoM7YQbSJC5+RxWyNxs54t7deye/daOPV2BxnfLHirOFVLVN5CRfq6IVL5evwl8zmGFwEfiIneuitT23iYtRnpqey7YdWf3wNlu+M5EHgIfP1kl8IGn7D2FGvvc+hrL/XPKLyJuKIELdt3ZPXA2k5k3cdxARhZfr9/M8UFEsOtKDbaNCAyyUJvD7F4X5lTZE8vZERHsulKDnCSBYdfA2UxkT4ZZCHwQEeyaTI8LdmDYNXA2C9mTYSYCH0QEuybT44IdGHYNnM1CTyXMROCDiGHH7LdcsAPDroGzWeiphJmY3IyIEmnJ9GpCUsvAIQt16NBTCTOxnP0cLGeHFZm9OiaSsMQ5+CrSB9SUPZn0AagN8vj4yczAhxMu6oK/H1gJ2ZMRaAQ+fjIr8OGOHYDdcN5DIBH4+MmMwIfMuwDsip5KBIqv1++IXNW1cOFCtWvXTnFxcerXr582bNhgdpW8Ip8FIkFpmaHsPYV6K+cHZe8p5O8VPqvInjyqVyuld2xK0IOgi7hVXStWrND999+vxYsXq1+/flqwYIGGDh2qnTt3Kjk52ezqVUKqfFgdwxUArCTiAp8nn3xSU6ZM0W233SZJWrx4sd555x0tWbJEM2bM8P2Ffv5Zio6ufDw6WoqL8yznTVSU1KBBtWULDx5Wg5PFKnM4VFI/1n087lSxHIZnOaX8530dDik+/syTx49L3kYszy174oRUVua9zg0b+le2uFgqLQ1M2fj48npLUkmJdPp0YMo2aFD+mUjSyZPSqVOBKRsXd+ZvpTZlT50qL+9NbKxUr17ty54+Xf5/4U1MjFS/fu3LlpaWf3ZnWbO9QPe/nCNDUv3oaJ2KLi978Kefdf+SzxR9cy8NvjCl8uvWr1/+2lL539iJE97rUJuy9eqV/19I5d+J48cDU7aK731pmaGN3x3WoWMlSmoUqz7t/jNEE+BzhNeytfnec47wrSzniHIBPEd4OPu7XJuytTlH+MIIkJ9++ilQL+W3kpISIzo62njjjTc8jt96663GtddeW+XvFBcXGy6Xy/3Iy8szJBmu8tNE5cfVV3u+QHx81eUkwxgwwLNss2Zey+akdDbaPvS2+5GXkOz9ddPSPF83Lc172bZtPcv26eO9bLNmnmUHDPBeNj7es+zVV3sve+6f2Y03Vl/22LEzZSdMqL7swYNnyt51V/Vlc3PPlH3wwerLbtt2pmxmZvVlN2w4U/axx6ovu3btmbLPPFN92bffPlN26dLqy77yypmyr7xSfdmlS8+Uffvt6ss+88yZsmvXVlv20YG3uf9+R976ZPWvm5l55nW3bau+7IMPnimbm1t92bvuOlP24MHqy06YcKbssWPVl73xRsNDdWWDdI4w+vTxLNu2rfeynCPOPDhHlD/C4BxhPPbYmbIbNlRf1o9zhMvlMiQZLpfLqI5fc3zmz5+vFStWuH8eM2aMmjZtqlatWmnLli3+vGRA/PjjjyotLVXz5s09jjdv3lwFBQVV/s68efPkdDrdj9TU1FBUFbC1HQVFlp0LVNPmmQePVnN3DMB0fq3qat++vf7+97+rf//+WrNmjcaMGaMVK1bolVde0b59+/Tee+8Fo6412r9/v1q1aqXPPvtM6enp7uO/+c1v9NFHH+nzzz+v9DslJSUqOasbr6ioSKmpqXLt31/1rPAgdGOv2V6ge1ZsUUn9WPeE5rhTxYr6zw9PnztcQDe2f2Xpxi4XoG7st7fu169XbnX/fPqsoa6oslLFni7/f3j8ph66pkdLrdleoD/8v69V4Cpxl23hjFPmiAs0rGMT73UIo6GuisR7Rw4dqbKYQ1JSk3h9MGvYmUm6DHWV4xxR+7IWP0dUEuShLl9Xdfk1x6egoMDdM/L2229rzJgxGjJkiNq1a6d+/fr585IB0axZM0VHR+vAgQMexw8cOKCUlCrmGUiKjY1VbGxs5ScaNvT8InrjS5kayg7u21EL4uM9JogW149zTxAdXNME0bNPWjU5+8QZyLJnB4OBLBsbe+biFMiyMTG+jwkHq2z9+mdOGNUoLTO0YV+R78t969U7c4KrSW3KRkd7/A03TU7UiZiqP8uyqGidiIl2l8vKLVLG6ztkyCGd9TsFrmJl/CPH95QNUVG+f+ccjoCXdS9G8NJuSdp7vMxzMUIAzhFVqs33nnNE7cta6BxR67IhOkcErGxtvvc+8CvwOe+885SXl6fU1FRlZWXp97//vSTJMAyVVhelB1lMTIwuvvhivf/++xo9erQkqaysTO+//77uvvtu0+rlC7vtMQXfhPOKqYoNUmvaduDitudpwONrvaZscKg8ZcPgtJSw/3tnc03A+vya43P99dfrlltu0eDBg1VYWKjhw4dLkjZv3qxOnToFtIK1df/99+u5557TCy+8oK+//loZGRn6+eef3au8whn5LHC2isSW56Y7KHAVK2P5phrnmgSbrzuaf7H3J59TNoQ7NtcErM+vwOepp57S3XffrbS0NK1Zs0aNGjWSJOXn5+uuu+4KaAVr65e//KX+9Kc/6ZFHHlGvXr2Uk5OjrKysShOegXBmlcSWFTuapzg9L/Qpzjj38FUk9ZJU9HJ5uyVxqLxHrm/7xFBWC0AtsGXFOdidHeEge0+hxj63vsZy/5zyi7BIbFndtgNWa0tNgrm5Jts3AP4L+OTmVatW+fzm1157rc9lAU72lVmtl6RimLYqvs4FskovSUUv17lzr1LqOPcqnOdzAZHE58CnYrJwTRwOh6kTnGEtnOyrFklzSSrmAmUs3ySHqu4lyRyZZqlgN9CLEbxtVFwxn4uNioHA8XmOT1lZmU8Pgh74Ktwn75op0uaS+DIXyGoCtRjBKvO5gEgRcXt1wRpqOtlbaYlzMNBLYh9sVAyElt+Bz88//6yPPvpI+/bt08lzskVOmzatzhVDZONkX7NgzSUxU3VzgezKavO5AKvzK/DZvHmzrr76ah0/flw///yzEhMT9eOPPyo+Pl7JyckEPqiR1U72Zk3AppckcMJ1En0kzecCrMCvwGf69OkaOXKkFi9eLKfTqfXr16t+/foaN26c7r333kDXERHISid7sydg00tSd2Z/htWJtFVvQLjzK4FhTk6OHnjgAUVFRSk6OlolJSVKTU3VY489pv/5n/8JdB0RgawyeZcJ2NYX7p+hrxmww6F3CogEfgU+9evXV9R/dqVNTk7Wvn37JElOp1N5eXmBqx0ilhVO9qy2sT6rfIaRuOoNCFd+DXVddNFF+ve//63OnTtrwIABeuSRR/Tjjz/qpZdeUrdu3QJdR0SocJ+8ywRs67PSZ8h8LiA0/Ap8/vCHP+jo0aOSpEcffVS33nqrMjIy1LlzZy1ZsiSgFURkC+eTvdUmYKMyq32GzOcCgs+vwKdPnz7ufycnJysrKytgFYL9hOvJ3koTsKXwXbVkJqt9hgCCjwSGgBdWWm1j9qqlcA26rPQZAggNvwKf9u3by+HwflL79ttv/a4QEC6skj3Z7H2ezA66qmOVzxBA6DgMw6j1coann37a4+dTp05p8+bNysrK0q9//WvNmDEjYBUMNV+3tTfbydNlein7O+09fFxtE+M1Pr2dYur5tUgPNQjnC3tpmaFL53/gdQJvRY/GJw8NCsrF3VvQVfFO4bIiKZw/QwCB4ev126/Ax5uFCxdq48aNWrp0aaBeMuSsEPjMe/crPbcuV2evwI1ySFMua6+ZV6eZV7EIFq5DOdl7CjX2ufU1lvvnlF8EfB6V2UFXbYXrZ+iPSGoLECi+Xr8DOsdn+PDhmjlzpqUDn3A3792v9NePcysdLzPkPk7wE3jhOgHbzFVLVloqLoXvZ1hb9F4BdRPQsZFXX31ViYlMEgyWk6fL9Ny6ykHP2Z5bl6uTp8tCVCOYzcxVS1ZbKh4Jwj0LNWAFficwPHtys2EYKigo0KFDh/Tss88GrHLw9FL2d6opwWyZUV5u0mUdJNElHgmq+wzNXLXEUnHfBOo7WFMWaofKs1APTkvhOw5Uw6/AZ/To0R4/R0VFKSkpSQMHDtQFF1wQiHqhCnsPH69VObrEra+mz9DMVUssFa9ZIL+DVhtaBMKVX4FPZmZmoOsBH7RNjPe5nNlLnFF3vn6GZm39wVLx6gX6O8jQIhAYPgc+RUVFPr9ouK6Gsrrx6e306LtfVzvcFeWQbunXVoOe+JAucQur7bCGWVt/hPt+a2YJxrAUQ4tAYPgc+DRp0qTapIVnKy0t9btC8C6mXpSmXNa+ylVdFaZc1l45eUfoErc4f4Y1zFq1FM77rZklGMNSDC0CgeFz4LN27Vr3v7/77jvNmDFDEydOVHp6uiQpOztbL7zwgubNmxf4WsKtYql6dXl83sr5wafXoks8fFltWCNSlooHSjA+P4YWgcDwOfAZMGCA+99z587Vk08+qbFjx7qPXXvtterevbv+93//VxMmTAhsLeFh5tVpemDIBV4zN9Mlbn18htYWrM+PoUWg7vya3Jydna3FixdXOt6nTx9Nnjy5zpVCzWLqRbmXrJ+LLnHr4zO0tmB+fgwtBg7pPuzJrwSGqampeu655yod/9vf/qbU1NQ6Vwp1U9ElLp3pAq9Al7g18BlaW7A/v4qhxVG9Wim9Y1P+DvyQtS1fl87/QGOfW697X87R2OfW69L5H5AE0gb82qvr3Xff1Q033KBOnTqpX79+kqQNGzZo165deu2113T11VcHvKKhYoW9unxFHh/r4zO0Nj6/8GSVzXVRO0HfpDQvL0+LFi3Sjh07JEldu3bVnXfeafken0gKfCS6ciMBn6G18fmFF6ttrgvfmbI7eySItMAHAHBG9p5CjX1ufY3l/jnlF6xUDLBg3wQEfHf2rVu3qlu3boqKitLWrVurLdujRw/fawoAQIhYLVVEpAinYV+fA59evXqpoKBAycnJ6tWrlxwOh6rqLHI4HCQwBACEJVJFhF64baHkc+CTm5urpKQk978BAPAmXOc2kSoitIKxfUtd+Rz4tG3btsp/AwBwNrOHNaoLusiAHVrB2L6lrvzK4/PCCy/onXfecf/8m9/8Rk2aNFH//v21d+/egFUOgO9Kywxl7ynUWzk/KHtPoUqr280WCJKKYY1zL3YVwxrBzpPjS36eigzYKU7P4awUZxxL2QMsHOdU+bWqq0uXLlq0aJEGDRqk7OxsXXnllVqwYIHefvtt1atXT6+//now6hoSrOqCFZl9hw1I5i8Vr21+nnAdjoskoVxF5+v1268en7y8PHXq1EmS9Oabb+rGG2/U7bffrnnz5mndunX+1RiAX8y+wwYq1GZYI9Bqmksilc8lObsnlAzYwVcxp8rb/6xD5TdpoZxT5Vfg06hRIxUWFkqS3nvvPQ0ePFiSFBcXpxMnTgSudgCq5c/JHggWM4c1zAy64F04br/jV+AzePBgTZ48WZMnT9Y333zj3qJi+/btateuXSDrB6AanOwRTsxcKh6Oc0lQLtzmVPm1O/vChQs1a9Ys5eXl6bXXXlPTpuXjcl988YXGjh0b0AoC8I6TPcKJmUvFyc8T3oZ1a6HBaSlhMafKr8CnSZMmeuaZZyodnzNnTp0rBMB3nOwRTsxcKk5+nvBXMafKbH4NdUnSunXrNG7cOPXv318//PCDJOmll17SJ598ErDKAaheOE4chL2ZNawRzLkkpIqILH71+Lz22msaP368fvWrX2nTpk0qKSmRJLlcLv3hD3/Qu+++G9BKAqgaydgQjswa1qgIus5N7ZBSh9QOpIqIPH7l8bnooos0ffp03XrrrWrcuLG2bNmiDh06aPPmzRo+fLgKCgqCUdeQII+P9dkxNwcnZ+CMQJ0DapsXCOYK+O7sZ9u5c6cuv/zySsedTqeOHDniz0sCAWHXACCcJg4CZgvEXJJw3GMKgeHXHJ+UlBTt3r270vFPPvlEHTp0qHOlAH/YPZEfydiAwCFVROTyK/CZMmWK7r33Xn3++edyOBzav3+//v73v+uBBx5QRkZGoOsI1IhEfgACiVQRkcuvwGfGjBm65ZZbdOWVV+rYsWO6/PLLNXnyZGVkZGjy5MmBrqPP2rVrJ4fD4fH44x//aFp9EDrcnQEIJFJFRC6/Ah+Hw6Hf/va3Onz4sLZt26b169fr0KFDcjqdat++faDrWCtz585Vfn6++3HPPfeYWh+EBndnAAKJVBGRq1aBT0lJiWbOnKk+ffrokksu0bvvvqu0tDRt375dXbp00dNPP63p06cHq64+ady4sVJSUtyPhg0bmlofhAZ3ZwACKRz3mEJg1CrweeSRR7Ro0SK1a9dOubm5uummm3T77bfrqaee0hNPPKHc3Fw99NBDwaqrT/74xz+qadOmuuiii/T444/r9OnT1ZYvKSlRUVGRxwPWw90ZgEALtz2mEBi1Ws6+cuVKvfjii7r22mu1bds29ejRQ6dPn9aWLVvkcJgf9U6bNk29e/dWYmKiPvvsM82cOVP5+fl68sknvf7OvHnz2GojAgQ7kZ8dcwMBVbHbd4FUEZGnVgkMY2JilJubq1atWkmSGjRooA0bNqh79+5Bq+CMGTM0f/78ast8/fXXuuCCCyodX7Jkie644w4dO3ZMsbGxVf5uSUmJO/O0VJ4AKTU1lQSGFhWMPD52zQ0EnIvvAsKZrwkMaxX4REdHq6CgQElJSZLK59Ns3bo1qBOaDx06pMLCwmrLdOjQQTExMZWOb9++Xd26ddOOHTvUpUsXn96PzM3WF8g7UjK3AuX4LiDcBSVzs2EYmjhxorv3pLi4WHfeeWelCcSvv/66H1WuWlJSkjvQqq2cnBxFRUUpOTk5YPVB+AvUDsBkboXVBeomgO8CIkmtAp8JEyZ4/Dxu3LiAVqYusrOz9fnnn+uKK65Q48aNlZ2drenTp2vcuHE677zzzK4eLKg2uYECEWgBgRTIYSm+C4gktQp8li5dGqx61FlsbKxefvllzZ49WyUlJWrfvr2mT5+u+++/3+yqwaLIDQSr8jYsVbF9S22HpfguIJL4tUlpOOrdu7fWr19vdjUQQcgNBCsKxrAU3wVEEr8yNwN2QG4gWFEwtm/hu4BIQuADeEHmVlhRMIal+C4gkhD4ANUgcyusJljDUnwXECkiZo4PECxkboWVVAxLFbiKq5zn41B5sOLPsBTfBUQCAh/AB4HKDQQEW7C3bwGsjsAHgC3YaY+pimGpc/P4pLB9C1C7LSvsgC0rgMhj1ws227fAToKyV5cdEPgAkYULdt2Vlhm6dP4HXpfJV8wb+uShQRHbi4bw5+v1m1VdiDilZYay9xTqrZwflL2nUKVlxPZ2VVMyP6k8mR9/I9ULRm4gwCzM8UFEseuQBqrGHlOBwZYViCT0+CBiVAxpnHuhq9ifKGtbvkk1g1m4YAcGW1YgkhD4ICIwpIGqcMEODLasQCQh8EFEYA4CqsIFOzDYsgKRhMAHEYEhDVSFC3bgsGUFIgWTmxERGNKAN8FK5mdHbFmBSEDgg4gQzP2JYH1csAOH7VtgdQQ+iAjsT4SacMEGIDHHBxGEOQgAgJrQ44OIwpAGAKA6BD6IOAxpAAC8YagLAADYBoEPAACwDQIfAABgGwQ+AADANgh8AACAbRD4AAAA2yDwAQAAtkHgAwAAbIPABwAA2AaBDwAAsA22rAAAIEyVlhnsPRhgBD4AAIShrG35mrP6K+W7it3HWjjjlDkyTcO6tTCxZtbGUBcAnKW0zFD2nkK9lfODsvcUqrTMMLtKsKGsbfnKWL7JI+iRpAJXsTKWb1LWtnyTamZ99PgAwH9wh41wUFpmaM7qr1RVyG1Ickias/orDU5LYdjLD/T4AIC4w0b42JB7uNLf4dkMSfmuYm3IPRy6SkUQAh8AtlfTHbZUfofNsBdC4eBR70GPP+XgicAHgO1xh41wktw4LqDl4InAB4DtcYeNcNK3faJaOOPkbfaOQ+Vzz/q2TwxltSIGgQ8A2+MOG+EkOsqhzJFpklQp+Kn4OXNkGhOb/UTgA8D2uMNGuBnWrYUWjeutFKdnsJ3ijNOicb1ZZVgHLGcHYHsVd9gZyzfJIXlMcuYOG2YZ1q2FBqelkLk5wByGYbBM4SxFRUVyOp1yuVxKSEgwuzoAQog8PoB1+Xr9pscHAP6DO2wg8hH4AMBZoqMcSu/Y1OxqAAgSAh8AOAu7YQORjcAHAP6DOT5A5GM5OwCIvboAu7BM4PPoo4+qf//+io+PV5MmTaoss2/fPo0YMULx8fFKTk7Wr3/9a50+fTq0FQVgOezVBdiHZQKfkydP6qabblJGRkaVz5eWlmrEiBE6efKkPvvsM73wwgtatmyZHnnkkRDXFIDVsFcXYB+WCXzmzJmj6dOnq3v37lU+/9577+mrr77S8uXL1atXLw0fPly/+93vtHDhQp08eTLEtQVgJezVBdiHZQKfmmRnZ6t79+5q3ry5+9jQoUNVVFSk7du3e/29kpISFRUVeTwA2At7dQH2ETGBT0FBgUfQI8n9c0FBgdffmzdvnpxOp/uRmpoa1HoCCD/s1QXYh6mBz4wZM+RwOKp97NixI6h1mDlzplwul/uRl5cX1PcDEH7YDRuwD1Pz+DzwwAOaOHFitWU6dOjg02ulpKRow4YNHscOHDjgfs6b2NhYxcbG+vQeACJXxW7Y5+bxSSGPDxBRTA18kpKSlJSUFJDXSk9P16OPPqqDBw8qOTlZkrRmzRolJCQoLS0tIO8BayDzLvzFXl1A5LNM5uZ9+/bp8OHD2rdvn0pLS5WTkyNJ6tSpkxo1aqQhQ4YoLS1N48eP12OPPaaCggLNmjVLU6dOpUfHRsi8i7piry4gsjkMw7BERq6JEyfqhRdeqHR87dq1GjhwoCRp7969ysjI0IcffqiGDRtqwoQJ+uMf/6h69XyP73zd1h7hpyLz7rl/0BX36ovG9Sb4AYAI5ev12zKBT6gQ+FhTaZmhS+d/4DUJnUPlczU+eWgQwxYAEIF8vX5HzHJ22BuZdwEAviDwQUQg8y4AwBcEPogIZN4FAPiCwAcRgcy7AABfEPggIpB5FwDgCwIfRIyKzLspTs/hrBRnHEvZAQCSLJTAEPAFmXcBANUh8EHEIfMuAMAbhroAAIBtEPgAAADbIPABAAC2QeADAABsg8AHAADYBoEPAACwDQIfAABgGwQ+AADANgh8AACAbZC5GQhzpWUGW3AAQIAQ+ABhLGtbvuas/kr5rmL3sRbOOGWOTGPTVQDwA0NdQJjK2pavjOWbPIIeSSpwFStj+SZlbcs3qWYAYF0EPkAYKi0zNGf1VzKqeK7i2JzVX6m0rKoSAABvCHyAMLQh93Clnp6zGZLyXcXakHs4dJUCgAhA4AOEoYNHvQc9/pQDAJQj8AHCUHLjuICWAwCUI/ABwlDf9olq4YyTt0XrDpWv7urbPjGU1QIAyyPwAcJQdJRDmSPTJKlS8FPxc+bINPL5AEAtEfgAYWpYtxZaNK63Upyew1kpzjgtGtebPD4A4AcSGAJhbFi3FhqclkLmZgAIEAIfIMxFRzmU3rGp2dUAgIjAUBcAALANAh8AAGAbBD4AAMA2CHwAAIBtEPgAAADbIPABAAC2QeADAABsg8AHAADYBoEPAACwDQIfAABgGwQ+AADANgh8AACAbRD4AAAA2yDwAQAAtkHgAwAAbIPABwAA2AaBDwAAsA3LBD6PPvqo+vfvr/j4eDVp0qTKMg6Ho9Lj5ZdfDm1FAQBA2KpndgV8dfLkSd10001KT0/X888/77Xc0qVLNWzYMPfP3oIkAABgP5YJfObMmSNJWrZsWbXlmjRpopSUlBDUCAAAWI1lhrp8NXXqVDVr1kx9+/bVkiVLZBiG2VUCAABhwjI9Pr6YO3euBg0apPj4eL333nu66667dOzYMU2bNs3r75SUlKikpMT9c1FRUSiqCgAATGBqj8+MGTOqnJB89mPHjh0+v97DDz+sSy65RBdddJEeeugh/eY3v9Hjjz9e7e/MmzdPTqfT/UhNTa1rswAAQJhyGCaOBR06dEiFhYXVlunQoYNiYmLcPy9btkz33Xefjhw5UuPrv/POO7rmmmtUXFys2NjYKstU1eOTmpoql8ulhIQE3xoCAABMVVRUJKfTWeP129ShrqSkJCUlJQXt9XNycnTeeed5DXokKTY2ttrnAQBA5LDMHJ99+/bp8OHD2rdvn0pLS5WTkyNJ6tSpkxo1aqTVq1frwIED+sUvfqG4uDitWbNGf/jDH/Tggw+aW3EAABA2LBP4PPLII3rhhRfcP1900UWSpLVr12rgwIGqX7++Fi5cqOnTp8swDHXq1ElPPvmkpkyZYlaVAQBAmDF1jk848nWMEAAAhA9fr98Rl8cHAADAGwIfAABgGwQ+AADANgh8AACAbRD4AAAA2yDwAQAAtkHgAwAAbIPABwAA2AaBDwAAsA0CHwAAYBsEPgAAwDYIfAAAgG1YZnd2AOGrtMzQhtzDOni0WMmN49S3faKioxxmVwsAKiHwAVAnWdvyNWf1V8p3FbuPtXDGKXNkmoZ1a2FizQCgMoa6APgta1u+MpZv8gh6JKnAVayM5ZuUtS3fpJoBQNUIfAD4pbTM0JzVX8mo4rmKY3NWf6XSsqpKAIA5CHwA+GVD7uFKPT1nMyTlu4q1Ifdw6CoFADUg8AHgl4NHvQc9/pQDgFAg8AHgl+TGcQEtBwChQOADwC992yeqhTNO3hatO1S+uqtv+8RQVgsAqkXgA8Av0VEOZY5Mk6RKwU/Fz5kj08jnAyCsEPgA8Nuwbi20aFxvpTg9h7NSnHFaNK43eXwAhB0SGAKok2HdWmhwWgqZmwFYAoEPgDqLjnIovWNTs6sBADViqAsAANgGgQ8AALANAh8AAGAbBD4AAMA2CHwAAIBtEPgAAADbIPABAAC2QeADAABsg8AHAADYBpmbz2EYhiSpqKjI5JoAAABfVVy3K67j3hD4nOPo0aOSpNTUVJNrAgAAauvo0aNyOp1en3cYNYVGNlNWVqb9+/ercePGcjiq3mSxqKhIqampysvLU0JCQohrGHyR3j4p8ttI+6wt0tsnRX4baV/oGYaho0ePqmXLloqK8j6Thx6fc0RFRal169Y+lU1ISAibDzwYIr19UuS3kfZZW6S3T4r8NtK+0Kqup6cCk5sBAIBtEPgAAADbIPDxQ2xsrDIzMxUbG2t2VYIi0tsnRX4baZ+1RXr7pMhvI+0LX0xuBgAAtkGPDwAAsA0CHwAAYBsEPgAAwDYIfAAAgG0Q+PzHxx9/rJEjR6ply5ZyOBx68803PZ4/duyY7r77brVu3VoNGjRQWlqaFi9e7FGmoKBA48ePV0pKiho2bKjevXvrtddeC2ErqldTGw8cOKCJEyeqZcuWio+P17Bhw7Rr1y6PMsXFxZo6daqaNm2qRo0a6YYbbtCBAwdC2Arv6tq+w4cP65577lGXLl3UoEEDtWnTRtOmTZPL5QpxS6oWiM+vgmEYGj58eJWvY5ZAtS87O1uDBg1Sw4YNlZCQoMsvv1wnTpwIUSuqF4g2hut5Zt68efqv//ovNW7cWMnJyRo9erR27tzpUcaX88e+ffs0YsQIxcfHKzk5Wb/+9a91+vTpUDbFq0C0ccuWLRo7dqxSU1PVoEEDde3aVU8//XSom1KlQH2GFQoLC9W6dWs5HA4dOXIkBC3wDYHPf/z888/q2bOnFi5cWOXz999/v7KysrR8+XJ9/fXXuu+++3T33Xdr1apV7jK33nqrdu7cqVWrVunLL7/U9ddfrzFjxmjz5s2haka1qmujYRgaPXq0vv32W7311lvavHmz2rZtq6uuuko///yzu9z06dO1evVqrVy5Uh999JH279+v66+/PpTN8Kqu7du/f7/279+vP/3pT9q2bZuWLVumrKwsTZo0KdRNqVIgPr8KCxYs8Loli1kC0b7s7GwNGzZMQ4YM0YYNG/Tvf/9bd999d7Xp60MpEG0M1/PMRx99pKlTp2r9+vVas2aNTp06pSFDhtTq/FFaWqoRI0bo5MmT+uyzz/TCCy9o2bJleuSRR8xoUiWBaOMXX3yh5ORkLV++XNu3b9dvf/tbzZw5U88884wZTfIQiPadbdKkSerRo0eoqu87A5VIMt544w2PYxdeeKExd+5cj2O9e/c2fvvb37p/btiwofHiiy96lElMTDSee+65oNXVX+e2cefOnYYkY9u2be5jpaWlRlJSkrv+R44cMerXr2+sXLnSXebrr782JBnZ2dkhq7sv/GlfVV555RUjJibGOHXqVDCrW2t1ad/mzZuNVq1aGfn5+VX+rYcDf9vXr18/Y9asWaGsqt/8baNVzjMHDx40JBkfffSRYRi+nT/effddIyoqyigoKHCXWbRokZGQkGCUlJSEtgE+8KeNVbnrrruMK664Iuj1ra26tO/ZZ581BgwYYLz//vuGJOOnn34KZdWrFR63QRbQv39/rVq1Sj/88IMMw9DatWv1zTffaMiQIR5lVqxYocOHD6usrEwvv/yyiouLNXDgQPMq7qOSkhJJUlxcnPtYVFSUYmNj9cknn0gqv1M5deqUrrrqKneZCy64QG3atFF2dnZoK1xLvrSvKi6XSwkJCapXL7y3tfO1fcePH9ctt9yihQsXKiUlJeT19Jcv7Tt48KA+//xzJScnq3///mrevLkGDBhQ7ecbTnz9DK1ynqkYIk5MTJTk2/kjOztb3bt3V/Pmzd1lhg4dqqKiIm3fvj2EtfeNP2309joVrxFO/G3fV199pblz5+rFF18Mm97Ws4VfjcLUX/7yF6Wlpal169aKiYnRsGHDtHDhQl1++eXuMq+88opOnTqlpk2bKjY2VnfccYfeeOMNderUycSa+6bij3fmzJn66aefdPLkSc2fP1/ff/+98vPzJZXPLYiJiVGTJk08frd58+YqKCgwoda+86V95/rxxx/1u9/9TrfffnuIa1t7vrZv+vTp6t+/v0aNGmVibWvPl/Z9++23kqTZs2drypQpysrKUu/evXXllVd6nesUTnz9DK1wnikrK9N9992nSy65RN26dZPk2/mjoKDAI+ipeL7iuXDibxvP9dlnn2nFihVhd57xt30lJSUaO3asHn/8cbVp0ybU1fYJgY+P/vKXv2j9+vVatWqVvvjiCz3xxBOaOnWq/vWvf7nLPPzwwzpy5Ij+9a9/aePGjbr//vs1ZswYffnllybW3Df169fX66+/rm+++UaJiYmKj4/X2rVrNXz48LCM2Gurtu0rKirSiBEjlJaWptmzZ4e+wrXkS/tWrVqlDz74QAsWLDC3sn7wpX1lZWWSpDvuuEO33XabLrroIj311FPq0qWLlixZYmb1feLr36gVzjNTp07Vtm3b9PLLL5tdlaAJRBu3bdumUaNGKTMz02P0IBz4276ZM2eqa9euGjduXJBqFgBmj7WFI50z9n78+HGjfv36xttvv+1RbtKkScbQoUMNwzCM3bt3VxqfNwzDuPLKK4077rgj6HWurXPbeLYjR44YBw8eNAzDMPr27WvcddddhmEYXsdq27RpYzz55JPBrG6t+dO+CkVFRUZ6erpx5ZVXGidOnAh2Vf3iT/vuvfdew+FwGNHR0e6HJCMqKsoYMGBAiGruG3/a9+233xqSjJdeesmj/JgxY4xbbrklqPX1hz9ttMJ5ZurUqUbr1q2Nb7/91uO4L+ePhx9+2OjZs6fH8xWf66ZNm4JZ7VqpSxsrbN++3UhOTjb+53/+J9jVrbW6tK9nz55GVFSU+xwTFRVlSDKio6ONRx55JFRNqJb1b+VD4NSpUzp16lSlnoHo6Gj3Xebx48clqdoyVuF0OpWUlKRdu3Zp48aN7mGRiy++WPXr19f777/vLrtz507t27dP6enpZlW31ry1Tyrv6RkyZIhiYmK0atUqj/kWVuGtfTNmzNDWrVuVk5PjfkjSU089paVLl5pY49rx1r527dqpZcuWlZbffvPNN2rbtq0ZVfWbtzaG83nGMAzdfffdeuONN/TBBx+offv2Hs/7cv5IT0/Xl19+qYMHD7rLrFmzRgkJCUpLSwtNQ6oRiDZK0vbt23XFFVdowoQJevTRR0NW/5oEon2vvfaatmzZ4j7H/O1vf5MkrVu3TlOnTg1dY6pjcuAVNo4ePWps3rzZ2Lx5syHJePLJJ43Nmzcbe/fuNQzDMAYMGGBceOGFxtq1a41vv/3WWLp0qREXF2c8++yzhmEYxsmTJ41OnToZl112mfH5558bu3fvNv70pz8ZDofDeOedd8xsmltNbXzllVeMtWvXGnv27DHefPNNo23btsb111/v8Rp33nmn0aZNG+ODDz4wNm7caKSnpxvp6elmNKeSurbP5XIZ/fr1M7p3727s3r3byM/Pdz9Onz5tVrPcAvH5nUthtKorEO176qmnjISEBGPlypXGrl27jFmzZhlxcXHG7t27zWhSJXVtYzifZzIyMgyn02l8+OGHHt+d48ePu8vUdP44ffq00a1bN2PIkCFGTk6OkZWVZSQlJRkzZ840o0mVBKKNX375pZGUlGSMGzfO4zUqevjMFIj2nWvt2rVht6qLwOc/Kj6ccx8TJkwwDMMw8vPzjYkTJxotW7Y04uLijC5duhhPPPGEUVZW5n6Nb775xrj++uuN5ORkIz4+3ujRo0elZadmqqmNTz/9tNG6dWujfv36Rps2bYxZs2ZVWkJ64sQJ46677jLOO+88Iz4+3rjuuuuM/Px8E1pTWV3b5+33JRm5ubnmNOosgfj8zhVOgU+g2jdv3jyjdevWRnx8vJGenm6sW7cuxC3xLhBtDNfzjLfvztKlS91lfDl/fPfdd8bw4cONBg0aGM2aNTMeeOCBsEknEYg2ZmZmVvkabdu2DX2DzhGoz/Bs4Rj4OAzDMOrUZQQAAGARzPEBAAC2QeADAABsg8AHAADYBoEPAACwDQIfAABgGwQ+AADANgh8AACAbRD4AIhIDodDb775ZlDfY+DAgbrvvvuC+h4AAovAB0CdZGdnKzo6WiNGjKj177Zr186U3eJHjhypYcOGVfncunXr5HA4tHXr1hDXCkAoEPgAqJPnn39e99xzjz7++GPt37/f7Or4ZNKkSVqzZo2+//77Ss8tXbpUffr0UY8ePUyoGYBgI/AB4Ldjx45pxYoVysjI0IgRI7Rs2bJKZVavXq3/+q//UlxcnJo1a6brrrtOUvkw0d69ezV9+nQ5HA45HA5J0uzZs9WrVy+P11iwYIHatWvn/vnf//63Bg8erGbNmsnpdGrAgAHatGmTz/W+5pprlJSUVKm+x44d08qVKzVp0iQVFhZq7NixatWqleLj49W9e3f985//rPZ1qxpea9Kkicf75OXlacyYMWrSpIkSExM1atQofffdd+7nP/zwQ/Xt21cNGzZUkyZNdMkll2jv3r0+tw1A9Qh8APjtlVde0QUXXKAuXbpo3LhxWrJkic7e/u+dd97Rddddp6uvvlqbN2/W+++/r759+0qSXn/9dbVu3Vpz585Vfn6+8vPzfX7fo0ePasKECfrkk0+0fv16de7cWVdffbWOHj3q0+/Xq1dPt956q5YtW+ZR35UrV6q0tFRjx45VcXGxLr74Yr3zzjvatm2bbr/9do0fP14bNmzwuZ7nOnXqlIYOHarGjRtr3bp1+vTTT9WoUSMNGzZMJ0+e1OnTpzV69GgNGDBAW7duVXZ2tm6//XZ3UAig7uqZXQEA1vX8889r3LhxkqRhw4bJ5XLpo48+0sCBAyVJjz76qG6++WbNmTPH/Ts9e/aUJCUmJio6OlqNGzdWSkpKrd530KBBHj//7//+r5o0aaKPPvpI11xzjU+v8d///d96/PHHPeq7dOlS3XDDDXI6nXI6nXrwwQfd5e+55x793//9n1555RV38FZbK1asUFlZmf72t7+5g5mlS5eqSZMm+vDDD9WnTx+5XC5dc8016tixoySpa9eufr0XgKrR4wPALzt37tSGDRs0duxYSeW9KL/85S/1/PPPu8vk5OToyiuvDPh7HzhwQFOmTFHnzp3ldDqVkJCgY8eOad++fT6/xgUXXKD+/ftryZIlkqTdu3dr3bp1mjRpkiSptLRUv/vd79S9e3clJiaqUaNG+r//+79avce5tmzZot27d6tx48Zq1KiRGjVqpMTERBUXF2vPnj1KTEzUxIkTNXToUI0cOVJPP/10rXrCANSMHh8Afnn++ed1+vRptWzZ0n3MMAzFxsbqmWeekdPpVIMGDWr9ulFRUR7DT1L5ENHZJkyYoMLCQj399NNq27atYmNjlZ6erpMnT9bqvSZNmqR77rlHCxcu1NKlS9WxY0cNGDBAkvT444/r6aef1oIFC9S9e3c1bNhQ9913X7Xv4XA4qq37sWPHdPHFF+vvf/97pd9NSkqSVN4DNG3aNGVlZWnFihWaNWuW1qxZo1/84he1ahuAqtHjA6DWTp8+rRdffFFPPPGEcnJy3I8tW7aoZcuW7knAPXr00Pvvv+/1dWJiYlRaWupxLCkpSQUFBR4BRE5OjkeZTz/9VNOmTdPVV1+tCy+8ULGxsfrxxx9r3Y4xY8YoKipK//jHP/Tiiy/qv//7v91DUJ9++qlGjRqlcePGqWfPnurQoYO++eabal8vKSnJo4dm165dOn78uPvn3r17a9euXUpOTlanTp08Hk6n013uoosu0syZM/XZZ5+pW7du+sc//lHrtgGoGoEPgFp7++239dNPP2nSpEnq1q2bx+OGG25wD3dlZmbqn//8pzIzM/X111/ryy+/1Pz5892v065dO3388cf64Ycf3IHLwIEDdejQIT322GPas2ePFi5cqP/3//6fx/t37txZL730kr7++mt9/vnn+tWvfuVX71KjRo30y1/+UjNnzlR+fr4mTpzo8R5r1qzRZ599pq+//lp33HGHDhw4UO3rDRo0SM8884w2b96sjRs36s4771T9+vXdz//qV79Ss2bNNGrUKK1bt065ubn68MMPNW3aNH3//ffKzc3VzJkzlZ2drb179+q9997Trl27mOcDBBCBD4Bae/7553XVVVd59FJUuOGGG7Rx40Zt3bpVAwcO1MqVK7Vq1Sr16tVLgwYN8lgVNXfuXH333Xfq2LGje6ina9euevbZZ7Vw4UL17NlTGzZs8JhkXPH+P/30k3r37q3x48dr2rRpSk5O9qstkyZN0k8//aShQ4d6DNvNmjVLvXv31tChQzVw4EClpKRo9OjR1b7WE088odTUVF122WW65ZZb9OCDDyo+Pt79fHx8vD7++GO1adNG119/vbp27apJkyapuLhYCQkJio+P144dO3TDDTfo/PPP1+23366pU6fqjjvu8KttACpzGOcOSAMAAEQoenwAAIBtEPgAAADbIPABAAC2QeADAABsg8AHAADYBoEPAACwDQIfAABgGwQ+AADANgh8AACAbRD4AAAA2yDwAQAAtkHgAwAAbOP/A++aiTzrb0VkAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(df['predicted_val'], df['observed_val'] - df['predicted_val'])\n",
    "plt.axhline(y=0, color='r', linestyle='--')\n",
    "plt.xlabel('Actual Values')\n",
    "plt.ylabel('Residuals')\n",
    "plt.title('Residual Plot')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "d2b54e03",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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z/fXXm0aNGhmXy2XatGljMjIyTEFBwXn3KRBIHMacdgwNAABAvAcBAABUgEAAAAAWAgEAAFgIBAAAYCEQAACAhUAAAACWKv+gpLKyMu3bt09hYWGV+rGvAADAf4wxKioqUkxMjJzOsx8nqHIg7Nu3T7GxsVW9OQAA8KO8vDzvr2WvSJUDofxHhubl5Xl/jC0AAAhshYWFio2NPe+P/q5yIJSfVggPDycQAACoYc739gDepAgAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAABLsL8HAFB9jDEqLi729xjVzhijkpISSZLL5ZLD4fDzRIHD7XazP3BJEAhALVJcXKyUlBR/j4HLKCcnRx6Px99joBbiFAMAALBwBAGopY4kjJZx1pJ/4qUnFfbZS5KkovjbpaA6fh7Ivxxlp1Rv20p/j4Farpa8egA4k3EG185vpEF1aufjqgTj7wFwReAUAwAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsAT7ewCcnzFGxcXFkiS32y2Hw+HniQAAl0qgvOZzBKEGKC4uVkpKilJSUrxPGgBA7RQor/kEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsBAIAADAQiAAAAALgQAAACwEAgAAsARcIGzcuFGjRo3Sxo0b/T0KAABXrIAKhOLiYs2bN0/5+fmaN2+eiouL/T0SAABXpIAKhD/96U86fPiwJOnw4cNasWKFnycCAODKFOzvAcrt3btXK1askDFGkmSM0YoVKzRw4EBdddVVfp7Ov8r3iSSOquCcfJ4fpz1vUMvwmlCrnf53avz47/iCA6GkpEQlJSXezwsLC6ttCGOMFi5ceNblc+bMkcPhqLb7q2lO3++33HKLHydBjVJ2SlKIv6fApVB2yvtHXhNqt5KSEtWtW9cv933BpxgyMzNVv35970dsbGy1DZGbm6vNmzertLTUZ3lpaak2b96s3NzcarsvAABwfhd8BGHatGmaPHmy9/PCwsJqi4TmzZurR48e2rp1q08kBAUFqVu3bmrevHm13E9N5XK5vH9+/fXX5Xa7/TgNAllxcfH//x+lM2DOIKK6nfZ3y2tC7XP6v+PTX/8vtwt+BXG5XJdsUIfDoV//+tdKTU2tcPmVfHpBks/jd7vd8ng8fpwGNcYV/u+mVuM14Yrhz+9/AXMVw1VXXaUxY8Z4d4bD4dCYMWPUrFkzP08GAMCVJ2ACQZLuuOMONWrUSJIUGRmpMWPG+HkiAACuTAEVCG63W5MnT1bjxo01adIkzqsBAOAnAfcupl69eqlXr17+HgMAgCtaQB1BAAAAgYFAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAhEAAAgIVAAAAAFgIBAABYCAQAAGAJ9vcAOD+3262cnBzvnwEAtVegvOYTCDWAw+GQx+Px9xgAgMsgUF7zOcUAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAsBAIAALAQCAAAwEIgAAAAC4EAAAAswf4eAMCl4Sg7JePvIapL6cmK/3yFcpSd8vcIuAIQCEAtVW/bSn+PcEmEffaSv0cArgicYgAAABaOIAC1iNvtVk5Ojr/HqHbGGJWUlEiSXC6XHA6HnycKHG63298joJYiEIBaxOFwyOPx+HuMS6Ju3br+HgG4onCKAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAQAAWIKrekNjjCSpsLCw2oYBAACXVvn37fLv42dT5UAoKiqSJMXGxlZ1EwAAwE+KiopUv379s37dYc6XEGdRVlamffv2KSwsTA6Ho8oDBprCwkLFxsYqLy9P4eHh/h6nRmCfVQ37rfLYZ1XDfqu82rzPjDEqKipSTEyMnM6zv9OgykcQnE6nrrrqqqrePOCFh4fXuifFpcY+qxr2W+Wxz6qG/VZ5tXWfnevIQTnepAgAACwEAgAAsBAIZ3C5XJo5c6ZcLpe/R6kx2GdVw36rPPZZ1bDfKo99dhFvUgQAALUXRxAAAICFQAAAABYCAQAAWAgEAABgIRBO89hjj6lXr16qW7euIiIiKlzH4XBYHy+99NLlHTSAXMg+y83N1dChQ1W3bl1FR0crIyNDp06duryDBriWLVtaz6vf/e53/h4r4CxevFgtW7aU2+1Wz5499fe//93fIwWsWbNmWc+pjh07+nusgPPBBx9o+PDhiomJkcPh0BtvvOHzdWOMZsyYoaZNm8rj8Sg5OVk7duzwz7CXGYFwmhMnTujWW2/VL3/5y3Oul5WVpf3793s/RowYcXkGDEDn22elpaUaOnSoTpw4oY0bN2r58uXKzs7WjBkzLvOkgW/27Nk+z6tf/epX/h4poPz5z3/W5MmTNXPmTG3dulXx8fEaNGiQDh486O/RAlbnzp19nlMffvihv0cKOEePHlV8fLwWL15c4dfnzJmjp556SkuXLtUnn3yi0NBQDRo0SMXFxZd5Uj8wsGRlZZn69etX+DVJ5vXXX7+s89QEZ9tna9asMU6n0xw4cMC7bMmSJSY8PNyUlJRcxgkDW4sWLcz8+fP9PUZAS0xMNBMmTPB+XlpaamJiYkxmZqYfpwpcM2fONPHx8f4eo0Y58/W9rKzMNGnSxMydO9e77IcffjAul8usXLnSDxNeXhxBqIIJEyYoMjJSiYmJWrZs2Xl/ZeaVbNOmTbrmmmvUuHFj77JBgwapsLBQX375pR8nCzy/+93v1KhRI3Xt2lVz587lNMxpTpw4oS1btig5Odm7zOl0Kjk5WZs2bfLjZIFtx44diomJUevWrXXHHXcoNzfX3yPVKLt379aBAwd8nnf169dXz549r4jnXZV/WdOVavbs2brhhhtUt25drV27VuPHj9eRI0eUnp7u79EC0oEDB3ziQJL38wMHDvhjpICUnp6ua6+9Vg0bNtTGjRs1bdo07d+/X/PmzfP3aAHh0KFDKi0trfC59PXXX/tpqsDWs2dPZWdnq0OHDtq/f78efvhh9e3bV1988YXCwsL8PV6NUP4aVdHz7kp4/ar1RxAeeOCBCt9YePpHZV5gpk+frt69e6tr1666//779Zvf/EZz5869hI/g8qvufXalqsx+nDx5svr166cuXbro3nvv1ZNPPqlFixappKTEz48CNVVKSopuvfVWdenSRYMGDdKaNWv0ww8/6OWXX/b3aKghav0RhClTpigtLe2c67Ru3brK2+/Zs6ceeeQRlZSU1Jqf2V2d+6xJkybWO83z8/O9X6vNLmY/9uzZU6dOndKePXvUoUOHSzBdzRIZGamgoCDvc6dcfn5+rX8eVZeIiAi1b99eO3fu9PcoNUb5cys/P19Nmzb1Ls/Pz1dCQoKfprp8an0gREVFKSoq6pJtf9u2bWrQoEGtiQOpevfZddddp8cee0wHDx5UdHS0JGndunUKDw9Xp06dquU+AtXF7Mdt27bJ6XR699mVLiQkRN26ddOGDRu8Vw2VlZVpw4YNmjhxon+HqyGOHDmiXbt26a677vL3KDVGq1at1KRJE23YsMEbBIWFhfrkk0/Oe7VbbVDrA6EycnNz9d133yk3N1elpaXatm2bJKlt27aqV6+e3nzzTeXn5+tHP/qR3G631q1bp8cff1xTp0717+B+dL59NnDgQHXq1El33XWX5syZowMHDuihhx7ShAkTalVUXYxNmzbpk08+Uf/+/RUWFqZNmzZp0qRJuvPOO9WgQQN/jxcwJk+erNTUVHXv3l2JiYlasGCBjh49qrFjx/p7tIA0depUDR8+XC1atNC+ffs0c+ZMBQUFafTo0f4eLaAcOXLE56jK7t27tW3bNjVs2FDNmzfXfffdp0cffVTt2rVTq1atNH36dMXExFwZl7f7+zKKQJKammokWR/vvfeeMcaYnJwck5CQYOrVq2dCQ0NNfHy8Wbp0qSktLfXv4H50vn1mjDF79uwxKSkpxuPxmMjISDNlyhRz8uRJ/w0dYLZs2WJ69uxp6tevb9xut4mLizOPP/64KS4u9vdoAWfRokWmefPmJiQkxCQmJpqPP/7Y3yMFrFGjRpmmTZuakJAQ06xZMzNq1Cizc+dOf48VcN57770KX8NSU1ONMf+71HH69OmmcePGxuVymRtvvNFs377dv0NfJvy6ZwAAYKn1VzEAAIDKIxAAAICFQAAAABYCAQAAWAgEAABgIRAAAICFQAAAABYCAbgC7dmzRw6Hw/uTLyvy/vvvy+Fw6IcffqjW+3Y4HHrjjTeqdZsAqh+BAASotLQ07299rFOnjlq1aqXf/OY3Ki4uvuhtx8bGav/+/br66qurYVIAtRG/iwEIYIMHD1ZWVpZOnjypLVu2KDU1VQ6HQ0888cRFbTcoKIjfggjgnDiCAAQwl8ulJk2aKDY2ViNGjFBycrLWrVsn6X+/zTAzM1OtWrWSx+NRfHy8Xn31Ve9tv//+e91xxx2KioqSx+NRu3btlJWVJaniUwxr1qxR+/bt5fF41L9/f+3Zs8dnllmzZlm/4nbBggVq2bKl9/PNmzdrwIABioyMVP369ZWUlKStW7ee9fGdOHFCEydOVNOmTeV2u9WiRQtlZmZWbWcBqFYcQQBqiC+++EIbN25UixYtJEmZmZl68cUXtXTpUrVr104ffPCB7rzzTkVFRSkpKUnTp0/Xv/71L+Xk5CgyMlI7d+7U8ePHK9x2Xl6efvzjH2vChAn6+c9/rk8//VRTpkyp9IxFRUVKTU3VokWLZIzRk08+qSFDhmjHjh0KCwuz1n/qqae0atUqvfzyy2revLny8vKUl5dX6fsFUP0IBCCAvfXWW6pXr55OnTqlkpISOZ1OPf300yopKdHjjz+u9evX67rrrpMktW7dWh9++KGeffZZJSUlKTc3V127dlX37t0lyed/+mdasmSJ2rRpoyeffFKS1KFDB/3zn/+s9KmMG264wefz5557ThEREfrb3/6mYcOGWevn5uaqXbt26tOnjxwOhzd+APgfgQAEsP79+2vJkiU6evSo5s+fr+DgYP3kJz/Rl19+qWPHjmnAgAE+6584cUJdu3aVJP3yl7/UT37yE23dulUDBw7UiBEj1KtXrwrv56uvvlLPnj19lpWHR2Xk5+froYce0vvvv6+DBw+qtLRUx44dU25uboXrp6WlacCAAerQoYMGDx6sYcOGaeDAgZW+XwDVj0AAAlhoaKjatm0rSVq2bJni4+P1/PPPe68+WL16tZo1a+ZzG5fLJUlKSUnRN998ozVr1mjdunW68cYbNWHCBP3+97+v0ixOp1Nn/nb4kydP+nyempqqw4cPa+HChWrRooVcLpeuu+46nThxosJtXnvttdq9e7dycnK0fv163XbbbUpOTvZ5LwUA/yAQgBrC6XTqt7/9rSZPnqx///vfcrlcys3NVVJS0llvExUVpdTUVKWmpqpv377KyMioMBDi4uK0atUqn2Uff/yxta0DBw7IGCOHwyFJ1s9R+Oijj/TMM89oyJAhkv733oZDhw6d83GFh4dr1KhRGjVqlEaOHKnBgwfru+++U8OGDc95OwCXFoEA1CC33nqrMjIy9Oyzz2rq1KmaNGmSysrK1KdPHxUUFOijjz5SeHi4UlNTNWPGDHXr1k2dO3dWSUmJ3nrrLcXFxVW43XvvvVdPPvmkMjIyNG7cOG3ZskXZ2dk+6/Tr10/ffvut5syZo5EjR+rtt99WTk6OwsPDveu0a9dOL7zwgrp3767CwkJlZGTI4/Gc9fHMmzdPTZs2VdeuXeV0OvXKK6+oSZMmioiIqI7dBeAicJkjUIMEBwdr4sSJmjNnjqZNm6bp06crMzNTcXFxGjx4sFavXq1WrVpJkkJCQjRt2jR16dJF119/vYKCgvTSSy9VuN3mzZvrtdde0xtvvKH4+HgtXbpUjz/+uM86cXFxeuaZZ7R48WLFx8fr73//u6ZOneqzzvPPP6/vv/9e1157re666y6lp6crOjr6rI8nLCxMc+bMUffu3dWjRw/t2bNHa9askdPJSxPgbw5z5klFAABwxSPTAQCAhUAAAAAWAgEAAFgIBAAAYCEQAACAhUAAAAAWAgEAAFgIBAAAYCEQAACAhUAAAAAWAgEAAFgIBAAAYPl/x334zlzIz/MAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.boxplot(x=df['observed_val'] - df['predicted_val'])\n",
    "plt.xlabel('Residuals')\n",
    "plt.title('Box Plot of Residuals')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "17fc41e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean Absolute Error: 4.5808383347481945\n",
      "Mean Squared Error: 33.24861525475262\n",
      "R-squared: 0.3365657604430209\n"
     ]
    }
   ],
   "source": [
    "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n",
    "\n",
    "print(\"Mean Absolute Error:\", mean_absolute_error(df['observed_val'], df['predicted_val']))\n",
    "print(\"Mean Squared Error:\", mean_squared_error(df['observed_val'], df['predicted_val']))\n",
    "print(\"R-squared:\", r2_score(df['observed_val'], df['predicted_val']))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5ab68f5",
   "metadata": {},
   "source": [
    "## plots of model data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "ce072ff3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Y6cAY9UkClCU5cWts2bJlvPrqq6xbt47q6uruxysqKohGo3R0dPRYv6WlhYqKitNu79JLL+XQoUM9rvqcbMWKFXi93u6fgwcPpmU/hBBC5J6Tq1/3pav6tam0Jqn1Uq2Sres6/ojKofYgTW1eIu2HMfsa5SpQlmU1EdJ1nWXLlvHyyy+zdu1axo4d22P5RRddhNlsZs2aNd2P7d69m8bGRmbMmHHa7dbV1VFSUoLVemq5dwCr1YrH4+nxI4QQYmhKtvr19EVLMlIlW9N0vMEYh9pDHGvrIO49gtl3sOCmwOualu0Q+pTVW2NLly5l5cqVvPLKK7jd7u5xP0VFRdjtdoqKiliyZAl33nknpaWleDwebr31VmbMmNE9Y+wPf/gDLS0tXHbZZdhsNt58801+8pOf8P/9f/9fNndNCCFEjuiufr3mbkq0VvyKu8dssK7q1yaLJan1kq2SrcY1OsMqvnAMLRrEEO7AVGDtLwK+Dprq3mR40zp8Iy7lspseznZIp8jq9Hml92C045555hm+8Y1vAImCinfddRfPP/88kUiEBQsW8OSTT3bfGnv99ddZsWIFe/fuRdd1zjnnHG655Ra+9a1vYTAkd8FLps8LIcTQN1h1hCJqnM6Qij+iQjSIIdKOQQ1lctdySjgU4PD2Dbgb36I28j4WJTHL7ogygsof7EJJ8rs5GUOujlC2SCIkhBCFQYvH2Ve/mVDHUezFwxlfO7PPKzzJrneyQESlMxwjFI2jxIIYwu0Y4uFM7UpOUdUYB3dsxrLvLWqDW3EqfY/R/ejaVZx74RVpe910fH/nzKwxIYQQItMMRmNSU9+TXa+rAnRnOEZMjaPE/JjCXhSt70RgKNG0OIc/qkP7aDWTOzcxVvElFvS62fMpRXxUNpdhs25MW9mBdJJESAghhBigWFyjMxTDF1bRNA1DtBNTxIui9T3jbKjQNY3mxo8IffgG57ZvYCafJhb0Sn58up1610y08Z9l5MRLqK0al5HK0ukgiZAQQgiRpHAsTmcolhj/o2uJLvARL4qenaasg6W1qZGOhjcYfWw9n9H7LjkT0c1st11McOw8qqfMZpQ1uX6f2SaJkBBCCHEGgYiKNxQjHIuDFscQ8WKIeFHIzSnh6dDZ/ilHP1hNRdNaLtA+6nOduK7QYJ5K26i5VE27mgpn/o2zlURICCGE6IOu6/giKt5gjFhcg3gUQ6RzSBdADAV8HNm+luKDa5gS3c5kpe9Eb5fhHJoq51I+dT6lpeXk5k2v5EgiJIQQQpxE13U6Q4krQKqmoUQDGKPeITsFPhqNcKh+E/aP32Rq6F3OVY6Pc+o17ucTZSQHhl1FUe0ChlWO5pzBDzUjJBESQgghSMwA6wzH8IZixONxDJFOTNHOITkAOq6qHNr1LsreN6n1b2a8crzQY6/kp4UydpXMwT5xARWjz2d8GmsA5QpJhIQQQhQ0Na7h7ZoBFo8dHwDdOeTG/+iaxpH9DUR3rWaidyOX055Y0Cv56dBdNHguRznns1SffyHjDMlV0s5XkggJIYQoSFFVoyMUJRCJo6thjOEOTLHAkBv/c+zQfjp3vM74T9dzGc19rhPUrdQ7LiUydi7Vk2cx2mIZ5CizRxIhIYRIUirVhsXZSfcxj6sqH76/ic62FhR7GSPGTcYU8w258T/tnzbRun011S1ruVA70Oc6Md1IvXU6nTVzGTn1SqrszkGOMjdIIiSEEEk4uf9UyfH+UzteS77/lBi4dB5zNa7xlw2vYNn6C0ZEG6kkhoaR1o0VtE2+gYrJuVfxeKASDU7fYtiRNUyJfYhB6fvKVoNxEseqrmLEtM9SXlRK+SDHmWskERJCiDNo2LSK4jV3Y9OD+BVPd0fyysh+wmvupgEkGUqzdB3zrgKIu7a8ytgt/4CDAEGchLFjIsaI2EGK6x7lEORlMhQJBzm0fQPuT96iNvIXzj/e4LT3uJ+9ymgOjphL6dT5lJZXUTT4oeYsSYSEEKIfWjyOvvERbHqQdsMwUBLfMDHFSrtuoURrRd/4CNqMa+Q2WZqk45j7jxdAjMTi6JFOyt57GCd+vBSDkpj5pGLFq5spogPXjufQJs7CkAezono3OD2nq8Fpr+TnMCPYW3YlzknzGVEzYchMd083SYSEEKIf++o3Ux5pxK94ur+QuykKfsVNeaSRffWbc7KhZD5K9Zj3KICoxlGiPkwRL5/ueZfq2BECOLuToBPbMxDQnZTFmjl0oJ7y8dMGYQ8HTtPiHN5Th7Z7NZN8mxhL3w1OWyniQ88cTOfNY+Q50xiXB4ldtkkiJIQQ/Qh1HE2MT1HMfS5P3LLxEeo4OsiRDV0DPeZd9X86QyqqGjveALUTRVcT6wfaMKEmEqG+tocZJ0HUQFtmdugsNH+ym+COrganx/pcx6/b2e6cgXbOZxk58TOMMfV93ETfJBESQoh+2IuHo2LCpMeIKdZTlpv0GCom7MXDsxDd0JTsMbd6htMWiNIZiqGp0RMJUK/6PyZnaWJ7xFDpY3sktmdy5kajiNbmg7TXv8HoY+u45DQNTqO6iQ9sFxMcM4/qKXMYZcuPBqe5SBIhIYTox/jamex4rYbKyH7adUvPWzW6jkv30WQdx+TamdkLcog58zHv5LBlPK6R0+jw+c5Y/6dsbC2t2yoYETuIVzf3vD2mazgJ0GIeRdnY2gzv2el1tn/K0e1vUtG0hgvi/TU4raWt+moqp86lwi1DntNBEiEhhOiHwWhEmb2c8Jq7KdFa8Svu7hlMLt1HSLGjzF4uA6XT6PTHPHr8mDvwXXATxcHmpOr/GAwG/JNvoLjuUYroIKA7UTFjIoaTABHs+CffgGuQx9Mk3+B0Ak0VVzFs2nxKS4fndYPTXCSJkBBCnMGUy6+lAbpr2ph0HyommqzjpI5QhvQ+5kbdh4qRI+bRhGr/ltETpsAAiiBWTJ7NIcC14znKYs2JMUGYaDGPwj+IdYQKvcFpLlJ0XR9atcRT0NnZSVFREV6vF4/Hk+1whMgqqZ58emo0yvuvPY3a1oiptIbpi5ZgKqBWBIMprun4wjE6AhGOfLgFzXsQu9XGsDGTzmqKu6ZptB6oTwygdpZSNrY241Pm46rKod3vouxJNDj1dDU47aWFMnYVz8E+KdHgVBlCM76Kh4/CXZT+a1np+P6WRAhJhITocnIlX9PxSr7HrFI9GeTYDJZwLE5nOJbo/xVXMUS8GKKdKHo826ENSO8Gp+VdDU576dBd7HDPggnzqT7/QgxDtMFpLidCcmtMCAFI9eT+yLHJvFA0TnswSjgWh3gEY9iLEvPnXQPUEw1ON3AZTX2uk2hw+hkiY+dRPXkWNXJVMaskERJCSPXkfsixyaxgVKU9mKgArUQDGKPevGuA2vFpM59uf+PMDU4t0+gc/Vmqaq+gyuEa5CjF6UgiJISQ6sn9kGOTfpqm44+qdIZiRKNd9X983QUQ88HJDU4n99PgdIdxIkerrpYGpzlMEiEhhFRP7occm/SJqHE6QyqBiIoeDWCIeDGrfQ8czkUDanA6/CrKpi6gZPhIZORpbpNESAgh1ZP7Icfm7MQ1HX9ExRc+cfXHkEdXf1Q1xqEdWzDve/MMDU6Hs7f0SpyTF0iD0zwjiZAQQqon90OOTWqCURV/WCUQjUMshCHi7bf6cy4ZWIPT2ZjO+6w0OM1jkggJIaR6cj/k2CQvqmr4I4kESNU0lGgAQ6QDQzyc7dCSkmyD03rnZcTPmS8NTocISYSEEEDPSr6Vkf2Y9RgxzDlZPXmwiz5msrJ0vhew1PWuW19qYuq7rqNEfZgiXhQt2udzslHU8HRaWw7RXv86o48m3+C0WhqcJq3rXB/b9wHuirE5+f6WREgI0ZOuo0P3DzlWc/XkwoYlxwsb7ngt84UNp1x+LdqMa3okLZPP8h/1bO1LOkRVDV84hi+souk6aPHj4386+x3/07xjI64dz1Eda+4uTNm6rWJQ21x0NTgd0bSWC+K7+1xHGpyeva5zPSrWjAGNGOacfH9LZWmksrQQcPqigS7dR1ix0zH3gaz/45UPMSYrX/clGFXxhmKEookZU4oaRon6MUR9KPTdNLRL846NVNc9ipUQAU5tfHrogjsylgyFAn4OH29wWhv9ANNpGpzuNoznSMVchk2bT3GpDIBPhcVk5OiH71D67s+xEcaHB9Vgycj7O2uVpcPhMI8//jjr1q3j6NGjaFrPN9Rf/vKXlIIRQmRHPhQNzIcYk5Vv+9J1+6sjGCMW10BTMUR9GKL+097+6k3TNFw7nsNKCC/FoCRuhalY8epmiujAteM5tImz0nabLBqNcKhhE/YDbzE19Od+GpxWHW9wulAanKZEwWo2YrM7cTjdGMw2jr5wK1YitBnKc/79nVIitGTJElavXs0Xv/hFPvOZz6D0LjImhMgr+VA0MB9iTFa+7Ium6fjCiStAajyOEgtijHZiSKH2T+uBeqpjzQRwdidB3RQDAd1JWayZQwfqKR8/LeWY46rK4d3vwZ43meLfzHglcPw1eq7XQim7i+dgnbiAyjETGS8zvgbEbDRitdmx2J3Y7S4MFgccP4Z76jbmxfu7S0qJ0Kuvvsqf/vQnZs2ale54hBBZkA9FA/MhxmTl+r6ocY3OcKLys6ZGMER9mKK+s2p8qgbaMKEmEqG+lmPGSRA10DbgbeuaRtP+HUR2reZ879vM6mpw2us72Ks7aehucHoRY4dog9P0U7CYTVisdiw2JzaHE6PFcWqSc1yuv797SykRGjlyJG63O92xCCGyJB+KBuZDjMnK1X2JqhreUAx/KIwSSdz6MmqRtGzb5CxN7DMxVPrYZxL7bHIm36E80eD0DcZ/up5LT9PgNKRb2O74DJGxn5UGp0kyKoZE4mNzYrE7sdodKCbbaROf3nL1/X06KSVCDz30EPfccw9PPfUUo0ePTndMQohBlg9FA/MhxmTl2r6EY3G8wShBfweGSCemDNT9KRtbS+u2CkbEDuLVzT1vj+kaTgK0mEdRNra23+0kGpyuZmTLWi7U9ve5TneD05q5VE29Shqc9kvBbExc8bHanVhsLsxWB5hTLxGQa+/vM0kpEbr44osJh8OMGzcOh8OB2dzz8ldb28AvbQohsicfigbmQ4zJypV9CUZVOnwBov52DDE/prO49XUmBoMB/+QbKK57lCI6COinzhrzT74BVx9jdQI+L00fvMWww2uYHNshDU7PioLFZMBmNmGxObB2je8xWZO+4nMmufL+TlZKidDf/M3fcPjwYX7yk58wYsQIGSwtxBCQyaKBhRRjsrK1L5qm44uo+LwdxINtGOJhBuvrqGLybA4Brh3PURZrTowJwkSLedQpdYQSDU7fxvXJW0yNbOu/wemIqymd8llKR1RLg9M+mI0GrBYzNrsTq82FwWJPa+LTl3z6rKZUR8jhcLBlyxamTUt9ZH8ukTpCQpyQrUrHA3ndfK/GfDI1GuX9155GbWvEVFrD9EVLMGVgHEssrtEZjBDwtkHEi6LF0v4ayTpdZWlVjXHow62Y9r3J1MBWnErft+gSDU6vwDl5ISNqJgxy9LnPaDBisVmx2ZzYHU6MZjuYsjM2KtOf1XR8f6eUCF144YU8+eSTXHbZZSm9aJf777+fl156iV27dmG325k5cyY/+9nPOO+887rXCYfD3HXXXbzwwgtEIhEWLFjAk08+yYgRI7rXaWxs5JZbbmHdunW4XC5uvPFG7r//fkym5C54SSIkRHadXGG5q9rwMWvuVaBNt8HY72BUpdPnJ+JvR4n6z1j0cLDpmsahkxqcltLZ53q9G5wqMt39BIMJq82JzebA6nBgtTkzerUnl2StoOJPf/pT7rrrLv7lX/6F2traU8YIJRvMhg0bWLp0KZdccgmqqnLvvfcyf/58PvzwQ5zOxBTL5cuX88c//pEXX3yRoqIili1bxnXXXcc777wDQDwe55prrqGiooLNmzfT1NTE17/+dcxmMz/5yU9S2T0hxCA6XYXlysh+wmvupgGGZDKUyf2Oazr+YASfrx0t6EXRIuRa2tD8yUcEP3yDCW3rz9jgVB3/WaonXSoNTgEdBd1oxWy1Y7U7cdid2GxWGaJyFlK6ItRV9bP3gdd1HUVRiMdTG3B37Ngxhg8fzoYNG5gzZw5er5fy8nJWrlzJF7/4RQB27drFxIkT2bJlC5dddhmvvfYa/+///T+OHDnSfZXoqaee4p577uHYsWNYkrjELFeEhMgOLR5nxwPzqIzs61FhGQBdp0RrTcwuufutvL311ZdM7Xc4FqfT10HY54WoH4Xc6qB0coPTcUk2OLUUeINTHQO6yYbR4sBid2C3O7FbTJiMuZbaZkfWrgitW7cupRc7E6/XC0BpaaKOxLZt24jFYsybN697nfPPP5+ampruRGjLli3U1tb2uFW2YMECbrnlFnbs2MH06dNPeZ1IJEIkcqI2Rmdn35dihRCZlS8VltMtnfut6zqBUAhfRyuxYKLhaS5dGxhYg9O5VE69uuAbnOoGK7rFgdXhxm53YbMYsJqGzh8CuSalROiKK65IdxxomsYdd9zBrFmzmDJlCgDNzc1YLBaKi4t7rDtixAiam5u71zk5Cepa3rWsL/fffz/33XdfmvdACDFQ+VaBNl3Ssd9xVcXf2Y6/sx0tFgJOmVCVNb0bnE4+TYPTXYZzaKq4imHTFlBaOpzkSykOLToKusmOye7CZnfjsNuxmQ1yu2uQpJQIQWIQ8/bt2/tsunrttQO/r7106VIaGhrYtGlTqiElbcWKFdx5553dv3d2djJq1KiMv64Qoqd8q0CbLmez39GgD5+3jWCgE/TcGfgsDU4HRjeYMVicWB0ubA43DqsZo0ESn2xIKRF6/fXX+frXv86nn356yrJUxggtW7aMV199lbfffpvq6uruxysqKohGo3R0dPS4KtTS0kJFRUX3On/+8597bK+lpaV7WV+sVitW66n/+AghBle+VaBNlwHvd1wl6G8n4G0jHEl/1edUSYPT5OmKCcxdTUrd2OxWud2VI1JKhG699Va+9KUv8Y//+I+n3JYaCF3XufXWW3n55ZdZv349Y8eO7bH8oosuwmw2s2bNGq6//noAdu/eTWNjIzNmzABgxowZ/Mu//AtHjx5l+PDEX09vvvkmHo+HSZMmpRybECLz8q0Cbboku9/EQvja2vD7OlFTnISSbrqm0XTgQyK73uD8jmQanH6WkedexNgky5kMFbrBgm6yYbI6sNmd2O027Gaj3O7KQSnNGvN4PLz//vuMHz/+rF78u9/9LitXruSVV17pUTuoqKgIu90OwC233MKf/vQnnn32WTweD7feeisAmzdvBhLT5y+44AKqqqp44IEHaG5u5mtf+xo33XRT0tPnZdaYENkldYRO2m/LKLjkJirPv5hQOAo5MvPr6OH9+BpWM651HTX6GRqcjpnHyCmzsFgK48p715R23WTDYLYnEh+bBbvZKLO7MixrBRW/+c1vMmvWLJYsWZLSi3a/+Gky42eeeYZvfOMbwImCis8//3yPgoon3/b65JNPuOWWW1i/fj1Op5Mbb7yRn/70p1ktqJgPlW/zIUZROAr1/di13+FPD2I0WymuOofcuPYDHZ+28Gn9G4xsXse52r4+11F1A9stF9BZM4+q2iuxOwujwamumNDNDnSzE6vDid1ixm4xyu2uQZa1RCgYDPKlL32J8vLyPgsq3nbbbSkFky3pToTy4a/bfIhRiCFP0wj52gl0fkooHCEXrv50NTgtO7yWKbGGfhqcns/RqrkMnzoPT3HZIEc5+HTFiG6yoZjsmO1O7HYHNrMRq0lmd2VT1hKhp59+mu985zvYbDbKysp6vAkURWH//v0pBZMt6UyETlct1qX7CCt2OuY+kPVEIx9iFGIo06Ih/B2tBPwdOTH2p7vBaeNbTA3/BYui9rnePmU0jcOvorR2PqUjqvtcZ6joLmRoc2G1ObHa7VhNUs8n12StoOI//MM/cN999/H3f//33VWmReISt77xEWx6sEe12JhipV23UKK1om98BG3GNVm75J8PMQoxJGkakWAHfm8bwWCQbF/9STQ4/T9M+1YzNbCVc7oanPa6uNG7welQnu6umG2YbS6s9uPJj9mIQaa0D3kpJULRaJQvf/nLkgT1kg9VcvMhRiGGEl2NEuhsJdDZTjSWvY7vkJjxdXjPB6gfrWZy50bGdjU47fVPQRsednhmYzp3PiMnTGPcEP233mg0Y7E5sTjd2OxuLBbpZVaIUkqEbrzxRn77299y7733pjuevJYPVXLzIUYhhoJYJIi/41OCvg60gY9ASKuTG5zOOE2D04BuY7tzBur4eVRPumxINjg1mRJd2i12Jza7E5PVke2QRA5IKRGKx+M88MADvPHGG0ydOvWUwdIPP/xwWoLLN/lQJTcfYhQin4V8Hfi9nxIOBbIaR6LB6RvUHF3HJXpjn+tEdRPbbRcRGD2X6torqR5iDU4NBgNWuxObw43d4cJotp16JVwUvJQSofr6+u5mpg0NDT2WFfLo+XyokpsPMQqRbzRVxedrJ9DRSlyNnPkJGXKiwek6Lojv6nMdTVdoME+htXoulVPnMmIINTjVUTDbnNjtTmwOFza7UxIfcUYZ7T5/6NAhqqqqCmYsUT5Uyc2HGIXIC3GVcLATv6+DUDCQtb5fyTY43W0Yz5GKqxhWu4CSYSMoGeQ4M8VgtmO1u7A5XdjtLoxSwFAMUEZrnk+aNIm6ujrGjRuXyZfJKVMuv5YGOFGjR/ehYqLJOi5navTkQ4xC5CRNQw15Cfo6CAT8qFp2kp+TG5zWht7lXCWaWNDr4kejUsn+YVfjmTyf8pFjh8SML10xYu7q0u5yY7VYsh2SyHMp1RFKltvt5oMPPsj5REgqS+dujAMxlPZnKO1LPjjT8Y5FQgQ7WwkFOollaeZX7wanRUrfY5COUsKu4iuwnj+fyrGTUPL8iryOgnL8qo/d6cLhcJ1Vl3b5bA0tWSuomKxCToTE4BpKlbKH0r7kg9Me78vvYNwFs/G1txKNBLMSW+8Gp8O7Gpz24tWdNLhmwrnzGXnuRRjzuMGpjpJoVmpxYHMkEh+bJT3NSuWzNfRkraCiELnkdJWyKyP7Ca+5mwbIm3/khtK+5IO+jrdRi1AV2UNkzV3saL2DismDX0/r2OEDdDa8wdjW9VyqH+lznZBuYbv9M0TGJhqc1uRxg1PdYEG3JKa1O+xu7FYTFlN6r2TJZ0ucjiRCIq8NpUrZQ2lf8kHv462go6CBwUinVkQRHbh2PIc2cdagTPjoaDvKpx+8zsjmdVzYT4PTessFeGvmUlV7FVV52uA0cdXHjmJNTG132O04MljFWT5boj8ZTYQKeSq9GBxDqVL2UNqXfJA43p8QwIEJFU4eJaAYCOhOymLNHDpQT/n4aRmJIdHgdA1lh9f02+D0Q+P5tFRexfBp8xlWXMawjESTWbrBjGZyYLa7sDvcOKwmbObBSTrksyX6k9FEKIPDj4QAhlal7KG0L7lMVeMEfF7aP2mgjCgh7D2ToK71MOMkiBpoS+vrR8NhDtZvwPXJW0wNb+P8rganvb6fezc4dac1iszrGuuD2YnV4cbhSFz1MWVhert8tkR/MpoIffjhh1RVVWXyJUSBG0qVsofSvuQaXdfxBwIEOtuIBjtR9DgmqzNxvImh0sfxJnG8Tc7Ss379Ew1O36Q2sJXxSiixoFfyc4Ry9pReiWPSAipGn5t30901ow3dZMdkdWB3OHFYzdjN6RnofDbksyX6k1IiFAgE+OlPf8qaNWs4evQoWq9aGvv37wdg1KhRZx+hEP0YSpWyh9K+5IpITMXn7SDkawU10V2966iWja2ldVsFI2IH8epmUE66UqFrOAnQYh5F2djalF775Aankzo3MRsvPQI4rg0PH7ovx3jegrxrcKorRnSTA83sxOpw4baasVuMWE25Nc5GPluiPyklQjfddBMbNmzga1/7GpWVlVnP9kXhGkqVsofSvmSTpun4/D4Cvg7UoDcxALoPBoMB/+QbKK57lCI6COhOVMyYiOEkQAQ7/sk34BpgYtLSuIfAjtc5p20DM+j7VsuJBqefpXrSpYzOowanusGCZnZgsjqxO93YzUbsGRzonA7y2RL9SamOUHFxMX/84x+ZNWtWJmIadFJHKP8NpfogQ2lfBlM4FMTX2UbY3wla8kUPm3dsxLXjOcpizd3Hu9VcgX/yDUlPnW9rOURb/Wpqjq5jvP5Jn+skGpxeSGD0PKprr8SSJw1OdcUIZgcmmxOrzYnNZsNmNp5VUcNskc/W0JO1gopjx47lT3/6ExMnTkzpRXONJEJDw1CqGJsP+5ILMYaDfoJ+LyG/Dy2eerNTTdNoPVCPGmjD5CylbGxtn1PmT14vioVo+0FGNK1lcpINTp19NDhN9rUHldGCxe7CYvdgd7qwmgw5f+U/2fdjutcT2ZW1ROi5557jlVde4de//jUOhyOlF84lkggJMTDZ/Ms6EvIR9HUSCnQSV6MZfa2TNe/YiKn+efwxcBNkivIxptM0OP3IMJ7DxxucFg8b0e82z/ZqVHooWKx2rA4PNpcHq9WW84nPydL9fpQrR/ljUCtLT58+vccHY+/evYwYMYIxY8ZgNve8v/2Xv/wlpWCEELkvGxV6w0EfQV8H4YCPeHxwe33FolF2rXueYS2bON9wALuh7+SrUalkf9lVeKYsSKrBafOOjVTXPYqVEAGcBHBiIsaI2EGK6x7lEGQwGVKwmIxYbE6sTg82hxtDHo1TOlm6349SgbrwJJ0ILV68OINhCCHywWBV6NU1jXAoQNDfQSQLyY+mxTm063iDU987fE4JQB+7c1Qv4iOtGs1kp+avH2B8kj2+NE3DteM5rITwUtw9Y03Filc3Z6SqtdVsxGaxYXG4sNpdKBbnqcUF80y6349SgbowJZ0I/fCHP8xkHEKIPJDJCr26phEM+AgGvESDPrS4msbIk3v9po93Etn5Bud1vM0sjhdS7LWbXt1Bgz6OOCaqDG2MNn6KVY9y6JMdSVegbj1QT3WsmQDOntP2Ia1Vrc1GIw6nG4fTjcnmApMl5W3lonS/H6UCdWFKafr8uHHjePfddykrK+vxeEdHBxdeeGF3HSEhxNCS7gq98bhGMNBJONBJOOgDbXCTHzje4HTHasZ+uu60DU7DupkPtPEEFTsjDe1UGTq7l6n6wCtQq4E2TKiJRKiv5SlWtVZQsFnMWBxubE4PFpsLsj3wOoPS/X6UCtSFKaVE6OOPPyYej5/yeCQS4dChQ2cdlBAiN6WjQm88rhEIdBLyJ678oJ/6b0mmJRqcvkFV89ozNjhtLprGxGN/pMrYjqoET1kvlQrUJmdp2qpamwwGHFZLYqyP0wNmR97f8kpWuitGSwXqwjSgRGjVqlXd///GG29QVHRiKmg8HmfNmjWMHTs2fdEJIXJKqhV643ENv99LyN+ZaHFxmiKHmZRqg9NSTSP4v1vTWoH6bKtaGxUDdocD+/GBzpjzoyZRuqW7YrRUoC5MA0qEugZMK4rCjTfe2GOZ2WxmzJgxPPTQQ2kLTgiRWwZSoVfrvvLTSSTY2X3lZzCvVUTDYQ7Vr8f5yVtMDf8lpQanmahAnco2TUYjNrsLu6soceXHIIN1010xWipQF6aUCyq+++67DBs2LBMxDTqpIyTEwJyuzgoz72D09CsI90p+BlPvBqeurganvTRRzkelV+KYNJ+K0eedcbuZqPnT/zbnYLFYsNkd2JxurPaiIT3e52xIHaHClbWCikONJELpI9VYB1c2j3fXawfbWzBaXZSNOpdYOJCV2166pnF47weou99kUudGyroanPaSaHA6C8N5C6iecAHKABOLTFSBPnmbFnc5I6dcjtPtxmZzYTCfmOWVD5+tXHg/puu18+F4iywmQo899ljfG1MUbDYb55xzDnPmzMGYJ28aSYTSQ/6KGlxZPd66Tijgw+/ryNpsL+hqcPoG57StZ+QZG5zOo3rSZZhyqHCgQVGw2uxYnR7sDjcma9+V+vPhs5UPMYqhJ6u9xo4dO0YwGKSkpASA9vZ2HA4HLpeLo0ePMm7cONatW8eoUaNSCmwwSSJ09k5XjdWl+wgrdjrmPiD/GKZRVo63rhMOdhL0ewkH/INe5LBL0g1OrRcSGDOPkbVzsNpypRWQgtVswGpzJtpZOD1g7D8xy4fPVj7EKIamQW2xcbKf/OQn/OpXv+I//uM/GD9+PJBoufHtb3+bm2++mVmzZvGVr3yF5cuX87//+78pBSbyh1RjHVyDerw1jUiok6A/UetH7aNsxmDwedto+eBNhh9Zw7QzNTgdOZfKaXMZ0UeD0+xQcFhM2J0u7E4PitWd9EDnfPhs5UOMQvQnpUTo+9//Pr/73e+6kyCAc845h5///Odcf/317N+/nwceeIDrr78+bYGK3CXVWAdXxo9315Ufn5dIMHvJTyjo58j29Xga36I2+gGTlL7jONHgdD4lwyooGeQ4+5IobGjC5nDhcBVjsKZW2DAfPlv5EKMQ/UkpEWpqakJVTx0ToKoqzc3NAFRVVeHz+c4uOpEXpBrr4MrE8dbicUKBREf3SNCHpmUn+YlFoxza8Q7WA28yNfhnzlWONzjt9f16kEr2DbsS95QFDB857owNTjPNoCjYzMZEI1OHC6ujCMzOs57llQ+frXyIUYj+pJQIXXXVVXz729/mP/7jP5g+fToA77//PrfccgtXX301APX19VJcsUBINdbBla7jHY1GCQV9hANeoqEA6IM/2wu6GpxuO97gdBPjlEBiQa/k5ygl7Cqeg/X8BVSOncT4LE8lNxkM2C0m7BYjVrsLLMd/0hhXPny28iFGIfqTUiL09NNP87WvfY2LLroIsznxV4CqqsydO5enn34aAJfLJcUVC4RUYx1cZ3O8g6Fgd4HDeLTv+jqDoavBaXjnas7v2NBPg1MnDa6Z6BPmUX3eJYxNsrt7ppiNhsR4H4sJs815PPlxZqy4YT58tvIhRiH6k9K/KhUVFbz55pvs2rWLjz76CIDzzjuP8847UZTsqquuSk+EIudJNdbBNdDjrUaC+Du9BPydaGo4q7F/2vQJ3vrXGfvpei7VD/e5Tlg3s91+CaExn6W69nJqLKdeZRhMZqMBu9mE3W7HYneB2Q4m+6AUN8yHz1Y+xChEf6SgIjJ9Pl2kjsjgOu3xvvx2Jn9mLsGAn5DfSygSyWqciQanq6lsXsv52t4+10k0OJ1Gx6i5jJx6NXana5Cj7MliMuIwG7E5XZjtRRm96pOMfPhs5UOMYujJWh2heDzOs88+y5o1azh69Cia1nNswdq1a5Pazttvv82DDz7Itm3baGpq4uWXX+7uZwbQ0tLCPffcw+rVq+no6GDOnDk8/vjjTJgwoXudK6+8kg0bNvTY7re//W2eeuqppPdHEqH0UaNR3n/tadS2RkylNUxftASTxXLmJ4qUdB3veOsBLJ4RnDPjWmLxGKGIik5m/8bpr8pywOelafsayg6tYXKsAeNpG5yeR0vl1Qyf+lk8Jelv2ZN8JWgFu8WIzWzAbnNgtHvA4gZj6rfiCrHScT7EKIaWrNURuv3223n22We55pprmDJlCkrvKZNJCgQCTJs2jW9+85tcd911PZbpus7ixYsxm8288soreDweHn74YebNm8eHH36I0+nsXvdb3/oWP/rRj7p/dzhypXhaYen6i3BU11+En5jY+eH/yF+EGbJjw/+ivPMLxkQPYjz+F/jh3S+eVe+rZHX1yKo+qUdW07tVHC6+mOH+XUwNbzttg9P9WgV73Jcw4rKvUFYxqkeD00zH2LrtRG8wpau+j8WAzWZP1PexuMB09on7yVdHSo6/9o7Xzu7qiMFozPnp5/kQoxC9pZQIvfDCC/zP//wPn/vc587qxRctWsSiRYv6XLZnzx62bt1KQ0MDkydPBuDf/u3fqKio4Pnnn+emm27qXtfhcFBRUXFWsYizc7rKspWR/YTX3E0DSDJ0tnQdYkGIBvhw0yuUbv0ZVkIEcKLixESMEbGDFNc9yiHIWDLUvGMj1XWPYiWEV3fRqNVgIUqtvo9prTsSK/VKfpr0UnZro3AqYcYbDjM1sJVDrZdBRWYqz58cYwAngV7Hp81sYtKsa1Csx2d6naG680DIZ0GI/JLSaD+LxcI552S2ckfk+LgGm83W/ZjBYMBqtbJp06Ye6/73f/83w4YNY8qUKaxYsYJgMJjR2ERPvSvLxgxWdMVAzGCl3VCGTQ8lKstmqTBfXtM0iPjQvE0Em/fQ2vQxB48cQdn2dCIRoRhVsYJiQFWseCnGSgjXjudOuWWdnnA0nPX/RZPmoSE+Fg8BrjB+wAzjTlxKz4HYbbqLzfFJbNJqCSouRpvaGWYMDUqMrh3P9Tw+BgNxg5UOpQwLUbQPXkB3V4G9JK1JkHwWhMg/KSVCd911F7/4xS/I5Djr888/n5qaGlasWEF7ezvRaJSf/exnHDp0iKampu71vvrVr/Lcc8+xbt06VqxYwX/9139xww039LvtSCRCZ2dnjx+RuoFUlhVJ0OIQ7kT3HibQsodjTY0cPnqMVn+IYFTl2P7tlMWaCeAEpddHWDEQwElZrJnWA/VpDaulcQ97XnmQIvUYFxr2McdYT5nSs2hqQLfyf/HzedXzN4SxMMrYykijF8PJb4sMxgjQeqD+xPExGNEVA3FMxDATN5jxKR7Kowcz8n6Uz4IQ+SelW2ObNm1i3bp1vPbaa0yePLm7llCXl1566awDM5vNvPTSSyxZsoTS0lKMRiPz5s1j0aJFPRKwm2++ufv/a2trqaysZO7cuezbt69HC5CT3X///dx3331nHaNIkMqyZ0mNghoCNYIeCxIOhwlG44Si8T4HPKuBNkyoiS/6vjaHGSdB1EDbWYfWfvQwrfWrGdWylou7Gpz2+n6P6ka26+PpxEWV0soE42E061RsSgwvfY/XS2eMJ7OYjBhifozEiSgOdOXUgbqZfD/KZ0GI/JNSIlRcXMwXvvCFdMdyiosuuoi6ujq8Xi/RaJTy8nIuvfRSLr744tM+59JLLwUSTWBPlwitWLGCO++8s/v3zs5ORo3KzFiFQiCVZQdIix8f6xNM/FeLE1HjBCJxQjEV7QxXWk3O0sTxJoZKH8ebxPE2OUtTCu9Eg9O1TI3v7HsXdIUd+hiOUcIIQydlhjBlhDHpEVRM6O5K1GOZi/GERDd3m9WO3eXBbPfQ6W0nts2CCZUYpyZCmXw/ymdBiPyTUiL0zDPPpDuOfhUVJbpI79mzh/fee48f//jHp123rq4OgMrKytOuY7VasVqzW6RtKJHKsklQoxD1QzQAamL8W0SNd1/5iQ+gvUXZ2Fpat1UwInYQr27ueXtM13ASoMU8irKxtUlvMxT0c6R+Q6LBaaSunwan4/gkXsZYDuEyxHApn/b52lUX/xWtB1enNcYuBkXBZjFjd7qx2V2JhqYnTXPP5vtRPgtC5J+Ui2Soqsr69evZt28fX/3qV3G73Rw5cgSPx4PLlVwxNL/fz969JwqsHThwgLq6OkpLS6mpqeHFF1+kvLycmpoa6uvruf3221m8eDHz588HYN++faxcuZLPfe5zlJWVsX37dpYvX86cOXOYOnVqqrsmBkgqy56GGoGIP5EAxWMAROMaoWicYFRFTXGgsMFgwD/5BorrHqWIDgK6ExUzJmI4CRDBjn/yDbjOUPn4RIPTt6gN/plzleOFF/tscHoFnskLKa8eR/GOjTjrHsWK7/SvbTalJcYuRsWAzWbG7ijC5vKgmB2njsHpOj5ZfD/KZ0GI/JNSQcVPPvmEhQsX0tjYSCQS4aOPPmLcuHHcfvvtRCKRpIsZrl+/vs9WHDfeeCPPPvssjz32GA8++CAtLS1UVlby9a9/nR/84AdYjhfoO3jwIDfccAMNDQ0EAgFGjRrFF77wBb7//e8PqLCSFFRMD6ksy4krPxEfxGNouk44Ficc0wjHBnbl50y66uSUnVwnx1zRbx2hkxucTva9Q7Hi73O9Y5Sws2gO1vPnUzluMkqvhCXZ104lxi4KCna7HYfTg93lSbS2GIBsvh/lsyDE4MhaZenFixfjdrt5+umnKSsr44MPPmDcuHGsX7+eb33rW+zZsyelYLJFEqH0KbjKsroOsVB3fR89HiUS0wirGhE1TlTVIIMVnpOpnNyzwenbjKC1z231bnBqPEOD02SrNidf3RlQDNjsTuyuIpxON8pZFjfM5vtxKH0WhtK+5AM53snLWiJUVlbG5s2bOe+883C73d2J0Mcff8ykSZPyro6PJEJiQNRoIvGJBSEWIhJTiagaYTVOJJbZxGcgTm5wOrqfBqf1tosJjp1Pde3lWLLQ4FRHwepwY3cV4XIVyT/4OUaubg0uOd4Dk7UWG5qmEe+jINihQ4dwuzNVMF+ILNG0kxKfILFYlIiauN0VicXPOMtrMJ3c4HR6Ug1Or6LCmZ3PrNHmwukqwen2YDrD1SeRHVIle3DJ8c6OlP71mT9/Po8++ii/+tWvAFAUBb/fzw9/+MOzbrshRE5QI4kZXrEgWjRMRFUJHU98Uh3knCmJBqdrKT20himx+qQanA4rGUb6W5yemWK0YnMV4yoqwSYzN3Na7yrZXYPTY4qVdt1CidaaqJI94xq5ipcGcryzJ6VE6KGHHmLBggVMmjSJcDjMV7/6Vfbs2cOwYcN4/vnn0x2jEJmnxY8nPiGIBYhEY0RUjVAs8+N8UhENhznU8DbOj9/st8HpAWUUHw+/ipIpCzLa4LRfRgtWpweHqxinw5Fyk2YxuAZSJVsarZ49Od7Zk1IiVF1dzQcffMALL7zA9u3b8fv9LFmyhL/927/Fbh/YzA4hsiYWPp78BNBiEcKxOKFYnHCO3e7qoqoxDu/8M4a9b1Ib2MJ4JZRY0LvBKcP4qORKHJMXUDH6PDLbFbBvumLE4vDg8JTgdLgwGiT5yTdSJXtwyfHOnpRvzJtMpjP29BIip/So6BwgGlO7x/qEY3Fy7aoPJGZ8Hd63HXXXm0zsfJvL8SYW9Mor2nDzoftyDOfOZ+S5FzDOkJ1L5waLC7unBJerCItZLt/nM6mSPbjkeGdP0onQqlWrkt7otdfKYC6RA3S9e2YXsSBaLEJEjefsWJ+TtTTuIbDjDc5p28AMWvpcJ6BbqXdcRmz8Z6mePIPRpvR1UR8I3WDG6izGXVyK3WqVW19DhFTJHlxyvLMn6URo8eLFSa2nKEqfM8qEGBRa/EQri1iIqKomrvjk2NT2vvTZ4LSXqG6k3nohvtHzqJ56BSNtfTc1zTQdBeX41R+PuwiLKbkK0SJ/SJXswSXHO3uSToS0HP7rWRS4WLi7oKEWC2esknMm+L1tNCfT4NQ8mU+rrqbygnkMdxeTrYvjusGC0VGEy1OK227FIGN/hrQpl19LA5yoa6P7UDHRZB0ndW0yQI53dqRUUDFZtbW1/OlPf8r5zu5SUDHPxGMnqjnHgqiqSigWJxiOcWRvHTF/EhWMs6h3g1PzaRqc7mYMB5wX4BhzCaOnzsravugoGKwu7O4SXG4PVlPiL1KpfpubMnFe1GiU9197GrWtEVNpDdMXLcFkObuq3+L05LOVvKxVlk7WyVWnc5kkQjmua5BzV/ITV4nGte5ZXlE1flY9rQZD7wanjq4Gp70cpJKd9uk4I81M0A5kd1+MFqzOYpyeUhw2S4+xP1L9Njdl4rzIuRa5LGuVpYXIuFjo+OyuYKK4IXQPdA716tzevGMj1XWPYiVEACcBnJiIMSJ2kOK6RzkEWUmGEg1O/wJ7VjPZ9w7juhqc9rqbdHKDUyXUTu32X2RtX3QUzHY3zqJSnE5Pn9PepfptbsrEeZFzLQqBJEIiN3T37zp+1UfXk+rcrmkarh3PYSWEl2JQErePVKx4dTNFdODa8RzaxMG5taRrGs2f7CK08w3Oa3+bWV0NTnvlE526g3rXTPQJn6X6vEsYazKhaRrB/70lK/tiMFoTNX88JVj6ueUh1W9zUybOi5xrUSgkERLZoWkQO17JORoALY6OTlTVBtTAtPVAPdWxZgI4uxOHboqBgO6kLNbMoQP1lI+flrHdSTQ4fYMxn67jM/00ON1uv4TQmHlU186mpleD00HfF8WAzeHG6SnB7vQkNe1dqt/mpkycFznXolBIIiQGh66DGj5pkHO4R+ITURO1ffQBTm9XA22YUBPJQ1/LMeMkiBpoS8de9OBtO8ax7aupbFrLdG1P36+vG2iwTKVj1Fyqpl5NZT8NTgdrX4wmKy5PKc6iEowDrD0k1W9zUybOi5xrUSgkERKZ0zWtPRZKJEG6fqJrezxONKYNOPHpzeQsTVRjJYZKH9VYSVRjNTlLz+p1ugQDnRypW9Pd4HTKaRqc7jSeS3PlXIZPnUdZSTllSWw7k/uiKAZsTjcuTyk2Z+oTAqT6bW7KxHmRcy0KxYAToVgsxsKFC3nqqaeYMGFCv+v+8pe/ZMSIESkHJ/LMyeN81BBoGpqud/fvykQPr7KxtbRuq2BE7CBe3dzzlpKu4SRAi3kUZWNrU36NaCTMofq3cXz8FlPD2zhPiSUWnNLgtJpPyq+iuHYhZRWjBtzjKxP7YrZYcXhKcblLMKSh8rRUv81NmTgvcq5FoRhwImQ2m9m+fXtS6371q18dcEAij/To3RXsMc6nq5pzpju3GwwG/JNvoLjuUYroIKA7UTFjIoaTABHs+CffgGuAg4sH1uD0CuyTFlBRcy7jz2IQc7r2xWAwYHd6cHlKsTjS229eqt/mpkycFznXolCkVEdo+fLlWK1WfvrTn2YipkGXL3WEsl5kq1fvLtQoANF4YmBzOMVxPumQjjpCvRucDutqcNpLu+5mh+dyDBM+y8jzpmNIc4PTgeyLpmm0HqhHDbRhLRrB2OlX4S4uQzFmtu+Y1JbJTVJHSBSarBVUvPXWW/nNb37DhAkTuOiii3A6ew7ufPjhh1MKJlvyIRHK2j9GfYzzicbjPQY4p/t2V6pOTgoGUlm65eDeRIPT1vWMPEOD0+j4eYyaPBNThhucJrMvJydMBjRUzIP6BZX1xFz0KRPnRc61yFVZS4Suuuqq029QUVi7dm1KwWRLridCpytq5tJ9hBU7HXMfSN8XXx/1fKJx7cRVnxxKfM5G27EjtG1PNDg9R/+4z3USDU6n46uZx8ipV2Cz9z2bKxs+3bWZ4dsexkoYv1KU2feEEELkqKxVll63bl1KLyYGLuNFzeJqYmDz8XE+uqYSVbXEtPZ4bl3xOVt+bxvN29+i/PBapsU/7HMdTVf40DSRYyOvpmLqPIYXlWatwempFBx2G05XCR0v/hYrEdoN5VLoTgghzsJZTZ/fu3cv+/btY86cOdjtdnRdT6oom0he2ouadfftStzyUmMRIscTn2hcy/jg5sEWDgU4vH09nsY11EbeZ+JpGpzuMYzl0IirKZs6n5JhlRQNcpz9UVBwuotwF5VisrvZU7eR8uhBKXQnhBBpkFIi1Nrayl//9V+zbt06FEVhz549jBs3jiVLllBSUsJDDz2U7jgL1lkXNVMjJ8b3qGFisSgRNU40lqjpc3LPrqHiRIPTNdQG/48JXQ1Oe+UMB6lg37ArcU9ewPDq8QOe7p5pJqMJp6cUV1EpBvOJOi5S6E4IIdInpURo+fLlmM1mGhsbmThxYvfjX/7yl7nzzjslEUqjARc1i8e6x/jo0SDRWKz7ak8kpvXZr2soSL7BaTG7imZjPn8BVeOmnNV090wxWWy4i8txuotQ+piRJoXuhBAifVJKhFavXs0bb7xBdXV1j8cnTJjAJ598kpbAREIyRc2aLWOYNP481NaPiUTCQ/Y2V28nNzg9/wwNThtcM9DOmU/1+ZcwxpR7BdV1xYTVVYzHU4Ld4eh3XSl0J4QQ6ZPSN0IgEMDRxz/WbW1tWK2n/oUqUtdnUTNMmPUILnxEsKHWfpnmlpYhe7Wnt2QanEZ0M9ttFxMc+1mqp1zOKKttkKM8Mx0FxeLC5i6hyFOExZTc1SkpdCeEEOmTUiI0e/ZsfvOb3/DjH/8YSEyZ1zSNBx54oN+p9SI1Uy6/lvpoBMOWxyiPHeyuI3TUXJ0osnf+rCGfBCXT4DSuK9RbpnU3OK3op8FpNukGM2ZncaLxqc2KwTDwCQZTLr+WBjhRW0r3oWKiyTpOCt0JIcQApFRHqKGhgblz53LhhReydu1arr32Wnbs2EFbWxvvvPMO48ePz0SsGZOLdYTC4TCRoJ9o2E805EfT4sRjKkfeewXF14TurqTq4r/CaM692zzpEgx0cuSDtZQeXMOU2HaMp2twajiX5qpEg1NPSXnaXj/VAo190VEwWl043CW4PEWYjf1vJ9kCdlLoTghRyLJWUBHA6/Xyr//6r3zwwQf4/X4uvPBCli5dSmVlZUqBZFMuJEKRaJRwwE8k5CcaDqDHoz2Wp6OFRD6IRsIcatiI48BbTA2/h7WrwWkvHysj+bj8aoqnLKCssibtcaTteBtt2NxFuNyl2G2WpJ4iLQ2EECI5WU2EhpJsJELRWJxQ0JdIfEIBdDV82nWbd2ykuu5RrIQIcGojzkMX3JHXyVBcVTm0888Y9r1JrX8z7q4Gp700U8bukiuwT1xAxejzUDI04+tsj7eOgsnuwVVchsvhGtCtr0GtIi6EEHkua5WlAdrb23n66afZuXMnAJMmTeLv/u7vKC0tTXWTQ1osrhEKh4gEfUSDfuLRIEoSM7o0TcO14zmshPBSDEriy1/Filc3U0QHrh3PoU2clfJtm2zQNY0j+xuI7XqD870buZyOxIJeOUN3g9Nz5zPy3AsYl+YGp72dzfFWjBZsrhJcRaXYrMld/enx2pmuIi6EEOIUKSVCb7/9Np///OcpKiri4osvBuCxxx7jRz/6EX/4wx+YM2dOWoPMZz6/n86ONuIRP4p24jZPstcIWg/UUx1rJoCz+0v5xEYMBHQnZbFmDh2op3z8tPQFniEtB/fiP97g9LJ+Gpw2OC4lMm4eo6bMYnSGG5yeLJXjbbS6cBaV4XYXpTTwuUvaq4gLIYQ4o5QSoaVLl/LlL3+Zf/u3f8N4/C/TeDzOd7/7XZYuXUp9fX1ag8xnasiHFmpPOvE55fmBNkyoiS/mvpZjxkkQNdCWepAZ1v5pE63b32BU81ouPk2D05huZPtJDU6rstTgNNnjHQt2YHaX4Skqw2G3p+W1pWK0EEIMvpQSob179/K///u/3UkQgNFo5M477+Q3v/lN2oITYHKWJqoIE0OljyrCJKoIm5y5dUsy0eB0DeWH1zBF3YmhjxlfJxqczqVi6tycaHB6puNtRCWGGU/NNCoqqvvYQuqkYrQQQgy+lBKhCy+8kJ07d3Leeef1eHznzp1Mm5b7t2fySdnYWlq3VTAidhCvbu55u0bXcBKgxTyKsrG12QvyuESD0w24G9/q2eC01+WwXG5werrjrSkGNF3BTYgm63gmT7887a8tFaOFEGLwpZQI3Xbbbdx+++3s3buXyy67DICtW7fyxBNP8NOf/pTt27d3rzt16tT0RFqgDAYD/sk3UFz3KEV0ENBPncXkn3wDriwNlFbVGAcb3sGyfw21wa152+C0S+/j7dfdRBQbZl2lSPcRUhwZq9osFaOFEGLwpTR9/kyzkxRFQdd1FEUhHo+nHNxgyeT0+fZjTfjTMKYjl+oIaVqcwx/VoX30BpM736FE8fW5Xu8Gp5ma7p5uJouN5o/ew/Tuv1MePTjotXykjpAQQiQna3WEBtJYdfTo0QPd/KDLh0QI0lvpeKASDU53E9r5Bue1b6Ciq8FpLz7dTr1rZneDU+NpGpxmc1/6YlQM2J1uHMVlWO2J1hzZrNoslaXTQ46PEENb3hdUfPvtt3nwwQfZtm0bTU1NvPzyyyxevLh7eUtLC/fccw+rV6+mo6ODOXPm8PjjjzNhwoTudcLhMHfddRcvvPACkUiEBQsW8OSTTzJixIik48iXRCgbWpsa6Wh4g9HH1jFWP9TnOr0bnFrO0OA0d65uKTgsZhyeEuyeMjAO3jT9dJArR/2T4yPE0JfVgoq7d+/m8ccf7y6oOHHiRG699dZTBlD3JxAIMG3aNL75zW9y3XXX9Vim6zqLFy/GbDbzyiuv4PF4ePjhh5k3bx4ffvghTmdievPy5cv54x//yIsvvkhRURHLli3juuuu45133kl11wpeZ/sxjn7wJhVNa7lA+6jPdRINTqfSXj2XkdPmJt3gtHfV5gBOTMQYETtIcd2jHIKMJ0NGxYDT4cBZVIrJXgR5csvuZKerQF0Z2U94zd00QEF/2cvxEUIkK6VE6He/+x1f+cpXuPjii5kxYwaQGCw9ZcoUXnjhBa6//vqktrNo0SIWLVrU57I9e/awdetWGhoamDx5MgD/9m//RkVFBc8//zw33XQTXq+Xp59+mpUrV3L11VcD8MwzzzBx4kS2bt3aPZBbnFko4OPwB2soObSG2uh2JvfX4LTyaoZP+yxlJeWUDeA1sl0l22Y243QX4fCUgjk9tX+yQSpQ90+OjxBiIFJKhO6++25WrFjBj370ox6P//CHP+Tuu+9OOhHqTySSmH1ks524zWIwGLBarWzatImbbrqJbdu2EYvFmDdvXvc6559/PjU1NWzZsuW0iVAkEunePiQurRWiRIPTTTgOvMnU8Huc29XgtNeMr64Gp0VT5jOscnTKM76yUSXbZDDgcDhwekox2T2Q4RYdg0EqUPdPjo8QYiBSSoSampr4+te/fsrjN9xwAw8++OBZBwUnEpoVK1bwy1/+EqfTySOPPMKhQ4doamoCoLm5GYvFQnFxcY/njhgxgubm5tNu+/777+e+++5LS5z55uQGp1P8WxivBBMLen1f9G5wOj4NV2gGr0q2gt1ixukuxu4uAXP/Y5byjVSg7p8cHyHEQKSUCF155ZVs3LiRc87peW1g06ZNzJ6dnr+wzGYzL730EkuWLKG0tBSj0ci8efNYtGgRZzu+e8WKFdx5553dv3d2djJq1KizDTlnDazB6SwME+Yz8rzpaW9wmukq2UNh7E8ypAJ1/+T4CCEGIqVE6Nprr+Wee+5h27ZtPQoqvvjii9x3332sWrWqx7qpuuiii6irq8Pr9RKNRikvL+fSSy/tbvRaUVFBNBqlo6Ojx1WhlpYWKioqTrtdq9WK1XrqP5BDzdFD+/A1vJ4zDU4zVSXbZDLh9hTj9JSi5PHYn2RJBer+yfERQgxESonQd7/7XQCefPJJnnzyyT6XAWkrqFhUlGjCsGfPHt577z1+/OMfA4lEyWw2s2bNmu5xSbt376axsbF7EHeh6WpwWt2yjou0A32uE9ON1Fun01kzl5FTrxy0BqfprpJttTlwFw3D7hq6V3/6IhWo+yfHRwgxECklQpqmpeXF/X4/e/fu7f79wIED1NXVUVpaSk1NDS+++CLl5eXU1NRQX1/P7bffzuLFi5k/fz6QSJCWLFnCnXfeSWlpKR6Ph1tvvZUZM2YU1IyxgK+Dpro3+21wCtBgnMSxkVdTMXUe5UWllA9ynJCYGn8IuusIOQmiYqLFPCrJOkIKDqcbd0k5FrtrMELOSVMuv5YGOFEnR/ehYqLJOk7q5CDHRwiRvKwWVFy/fj1XXXXVKY/feOONPPvsszz22GM8+OCDtLS0UFlZyde//nV+8IMfYLFYutftKqj4/PPP9yio2N+tsd6yXVAxlSrLvRucWpS+r7ztVcZwsOJqSmvnU1pelfJ+pNtA99moGHC6i3CVlGO0DP3bX8mSysn9k+MjxNA2qJWlH3vsMW6++WZsNhuPPfZYv+vedtttKQWTLdlMhAZSZVlVYxzcsRnLvreoDW7FqUT63OYhRrC37EpckxcwYlSutjdNjtlowOUpxllUjjLEZn8JIYQ4O4OaCI0dO5b33nuPsrIyxo4de/oNKgr79+9PKZhsyVYi1LvKcu/xMocuuIPhE2ceb3C6msmdm07b4PRTithZNAfTeZ9l5PipedPg9HSsZhMuTwmOovK8a30hhBBicAxqi40DBw70+f8iNf1VWe7QTPh1E773f0d13SPM5NPEk3pNd/fpduqdMxINTid+hjGnaXCaPxQcVjOuolKsrjIw5vv+CCGEyHXyTZMlfVVZbtMceDU7Y5UmphoOA5+c8rzeDU5HnaHBaT5QUHDaLbiLhmFylgyJ6s9CCCHyQ9KJ0MkFCM/k4YcfTimYQtJVZblJL6NV81DJMS4y7II+coC4rtBgnkrbqLlUTbuaCmd6b99li8mQKIDo8pRiGMIFEIUQQuSupBOhZ555hilTpmAymVAU5bTVnZXevX3EKUIBH61NB7Bq5UxR9mE09H0sd2vVHCi5nOqZX6K0tJzU6i3nHqvZhMtdnPfNT4UQQuS/pBMhr9fL7373O4YPH864ceN49913KSsbSO/xwnZyg9ParganfVwA+VgbwQG9kgrlU7C6mfi572SkE/vgU7DbLLiLy7E6S+TqjxBCiJyQdCJUUlLCgQMHGD58OB9//HHaiioOZXFVZc+2t1DrX+63wWmLXswubRQWRWOkcoxphr2JWWOTb0m6ynKuUlBwOuy4S8oT/b/kiqEQQogcknQidP311zNnzhyqqqpQFIWLL74Y42kKk+Xb9PlM+GDt/zDy7e/xmdM0OO3QXTR4LsfvGseoo2uZGD/UXUco+SrLucuoGHC53LiKyzDY3NkORwghhOhT0onQr371K6677jr27t3Lbbfdxre+9S3cbvmCO53iyvEM60qCjgvqVuodlxIZO5fqybMYfbxCtqb9NYd6VVnO1ytBFpMRl9uDwzMMxeLIdjhCJEUqUAtRuAY0fX7hwoUAbNu2jdtvv10SoX6MnngR+4xjqVEbz9jg1GAwUD5+WhaiTBcFh8WE01OCzV0GJsuZnyJEjmjYtKq7J1nJ8auyO16rkZ5kQhSIrPYayxWZqiy9b/tmTDY3BmVojqcyKgacDjtOTykmR5HU/xF5p2HTKorX3I1ND+JXPD261IcVOx1zH5BkSIgclo7v7/y8/5Inxk+diadkWLbDSDur2UhZSSmVNeMoqjoHk6tUkiCRd7R4HH3jI9j0IO2GYcQMVnTFQMxgpd1Qhk0PoW98BC3ed0NjIcTQIJWlRVK6qj87PWVYnCXS/kLkvX31mymPNOJXPKfOZlQU/Iqb8kgj++o3M+GC/J24IITon3ybiX5ZTEYcThcuTymK1S3T38WQEeo4mhgTpPTd1Ddxm8xH6DRNk4UQQ4MkQqIPieanTk8JNlcJmKzZDkiItLMXD0fFhEmPEVNOfY+b9BgqJuzFw7MQnRBisMgYIdHNqBgoctqpqhpFWfV52IorJAkSQ9b42pkcs9bg0n3Qe86IruPSfRyz1jC+dmZ2AhRCDApJhAQWk5ESt5PKkdV4KidglBYYogAYjEaU2csJK3ZKtFbMWgRF1zBrEUq0VkKKHWX2cqknJMQQJ7fGCpjdYsLtcGB1l4GM/xEFaMrl19IA3XWETLoPFRNN1nFSR0iIAiGJUB6Jx1SOvPcKiq8J3V1J1cV/hdF86inUNI3WXpWquxq3Kig4rCbcLhdmVxlYTi3wmK/SXR1Yqg0XhimXX4v6mYW8/9rTqG2NmEprmL5oCSaLFAYVohBIQUUyV1ARoP1YE/40zDo5tOZXTGp+CaceQkFHRyGg2Pmw4jqq597cvV7zjo24djxHWay5u3dZq7mCwOQbOOfiubjdxRgdJWC2nXVMueTk6sBd+33Mmnp14HRvT+QuOddC5C8pqFggDq35FRc3rcSlB9EwEMOEhgGXHuTippUcWvMrIJEEVdc9yojYQSJY8FJEBAsjYgeprHuMQ/t3YSyqHJJJUPGau6mM7EtUAzaUElbsVEb2U7zmbho2rcrq9kTuknMthJBEKMfFYyqTml/CgEb0eAIEChoGopgwoDGp+SVikSiuHc9hJYSXYlSDFd1gJGpw0qoMx0oE/Z3HhlyV3HRXB5Zqw4VDzrUQAiQRynlH3nsFpx4ijhGFnoOZFRTiGHHqIVrW/5KyWDMBnOgGE3FMxBUzmmIAg6FHldyhZCDVgbOxPZG75FwLIUASoZyn+JpQ0NHoe0aXhoKCji3YhJE4EcVBXDGhKz1PraqYMaEOuSq5oY6jiXEd/VUHHsB+p3t7InfJuRZCgCRCOU93V6KjYKDvMe1dA6dDZZOJYcGE2ud6Q7VK7snVgfsy0P1O9/ZE7pJzLYQASYRyXtXFf0VAsWMkjn5SMqQDGjomNPyKk4u/el9BVslNd3VgqTZcOORcCyFAEqGcZzSb+LDiOjQMWFBR0NDRMaBjJY6GgV3jb8Jitxdkldx0VweWasOFQ861EAKkoGLOU1A47//dxvtvOjn3k+dw6SFMaOgo+BQnu8bfxGVfuw8o3Cq56d7vQj2OhUjOtRBCCiqSmwUVTQYDTqcbV1EpBlui/YUajSZV/bZQKyJLZWmRKjnXQuSndHx/SyJEbiVCVrMRl7sYh2fYkCt8KIQQQqRTOr6/5dZYTkj0/3IVlWJ1lYGx7+m8QgghhEgvSYSyyKgYcNosuIrLEv2/DHIpXgghhBhMkghlgdlowOV04iwqQ7H2UdVWCCGEEINCEqFBZDWbcHuKsbtLwWzPdjhCCCFEwZNEaBDYLFbcxaXYXKVglEMuhBBC5Ar5Vs6wouJSDMMq5PaXEEIIkYMkEcowg9ma7RCEEEIIcRrSYkMIIYQQBSuridDbb7/N5z//eaqqqlAUhd///vc9lvv9fpYtW0Z1dTV2u51Jkybx1FNP9VjnyiuvRFGUHj/f+c53BnEvRK7Q4nH21G1k+/rfsaduI1o8nu2QhBBC5Lis3hoLBAJMmzaNb37zm1x33XWnLL/zzjtZu3Ytzz33HGPGjGH16tV897vfpaqqimuvPdED6Fvf+hY/+tGPun93OByDEr/IHQ2bVnX3iypBRcXEjtdqpF+UEEKIfmU1EVq0aBGLFi067fLNmzdz4403cuWVVwJw880388tf/pI///nPPRIhh8NBRUVFpsMVOaph0yqK19yNTQ/iVzyoihmTHqMysp/wmrtpAEmGhBBC9CmnxwjNnDmTVatWcfjwYXRdZ926dXz00UfMnz+/x3r//d//zbBhw5gyZQorVqwgGAxmKWIx2LR4HH3jI9j0IO2GYcQMVnTFQMxgpd1Qhk0PoW98RG6TCSGE6FNOzxp7/PHHufnmm6mursZkMmEwGPj3f/935syZ073OV7/6VUaPHk1VVRXbt2/nnnvuYffu3bz00kun3W4kEiESiXT/3tnZmdH9EJmzr34z5ZFG/EofFboVBb/ipjzSyL76zUy4YHZ2ghRCCJGzcj4R2rp1K6tWrWL06NG8/fbbLF26lKqqKubNmwckbpd1qa2tpbKykrlz57Jv3z7Gjx/f53bvv/9+7rvvvkHZB5FZoY6jiTFBSt+NahO3yXyEOo4OcmRCCCHyQc7eGguFQtx77708/PDDfP7zn2fq1KksW7aML3/5y/z85z8/7fMuvfRSAPbu3XvadVasWIHX6+3+OXjwYNrjF4PDXjwcFRMmPdbncpMeQ8WEvXj4IEcmhBAiH+RsIhSLxYjFYhgMPUM0Go1omnba59XV1QFQWVl52nWsVisej6fHj8hP42tncsxag0v3ga73XKjruHQfx6w1jK+dmZ0AhRBC5LSs3hrz+/09rtwcOHCAuro6SktLqamp4YorruB73/sedrud0aNHs2HDBn7zm9/w8MMPA7Bv3z5WrlzJ5z73OcrKyti+fTvLly9nzpw5TJ06NVu7JQaRwWhEmb2c8Jq7KdFa8Svu7lljLt1HSLGjzF6OwWjMdqhCCCFykKLrvf+MHjzr16/nqquuOuXxG2+8kWeffZbm5mZWrFjB6tWraWtrY/To0dx8880sX74cRVE4ePAgN9xwAw0NDQQCAUaNGsUXvvAFvv/97w/oKk9nZydFRUV4vV65OpSnTq4jZDpeR+iYVeoICSHEUJaO7++sJkK5QhKhoUGLx9lXv5lQx1HsxcMZXztTrgQJIcQQlo7v75yeNSbEQBiMRpkiL4QQYkBydrC0EEIIIUSmSSIkhBBCiIIliZAQQgghCpYkQkIIIYQoWJIICSGEEKJgSSIkhBBCiIIliZAQQgghCpYkQkIIIYQoWJIICSGEEKJgSSIkhBBCiIIliZAQQgghCpYkQkIIIYQoWJIICSGEEKJgSSIkhBBCiIIliZAQQgghCpYkQkIIIYQoWJIICSGEEKJgSSIkhBBCiIIliZAQQgghCpYkQkIIIYQoWJIICSGEEKJgSSIkhBBCiIIliZAQQgghCpYkQkIIIYQoWJIICSGEEKJgSSIkhBBCiIIliZAQQgghCpYp2wEIkS5aPM6++s2EOo5iLx7O+NqZGIzGbIeVkqG0L0IIkcskERJDQsOmVegbH6E80kgJKiomdrxWgzJ7OVMuvzbb4Q3IUNoXIYTIdZIIibzXsGkVxWvuxqYH8SseVMWMSY9RGdlPeM3dNEDeJBBDaV+EECIfyBghkde0eBx94yPY9CDthmHEDFZ0xUDMYKXdUIZND6FvfAQtHs92qGc0lPZFCCHyhSRCIq/tq99MeaQRv+IBRem5UFHwK27KI43sq9+cnQAHYCjtixBC5AtJhEReC3UcxYSKqpj7XK4qZkyohDqODnJkAzeU9kUIIfKFJEIir9mLh6NiwqTH+lxu0mOomLAXDx/kyAZuKO2LEELkC0mERF4bXzuTY9YaXLoPdL3nQl3Hpfs4Zq1hfO3M7AQ4AENpX4QQIl9IIiTymsFoRJm9nLBip0RrxaxFUHQNsxahRGslpNhRZi/Pixo8Q2lfhBAiX8j0eZH3plx+LQ3QXXvHpPtQMdFkHZd3tXeG0r4IIUQ+UHS99zX4wtPZ2UlRURFerxePx5PtcESKhlI15qG0L0IIkSnp+P7O6q2xt99+m89//vNUVVWhKAq///3veyz3+/0sW7aM6upq7HY7kyZN4qmnnuqxTjgcZunSpZSVleFyubj++utpaWkZxL0QucJgNDLhgtlMvfJ6JlwwO68Th6G0L0IIkcuymggFAgGmTZvGE0880efyO++8k9dff53nnnuOnTt3cscdd7Bs2TJWrVrVvc7y5cv5wx/+wIsvvsiGDRs4cuQI11133WDtghBCCCHyWM7cGlMUhZdffpnFixd3PzZlyhS+/OUv84Mf/KD7sYsuuohFixbxz//8z3i9XsrLy1m5ciVf/OIXAdi1axcTJ05ky5YtXHbZZUm9ttwaE0IIIfJP3t8aO5OZM2eyatUqDh8+jK7rrFu3jo8++oj58+cDsG3bNmKxGPPmzet+zvnnn09NTQ1btmw57XYjkQidnZ09foQQQghReHI6EXr88ceZNGkS1dXVWCwWFi5cyBNPPMGcOXMAaG5uxmKxUFxc3ON5I0aMoLm5+bTbvf/++ykqKur+GTVqVCZ3QwghhBA5KucToa1bt7Jq1Sq2bdvGQw89xNKlS3nrrbfOarsrVqzA6/V2/xw8eDBNEQshhBAin+RsHaFQKMS9997Lyy+/zDXXXAPA1KlTqaur4+c//znz5s2joqKCaDRKR0dHj6tCLS0tVFRUnHbbVqsVq9Wa6V0QQgghRI7L2StCsViMWCyGwdAzRKPRiKZpQGLgtNlsZs2aNd3Ld+/eTWNjIzNmzBjUeIUQQgiRf7J6Rcjv97N3797u3w8cOEBdXR2lpaXU1NRwxRVX8L3vfQ+73c7o0aPZsGEDv/nNb3j44YcBKCoqYsmSJdx5552Ulpbi8Xi49dZbmTFjRtIzxoQQQghRuLI6fX79+vVcddVVpzx+44038uyzz9Lc3MyKFStYvXo1bW1tjB49mptvvpnly5ejKAqQKKh411138fzzzxOJRFiwYAFPPvlkv7fGepPp80IIIUT+Scf3d87UEcomSYSEEEKI/DPk6wgJIYQQQmSSJEJCCCGEKFiSCAkhhBCiYEkiJIQQQoiCJYmQEEIIIQqWJEJCCCGEKFiSCAkhhBCiYEkiJIQQQoiClbNNV4UQuU2Lx9lXv5lQx1HsxcMZXzsTg9GY7bCEEGJAJBESQgxYw6ZV6BsfoTzSSAkqKiZ2vFaDMns5Uy6/NtvhCSFE0iQREkIMSMOmVRSvuRubHsSveFAVMyY9RmVkP+E1d9MAkgwJIfKGjBESQiRNi8fRNz6CTQ/SbhhGzGBFVwzEDFbaDWXY9BD6xkfQ4vFshyqEEEmRREgIkbR99ZspjzTiVzygKD0XKgp+xU15pJF99ZuzE6AQQgyQJEJCiKSFOo5iQkVVzH0uVxUzJlRCHUcHOTIhhEiNJEJCiKTZi4ejYsKkx/pcbtJjqJiwFw8f5MiEECI1kggJIZI2vnYmx6w1uHQf6HrPhbqOS/dxzFrD+NqZ2QlQCCEGSBIhIUTSDEYjyuzlhBU7JVorZi2ComuYtQglWishxY4ye7nUExJC5A2ZPi+EGJApl19LA3TXETLpPlRMNFnHSR0hIUTekURICDFgUy6/Fm3GNT0qS0+WytJCiDwkiZAQIiUGo5EJF8zOdhhCCHFWZIyQEEIIIQqWJEJCCCGEKFiSCAkhhBCiYEkiJIQQQoiCJYmQEEIIIQqWJEJCCCGEKFiSCAkhhBCiYEkiJIQQQoiCJYmQEEIIIQqWVJYG9ONdtDs7O7MciRBCCCGS1fW93fU9ngpJhACfzwfAqFGjshyJEEIIIQbK5/NRVFSU0nMV/WzSqCFC0zSOHDmC2+1GUZRsh5P3Ojs7GTVqFAcPHsTj8WQ7HHGcnJfcJecmN8l5yV1d56axsRFFUaiqqsJgSG20j1wRAgwGA9XV1dkOY8jxeDzyj0cOkvOSu+Tc5CY5L7mrqKjorM+NDJYWQgghRMGSREgIIYQQBUsSIZF2VquVH/7wh1it1myHIk4i5yV3ybnJTXJeclc6z40MlhZCCCFEwZIrQkIIIYQoWJIICSGEEKJgSSIkhBBCiIIliZBI2dtvv83nP/95qqqqUBSF3//+9z2WK4rS58+DDz6YnYALxJnOi9/vZ9myZVRXV2O325k0aRJPPfVUdoItMGc6Ny0tLXzjG9+gqqoKh8PBwoUL2bNnT3aCLSD3338/l1xyCW63m+HDh7N48WJ2797dY51wOMzSpUspKyvD5XJx/fXX09LSkqWIC0My5+VXv/oVV155JR6PB0VR6OjoGPDrSCIkUhYIBJg2bRpPPPFEn8ubmpp6/Pznf/4niqJw/fXXD3KkheVM5+XOO+/k9ddf57nnnmPnzp3ccccdLFu2jFWrVg1ypIWnv3Oj6zqLFy9m//79vPLKK7z//vuMHj2aefPmEQgEshBt4diwYQNLly5l69atvPnmm8RiMebPn9/juC9fvpw//OEPvPjii2zYsIEjR45w3XXXZTHqoS+Z8xIMBlm4cCH33ntv6i+kC5EGgP7yyy/3u85f/dVf6VdfffXgBCR0Xe/7vEyePFn/0Y9+1OOxCy+8UP+Hf/iHQYxM9D43u3fv1gG9oaGh+7F4PK6Xl5fr//7v/56FCAvX0aNHdUDfsGGDruu63tHRoZvNZv3FF1/sXmfnzp06oG/ZsiVbYRac3uflZOvWrdMBvb29fcDblStCYlC0tLTwxz/+kSVLlmQ7lII3c+ZMVq1axeHDh9F1nXXr1vHRRx8xf/78bIdW0CKRCAA2m637MYPBgNVqZdOmTdkKqyB5vV4ASktLAdi2bRuxWIx58+Z1r3P++edTU1PDli1bshJjIep9XtJFEiExKH7961/jdrvlUnIOePzxx5k0aRLV1dVYLBYWLlzIE088wZw5c7IdWkHr+mJdsWIF7e3tRKNRfvazn3Ho0CGampqyHV7B0DSNO+64g1mzZjFlyhQAmpubsVgsFBcX91h3xIgRNDc3ZyHKwtPXeUkXaboqBsV//ud/8rd/+7c9/toV2fH444+zdetWVq1axejRo3n77bdZunQpVVVVPf7iFYPLbDbz0ksvsWTJEkpLSzEajcybN49FixahS93bQbN06VIaGhrkKlyOyeR5kURIZNzGjRvZvXs3v/3tb7MdSsELhULce++9vPzyy1xzzTUATJ06lbq6On7+859LIpRlF110EXV1dXi9XqLRKOXl5Vx66aVcfPHF2Q6tICxbtoxXX32Vt99+m+rq6u7HKyoqiEajdHR09Lgq1NLSQkVFRRYiLSynOy/pIrfGRMY9/fTTXHTRRUybNi3boRS8WCxGLBbDYOj50TcajWialqWoRG9FRUWUl5ezZ88e3nvvPf7qr/4q2yENabqus2zZMl5++WXWrl3L2LFjeyy/6KKLMJvNrFmzpvux3bt309jYyIwZMwY73IJxpvOSLnJFSKTM7/ezd+/e7t8PHDhAXV0dpaWl1NTUANDZ2cmLL77IQw89lK0wC86ZzssVV1zB9773Pex2O6NHj2bDhg385je/4eGHH85i1IXhTOfmxRdfpLy8nJqaGurr67n99ttZvHixDGTPsKVLl7Jy5UpeeeUV3G5397ifoqIi7HY7RUVFLFmyhDvvvJPS0lI8Hg+33norM2bM4LLLLsty9EPXmc4LJMZvNTc3d3+u6uvrcbvd1NTUJD+o+ixns4kC1jVdsffPjTfe2L3OL3/5S91ut+sdHR3ZC7TAnOm8NDU16d/4xjf0qqoq3Waz6eedd57+0EMP6ZqmZTfwAnCmc/OLX/xCr66u1s1ms15TU6N///vf1yORSHaDLgB9nRNAf+aZZ7rXCYVC+ne/+129pKREdzgc+he+8AW9qakpe0EXgGTOyw9/+MMzrnMm0n1eCCGEEAVLxggJIYQQomBJIiSEEEKIgiWJkBBCCCEKliRCQgghhChYkggJIYQQomBJIiSEEEKIgiWJkBBCCCEKliRCQgghhChYkggJIU7ryiuv5I477jjt8jFjxvDoo492/64oCr///e8B+Pjjj1EUhbq6upRee/369SiKQkdHR0rPH4h/+qd/4oILLsj46wghco/0GhNCpOzdd9/F6XRmO4wBURSFl19+mcWLF2c7FCFEDpBESAiRsvLy8myHIIQQZ0VujQkh+qWqKsuWLaOoqIhhw4bxgx/8gK4Whb1vjZ2NP/3pT5x77rnY7XauuuoqPv7441PW2bRpE7Nnz8ZutzNq1Chuu+02AoFA9/IxY8bw4x//mL/5m7/B6XQycuRInnjiiR7LAb7whS+gKEr3713+67/+izFjxlBUVMRXvvIVfD5fUrFfeeWV3Hrrrdxxxx2UlJQwYsQI/v3f/51AIMDf/d3f4Xa7Oeecc3jttde6n9N16++NN95g+vTp2O12rr76ao4ePcprr73GxIkT8Xg8fPWrXyUYDCZ/IIUQAyKJkBCiX7/+9a8xmUz8+c9/5he/+AUPP/ww//Ef/5HW1zh48CDXXXcdn//856mrq+Omm27i7//+73uss2/fPhYuXMj111/P9u3b+e1vf8umTZtYtmxZj/UefPBBpk2bxvvvv8/f//3fc/vtt/Pmm28CiVt5AM888wxNTU3dv3dt//e//z2vvvoqr776Khs2bOCnP/1p0vvw61//mmHDhvHnP/+ZW2+9lVtuuYUvfelLzJw5k7/85S/Mnz+fr33ta6ckNf/0T//Ev/7rv7J582YOHjzIX//1X/Poo4+ycuVK/vjHP7J69Woef/zxAR1PIcQAJN2nXghRcK644gp94sSJuqZp3Y/dc889+sSJE3Vd1/XRo0frjzzySPcyQH/55Zd1Xdf1AwcO6ID+/vvvn/F1VqxYoU+aNKnHY/fcc48O6O3t7bqu6/qSJUv0m2++ucc6Gzdu1A0Ggx4KhbrjWbhwYY91vvzlL+uLFi3qM8YuP/zhD3WHw6F3dnZ2P/a9731Pv/TSS88Yu64njtPll1/e/buqqrrT6dS/9rWvdT/W1NSkA/qWLVt0Xdf1devW6YD+1ltvda9z//3364C+b9++7se+/e1v6wsWLEgqDiHEwMkVISFEvy677DIURen+fcaMGezZs4d4PJ6219i5cyeXXnppj8dmzJjR4/cPPviAZ599FpfL1f2zYMECNE3jwIEDp33ejBkz2Llz5xljGDNmDG63u/v3yspKjh49mvQ+TJ06tfv/jUYjZWVl1NbWdj82YsQIgFO2efLzRowYgcPhYNy4cT0eG0gcQoiBkcHSQoi84Pf7+fa3v81tt912yrKampqz3r7ZbO7xu6IoaJp2Vs8/+bGuZLL3Nnuvc7ZxCCEGRhIhIUS//u///q/H71u3bmXChAkYjca0vcbEiRNZtWrVKa9zsgsvvJAPP/yQc845p99t9X7e1q1bmThxYvfvZrM5rVezhBD5TW6NCSH61djYyJ133snu3bt5/vnnefzxx7n99tvT+hrf+c532LNnD9/73vfYvXs3K1eu5Nlnn+2xzj333MPmzZtZtmwZdXV17Nmzh1deeeWUwdLvvPMODzzwAB999BFPPPEEL774Yo94x4wZw5o1a2hubqa9vT2t+yGEyD+SCAkh+vX1r3+dUCjEZz7zGZYuXcrtt9/OzTffnNbXqKmp4Xe/+x2///3vmTZtGk899RQ/+clPeqwzdepUNmzYwEcffcTs2bOZPn06//iP/0hVVVWP9e666y7ee+89pk+fzj//8z/z8MMPs2DBgu7lDz30EG+++SajRo1i+vTpad0PIUT+UXT9eEEQIYTIc2PGjOGOO+7oty2IEEKcTK4ICSGEEKJgSSIkhMi473znOz2mvZ/8853vfCfb4fWrsbHxtLG7XC4aGxuzHaIQ4izIrTEhRMYdPXqUzs7OPpd5PB6GDx8+yBElT1XVPtt9dBkzZgwmk0zAFSJfSSIkhBBCiIIlt8aEEEIIUbAkERJCCCFEwZJESAghhBAFSxIhIYQQQhQsSYSEEEIIUbAkERJCCCFEwZJESAghhBAFSxIhIYQQQhSs/x9rs6y7eertXQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.regplot(x='bill_depth_mm',y='flipper_length_mm', data=olsdata)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0664c1ca",
   "metadata": {},
   "source": [
    "### Checking the normality assumption"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "de7cc477",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import statsmodels.api\n",
    "fig = statsmodels.api.qqplot(model.resid, line = 's')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "27838c76",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig = sns.histplot(model.resid)\n",
    "fig.set_xlabel(\"Residual Value\")\n",
    "fig.set_title(\"Histogram of Residuals\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77cc197a",
   "metadata": {},
   "source": [
    "### Check the homoscedasticity assumption"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "1dd86f31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "fig = sns.scatterplot(x=df['predicted_val'], y=model.resid)\n",
    "\n",
    "# Add reference line at residuals = 0\n",
    "fig.axhline(0)\n",
    "\n",
    "# Set x-axis and y-axis labels\n",
    "fig.set_xlabel(\"Fitted Values\")\n",
    "fig.set_ylabel(\"Residuals\")\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}