Assignment1-Basic Statistics Level-1 (Code File).ipynb

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   "metadata": {},
   "source": [
    "#  Importing all the requied libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "002f7d61",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import statistics as stat\n",
    "import scipy.stats as stats\n",
    "import statsmodels.api as sm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "136db8c4",
   "metadata": {},
   "source": [
    "#  "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7439d41a",
   "metadata": {},
   "source": [
    "#  Q 20) Calculate probability from the given dataset for the below cases\n",
    "\n",
    "### Data _set: Cars.csv\n",
    "### Calculate the probability of MPG  of Cars for the below cases.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "521ca508",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the dataset\n",
    "\n",
    "cars=pd.read_csv(\"Cars (1).csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1b96a766",
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
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       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
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       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
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       "      <th>76</th>\n",
       "      <td>322</td>\n",
       "      <td>36.900000</td>\n",
       "      <td>50</td>\n",
       "      <td>169.598513</td>\n",
       "      <td>16.132947</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>238</td>\n",
       "      <td>19.197888</td>\n",
       "      <td>115</td>\n",
       "      <td>150.576579</td>\n",
       "      <td>37.923113</td>\n",
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       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>263</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>50</td>\n",
       "      <td>151.598513</td>\n",
       "      <td>15.769625</td>\n",
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       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>295</td>\n",
       "      <td>19.833733</td>\n",
       "      <td>119</td>\n",
       "      <td>167.944460</td>\n",
       "      <td>39.423099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>236</td>\n",
       "      <td>12.101263</td>\n",
       "      <td>107</td>\n",
       "      <td>139.840817</td>\n",
       "      <td>34.948615</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     HP        MPG  VOL          SP         WT\n",
       "0    49  53.700681   89  104.185353  28.762059\n",
       "1    55  50.013401   92  105.461264  30.466833\n",
       "2    55  50.013401   92  105.461264  30.193597\n",
       "3    70  45.696322   92  113.461264  30.632114\n",
       "4    53  50.504232   92  104.461264  29.889149\n",
       "..  ...        ...  ...         ...        ...\n",
       "76  322  36.900000   50  169.598513  16.132947\n",
       "77  238  19.197888  115  150.576579  37.923113\n",
       "78  263  34.000000   50  151.598513  15.769625\n",
       "79  295  19.833733  119  167.944460  39.423099\n",
       "80  236  12.101263  107  139.840817  34.948615\n",
       "\n",
       "[81 rows x 5 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "cars"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "0ba19dac",
   "metadata": {},
   "outputs": [
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       "      <th></th>\n",
       "      <th>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
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       "     HP        MPG  VOL          SP         WT\n",
       "76  322  36.900000   50  169.598513  16.132947\n",
       "77  238  19.197888  115  150.576579  37.923113\n",
       "78  263  34.000000   50  151.598513  15.769625\n",
       "79  295  19.833733  119  167.944460  39.423099\n",
       "80  236  12.101263  107  139.840817  34.948615"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cars.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0433d853",
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>81.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>81.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>117.469136</td>\n",
       "      <td>34.422076</td>\n",
       "      <td>98.765432</td>\n",
       "      <td>121.540272</td>\n",
       "      <td>32.412577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>57.113502</td>\n",
       "      <td>9.131445</td>\n",
       "      <td>22.301497</td>\n",
       "      <td>14.181432</td>\n",
       "      <td>7.492813</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>49.000000</td>\n",
       "      <td>12.101263</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>99.564907</td>\n",
       "      <td>15.712859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>84.000000</td>\n",
       "      <td>27.856252</td>\n",
       "      <td>89.000000</td>\n",
       "      <td>113.829145</td>\n",
       "      <td>29.591768</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>35.152727</td>\n",
       "      <td>101.000000</td>\n",
       "      <td>118.208698</td>\n",
       "      <td>32.734518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>140.000000</td>\n",
       "      <td>39.531633</td>\n",
       "      <td>113.000000</td>\n",
       "      <td>126.404312</td>\n",
       "      <td>37.392524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>322.000000</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>169.598513</td>\n",
       "      <td>52.997752</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "</div>"
      ],
      "text/plain": [
       "               HP        MPG         VOL          SP         WT\n",
       "count   81.000000  81.000000   81.000000   81.000000  81.000000\n",
       "mean   117.469136  34.422076   98.765432  121.540272  32.412577\n",
       "std     57.113502   9.131445   22.301497   14.181432   7.492813\n",
       "min     49.000000  12.101263   50.000000   99.564907  15.712859\n",
       "25%     84.000000  27.856252   89.000000  113.829145  29.591768\n",
       "50%    100.000000  35.152727  101.000000  118.208698  32.734518\n",
       "75%    140.000000  39.531633  113.000000  126.404312  37.392524\n",
       "max    322.000000  53.700681  160.000000  169.598513  52.997752"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cars.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "42d87c1c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Boxplot\n",
    "\n",
    "sns.boxplot(x=\"MPG\",data=cars,orient=\"h\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f7a1d32",
   "metadata": {},
   "source": [
    "# Calculation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1b0f1ade",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P(MPG>38)= 0.348\n"
     ]
    }
   ],
   "source": [
    "Prob_MPG_greater_than_38=np.round(1-stats.norm.cdf(38,loc=cars.MPG.mean(),scale=cars.MPG.std()),3)\n",
    "print(\"P(MPG>38)=\",Prob_MPG_greater_than_38)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "59479bbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P(MPG<40)= 0.729\n"
     ]
    }
   ],
   "source": [
    "Prob_MPG_less_than_40=np.round(stats.norm.cdf(40,loc=cars.MPG.mean(),scale=cars.MPG.std()),3)\n",
    "print(\"P(MPG<40)=\",Prob_MPG_less_than_40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "fac4fe52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "p(MPG>20)= 0.943\n"
     ]
    }
   ],
   "source": [
    "Prob_MPG_greater_than_20 = np.round(1-stats.norm.cdf(20, loc = cars.MPG.mean(), scale = cars.MPG.std()),3)\n",
    "print('p(MPG>20)=',(Prob_MPG_greater_than_20))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "13aa28de",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P(MPG<50)= 0.956\n"
     ]
    }
   ],
   "source": [
    "Prob_MPG_less_than_50=np.around(stats.norm.cdf(50,loc=cars.MPG.mean(),scale=cars.MPG.std()),3)\n",
    "print(\"P(MPG<50)=\",(Prob_MPG_less_than_50))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b1820f95",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "P(20<MPG<50)= 0.013000000000000012\n"
     ]
    }
   ],
   "source": [
    "Prob_MPG_greater20_and_lessthan50=(Prob_MPG_less_than_50) - (Prob_MPG_greater_than_20)\n",
    "print(\"P(20<MPG<50)=\",(Prob_MPG_greater20_and_lessthan50))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6e77155",
   "metadata": {},
   "source": [
    "# "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc830a7c",
   "metadata": {},
   "source": [
    "# Question no:21-Check whether the data follows normal distribution\n",
    "### a)\tCheck whether the MPG of Cars follows Normal Distribution \n",
    "### Dataset: Cars.csv\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "76c2eeff",
   "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>HP</th>\n",
       "      <th>MPG</th>\n",
       "      <th>VOL</th>\n",
       "      <th>SP</th>\n",
       "      <th>WT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49</td>\n",
       "      <td>53.700681</td>\n",
       "      <td>89</td>\n",
       "      <td>104.185353</td>\n",
       "      <td>28.762059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.466833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>55</td>\n",
       "      <td>50.013401</td>\n",
       "      <td>92</td>\n",
       "      <td>105.461264</td>\n",
       "      <td>30.193597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>70</td>\n",
       "      <td>45.696322</td>\n",
       "      <td>92</td>\n",
       "      <td>113.461264</td>\n",
       "      <td>30.632114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>53</td>\n",
       "      <td>50.504232</td>\n",
       "      <td>92</td>\n",
       "      <td>104.461264</td>\n",
       "      <td>29.889149</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   HP        MPG  VOL          SP         WT\n",
       "0  49  53.700681   89  104.185353  28.762059\n",
       "1  55  50.013401   92  105.461264  30.466833\n",
       "2  55  50.013401   92  105.461264  30.193597\n",
       "3  70  45.696322   92  113.461264  30.632114\n",
       "4  53  50.504232   92  104.461264  29.889149"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cars.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0162ec3f",
   "metadata": {},
   "source": [
    "# Here our main agenda is whether the MPG of cars follows Normal Distribution or not."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "1bb593c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Distplot\n",
    "\n",
    "sns.distplot(cars.MPG,label=\"Cars-MPG\")\n",
    "plt.xlabel(\"MPG\")\n",
    "plt.ylabel(\"Density\")\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "084399f2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "34.42207572802469"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculating the MEAN value\n",
    "\n",
    "cars.MPG.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5cb0a19b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "35.15272697"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculating the Median Value\n",
    "\n",
    "cars.MPG.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c5687a17",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "HP     1.716216\n",
       "MPG   -0.177947\n",
       "VOL   -0.590197\n",
       "SP     1.611450\n",
       "WT    -0.614753\n",
       "dtype: float64"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Calculating the Skew\n",
    "\n",
    "cars.skew()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "46723432",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "mean, cov = [0, 0], [(1, .6), (.6, 1)]\n",
    "x, y = np.random.multivariate_normal(mean, cov, 100).T\n",
    "y += x + 1\n",
    "\n",
    "f, ax = plt.subplots(figsize=(6, 6))\n",
    "\n",
    "ax.scatter(x, y, c=\".3\")\n",
    "ax.set(xlim=(-3, 3), ylim=(-3, 3))\n",
    "\n",
    "# Plot the initial diagonal line based on the starting\n",
    "# xlims and ylims.\n",
    "diag_line, = ax.plot(ax.get_xlim(), ax.get_ylim(), ls=\"--\", c=\".3\")\n",
    "\n",
    "def on_change(axes):\n",
    "    # When this function is called it checks the current\n",
    "    # values of xlim and ylim and modifies diag_line\n",
    "    # accordingly.\n",
    "    x_lims = ax.get_xlim()\n",
    "    y_lims = ax.get_ylim()\n",
    "    diag_line.set_data(x_lims, y_lims)\n",
    "\n",
    "# Connect two callbacks to your axis instance.\n",
    "# These will call the function \"on_change\" whenever\n",
    "# xlim or ylim is changed.\n",
    "ax.callbacks.connect('xlim_changed', on_change)\n",
    "ax.callbacks.connect('ylim_changed', on_change)\n",
    "\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "29c9e7ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function matplotlib.pyplot.show(close=None, block=None)>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Hisplot\n",
    "\n",
    "plt.hist(cars[\"MPG\"],bins=20,edgecolor=\"black\")\n",
    "plt.show"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "099d852a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Boxplot\n",
    "\n",
    "plt.boxplot(x=\"MPG\",data=cars)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "b35a60ac",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# qq-plot\n",
    "\n",
    "sm.qqplot(cars[\"MPG\"])\n",
    "plt.xlabel(\"MPG\",color=\"green\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "c0e601aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Probability Plot\n",
    "\n",
    "stats.probplot(cars[\"MPG\"],dist=\"norm\",plot=plt)\n",
    "plt.xlabel(\"MPG\",color=\"black\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c324028e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(cars[\"MPG\"],kde=True,bins=10)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b5dc25e",
   "metadata": {},
   "source": [
    "# b) Check Whether the Adipose Tissue (AT) and Waist Circumference (Waist) from wc-at data set follows Normal Distribution \n",
    "### Dataset: wc-at.csv\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "5cef4b92",
   "metadata": {},
   "outputs": [],
   "source": [
    "wc_at=pd.read_csv(\"wc-at (1).csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "80741d38",
   "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>Waist</th>\n",
       "      <th>AT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>74.75</td>\n",
       "      <td>25.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>72.60</td>\n",
       "      <td>25.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>81.80</td>\n",
       "      <td>42.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>83.95</td>\n",
       "      <td>42.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>74.65</td>\n",
       "      <td>29.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>100.10</td>\n",
       "      <td>124.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>93.30</td>\n",
       "      <td>62.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>101.80</td>\n",
       "      <td>133.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>107.90</td>\n",
       "      <td>208.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>108.50</td>\n",
       "      <td>208.00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>109 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Waist      AT\n",
       "0     74.75   25.72\n",
       "1     72.60   25.89\n",
       "2     81.80   42.60\n",
       "3     83.95   42.80\n",
       "4     74.65   29.84\n",
       "..      ...     ...\n",
       "104  100.10  124.00\n",
       "105   93.30   62.20\n",
       "106  101.80  133.00\n",
       "107  107.90  208.00\n",
       "108  108.50  208.00\n",
       "\n",
       "[109 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc_at"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "a8906790",
   "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>Waist</th>\n",
       "      <th>AT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>74.75</td>\n",
       "      <td>25.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>72.60</td>\n",
       "      <td>25.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>81.80</td>\n",
       "      <td>42.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>83.95</td>\n",
       "      <td>42.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>74.65</td>\n",
       "      <td>29.84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Waist     AT\n",
       "0  74.75  25.72\n",
       "1  72.60  25.89\n",
       "2  81.80  42.60\n",
       "3  83.95  42.80\n",
       "4  74.65  29.84"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc_at.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "dd52549d",
   "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>Waist</th>\n",
       "      <th>AT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>100.1</td>\n",
       "      <td>124.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>93.3</td>\n",
       "      <td>62.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>101.8</td>\n",
       "      <td>133.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>107.9</td>\n",
       "      <td>208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>108.5</td>\n",
       "      <td>208.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     Waist     AT\n",
       "104  100.1  124.0\n",
       "105   93.3   62.2\n",
       "106  101.8  133.0\n",
       "107  107.9  208.0\n",
       "108  108.5  208.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc_at.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1b98f3ac",
   "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>Waist</th>\n",
       "      <th>AT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>109.000000</td>\n",
       "      <td>109.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>91.901835</td>\n",
       "      <td>101.894037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>13.559116</td>\n",
       "      <td>57.294763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>63.500000</td>\n",
       "      <td>11.440000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>80.000000</td>\n",
       "      <td>50.880000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>90.800000</td>\n",
       "      <td>96.540000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>137.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>121.000000</td>\n",
       "      <td>253.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Waist          AT\n",
       "count  109.000000  109.000000\n",
       "mean    91.901835  101.894037\n",
       "std     13.559116   57.294763\n",
       "min     63.500000   11.440000\n",
       "25%     80.000000   50.880000\n",
       "50%     90.800000   96.540000\n",
       "75%    104.000000  137.000000\n",
       "max    121.000000  253.000000"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc_at.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "9e52643e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Waist     91.901835\n",
       "AT       101.894037\n",
       "dtype: float64"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc_at.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "600cca5a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Waist    90.80\n",
       "AT       96.54\n",
       "dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "wc_at.median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "5bf2f9fa",
   "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>Waist</th>\n",
       "      <th>AT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>94.5</td>\n",
       "      <td>121.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>106.0</td>\n",
       "      <td>123.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>108.5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Waist     AT\n",
       "0   94.5  121.0\n",
       "1  106.0  123.0\n",
       "2  108.5    NaN"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# waist is multimodal, AT is bimodal data\n",
    "\n",
    "wc_at.mode()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "9397b89f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vvfRSs+M+Pj4MT0RERE7mRqbcSD5h/NfFi6J4zQ/UUvtfH/f29sbRo0dx8OBBvPrqq0hOTkZqauoNnXfhwoWoqKiwPnJycq75uYiIiMg1SdbzFBgYCLlc3qy3p7CwsNWVhLVabYvtFQpFk81FZTIZevbsCQAYPHgwMjIysHjxYowdO7Zd5wUAlUoFlUpl02ckIiIi1yNZz5Obmxvi4+Oxc+fOJsd37tyJESNGtPia4cOHN2u/Y8cOJCQkNJvvdDVRFK3zldpzXiIiIqJGki5VkJycjBkzZiAhIQHDhw/He++9h+zsbMyZMweAZagsLy8PGzZsAADMmTMH77zzDpKTk/HYY48hLS0Na9euxaZNm6zvuXjxYiQkJKBHjx7Q6/XYtm0bNmzYgFWrVrX5vEREREStkTQ8TZs2DSUlJXj55ZeRn5+P/v37Y9u2bYiMjAQA5OfnIzs729o+Ojoa27Ztw7x58/Duu+8iLCwMK1assK7xBAA1NTV44oknkJubC3d3d8TGxmLjxo2YNm1am89LRERE1BpuDNxOlZWV0Gg0qKio4N12RERETsIev78lv9uOiIiIyJkwPBERERHZgOGJiIiIyAYMT0REREQ2YHgiIiIisgHDExEREZENGJ6IiIiIbMDwRERERGQDhiciIiIiG0i6PQsRtezD/dnXb+TgpidGSF0CEVGHYM8TERERkQ0YnoiIiIhswPBEREREZAOGJyIiIiIbMDwRERER2YDhiYiIiMgGDE9ERERENmB4IiIiIrIBwxMRERGRDRieiIiIiGzA7VmIiFyUs2/zwy1+yFGx54mIiIjIBgxPRERERDZgeCIiIiKyAcMTERERkQ0YnoiIiIhswPBEREREZAOGJyIiIiIbMDwRERER2YDhiYiIiMgGDE9ERERENmB4IiIiIrIBwxMRERGRDRieiIiIiGzA8ERERERkA4YnIiIiIhswPBERERHZgOGJiIiIyAYMT0REREQ2YHgiIiIisgHDExEREZENGJ6IiIiIbKCQugAicg5mUUR+eT0KKuuglMvgrpQj3N8DaqVc6tKIiDoVwxMRXVOd3oTvTl/BsZxy1OpNTZ5TygX0C9NgeEwAwv09JKqQiKhzMTwRUauO5pTj6xP5qNEZAQAqhQzd/dxhMgMVdXqU1RpwNKccx3LKMaJHAJL6aaGUczYAEbk2hiciakYURXyXUYiUM4UAgCBvFSb3D0XPYC/IZYK1TW5ZHdIuluBoTjl+ulCCs1eq8dCIKPh5uklZPhFRh2J4IqImRFHENycL8OP5YgDAuD5BGBcbDIWsaY+SIAgI9/dAuL8HBnbXYGt6HoqqdXhvz0U8OjJaitKJiDoF+9eJqImUM4XW4HTXwFDc1lfbLDj9WqzWB0+M7YkgLxUq6gxY88NFXCiq7oxyiYg6HcMTEVmdK6zCrgzLUN2UwWEY3iOwza/VuCvx2OgYaH3UqNIZ8di/D6GiztBRpRIRSYbhiYgAABV1Bmw+mAMRwNAofyRGB9j8Hl4qBR4ZGQ2NuxIXi2vw5KZ0mMyi/YslIpKQ5OFp5cqViI6OhlqtRnx8PPbs2XPN9rt370Z8fDzUajViYmKwevXqJs+vWbMGo0aNgp+fH/z8/DBhwgQcOHCgSZtFixZBEIQmD61Wa/fPRuQsRFHE/w7noFZvQphGjTsHhrb7vbxUCsy4ORJqpQy7zxbhHzvO2LFSIiLpSRqeNm/ejLlz5+K5555Deno6Ro0ahUmTJiE7O7vF9pmZmZg8eTJGjRqF9PR0PPvss3jyySexZcsWa5vU1FQ8+OCDSElJQVpaGiIiIpCUlIS8vLwm79WvXz/k5+dbHydOnOjQz0rkyI7nVuBiUQ0UMgEPDou44eUGwnzd8eZ9gwAAq3ZfwKFLpfYok4jIIUganpYtW4ZHH30Us2fPRlxcHJYvX47w8HCsWrWqxfarV69GREQEli9fjri4OMyePRuPPPIIli5dam3z3//+F0888QQGDx6M2NhYrFmzBmazGbt27WryXgqFAlqt1voICgrq0M9K5KjqDSZsO5kPABjbJxgBXiq7vO9dg8JwX3x3iCLw1P+OoVZvtMv7EhFJTbLwpNfrcfjwYSQlJTU5npSUhL1797b4mrS0tGbtJ06ciEOHDsFgaHliam1tLQwGA/z9/ZscP3fuHMLCwhAdHY0HHngAFy9evGa9Op0OlZWVTR5ErmBXxhVU1RsR4OmGUb3aPkG8Lf52V1+EadTIKqnF4m2n7freRERSkSw8FRcXw2QyISQkpMnxkJAQFBQUtPiagoKCFtsbjUYUFxe3+JoFCxagW7dumDBhgvVYYmIiNmzYgG+//RZr1qxBQUEBRowYgZKSklbrXbx4MTQajfURHh7e1o9K5LBKa/RIu2j5ur9rUJjdVwf3USuxpGH47j/7snA0p9yu709EJAXJJ4wLgtDkz6IoNjt2vfYtHQeAJUuWYNOmTfj000+hVqutxydNmoSpU6diwIABmDBhAr7++msAwL///e9Wz7tw4UJUVFRYHzk5Odf/cEQOLuVMIcwi0CvYC71DvDvkHCN7BWLqTd0BAH/7/CTMvPuOiJycZOEpMDAQcrm8WS9TYWFhs96lRlqttsX2CoUCAQFNb6teunQpXnvtNezYsQMDBw68Zi2enp4YMGAAzp0712oblUoFHx+fJg8iZ1Zao0d6dhkAYHxcy99z9vLMpD7wVilwPLcCHx/iPzyIyLlJFp7c3NwQHx+PnTt3Njm+c+dOjBgxosXXDB8+vFn7HTt2ICEhAUql0nrszTffxCuvvILt27cjISHhurXodDpkZGQgNLT9t2cTOZvGXqfeIV6I8Pfo0HMFe6vxlwm9AABLvj2DilounklEzkvSYbvk5GS8//77WLduHTIyMjBv3jxkZ2djzpw5ACxDZTNnzrS2nzNnDrKyspCcnIyMjAysW7cOa9euxfz5861tlixZgueffx7r1q1DVFQUCgoKUFBQgOrqX7aKmD9/Pnbv3o3MzEzs378f9913HyorKzFr1qzO+/BEErq61+nW2I7tdWo0a0QUegV7obRGj1W7L3TKOYmIOoKk4WnatGlYvnw5Xn75ZQwePBg//PADtm3bhsjISABAfn5+kzWfoqOjsW3bNqSmpmLw4MF45ZVXsGLFCkydOtXaZuXKldDr9bjvvvsQGhpqfVy9nEFubi4efPBB9OnTB/feey/c3Nywb98+63mJXN2+iyUwi0DP4I7vdWqklMuwYFIsAGD9T5koqKjvlPMSEdmbIDbOuCabVFZWQqPRoKKigvOfyO4+3N/yQrH2oDOa8Mb206g3mDFreBT6aDtmovj0xIhmx0RRxP+tTsOhrDJMT4zAa/cM6JBzk0VHfh11hpa+hohulD1+f0t+tx0Rda707HLUG8wI8HRDrxCvTj23IAh4pqH3afPBHFwsqr7OK4iIHA/DE1EXIoqidV2n4T0CILvGsiAdZWiUP26NDYbJLOKtXa3f4UpE5KgYnoi6kAtFNSiq0sFNIcNNEX6S1ZF8W28AwJfHLiOzuEayOoiI2oPhiagLOdCwQe9NEb5QK+WS1dG/mwbjY4NhFoF3U85LVgcRUXswPBF1EbV6IzLyLXsyJkT6X6d1x/vzeMu6T1vT85BdUitxNUREbcfwRNRFHMutgMksIlSjRpivu9TlYHC4L0b3DoLJLGJlKnufiMh5MDwRdRFHsiyLYko51+nXnry1JwDg0yN5KKziuk9E5BwYnoi6gILKeuSV10EmAIPCfaUuxyohyh9DInyhN5nxn7QsqcshImoThieiLiC9odcpVusDL5VC4mqaemxUDABg474s1OlNEldDRHR9DE9ELs4sijiWWw7AsYbsGk3sp0W4vzvKag345Eiu1OUQEV0XwxORi8sqqUVlvRFqpQy9O3lF8baQywQ8cks0AGDdj5kwm7ljFBE5NoYnIhd3Iq8CANA31AcKuWN+y/9fQji81QpkFtdg1+lCqcshIromx/xJSkR2YRZF/NwQngZ000hcTeu8VArrJrBr9lyUuBoiomtjeCJyYZdKalClswzZ9Qh2vCG7qz00IgoKmYADmaU43jBHi4jIETE8EbmwE7mWXqd+oRooZI797R6qccddg8IAAGv2ZEpcDRFR6xz7pykRtZtZFHHysmU7lgHdHXfI7mqPjrRMHN92Ih955XUSV0NE1DKGJyIXlV1Si5rGIbsgxx6ya9S/mwbDYwJgMovYuI+LZnY2URRhNJmlLoPI4TnWanlEZDcZBZZep1itD+QyQeJq2m7WiCikXSzB5oM5+Mv4XlAr5VKX5NIul9dh38USXCyuQVW9AQaTiGBvFaIDPREf6Yfufh5Sl0jkcBieiFxURn4VACBW6y1xJbaZEBeMMI0alyvqse1EPu69qbvUJbmksho9tqbn4XxRdbPnCqt0KKzS4UBmKYZG+2NiXy3c3RhiiRoxPBG5oKIqHYqrdZALAnqHOFd4UshlmJ4YgaU7zuLfaVkMTx3geG45Pjuah3qDGTLBMlwaH+GHAC8VFHIBOaW1OJFXgeO5FTiQWYozBVV4dGQ0Ar1UUpdO5BA454nIBWXkW4bsYoI8nXLYa9rQCCjlAo7llHPZAjtLPVOIjw7moN5gRoS/B5Jv64MHhkagV4g3/D3d4KNWol+YBg8MjcDsUdEI8HRDRZ0B7++5iOIqndTlEzkEhiciF2Sd7xTqI3El7RPkrcLkAaEAgA1pnDhuL9+fvoIdp64AAEb3CsJjo2Lg7+nWavuYQC88PqYHgr1VqKw3Ys2PF1Feq++scokcFsMTkYup1hmRXVILAIhzsvlOV5s5PAoA8OWxyyir4S/sG/XD2SJ8l2HZ+mZi3xDc3l/bphsJvFQKzB4Vg2BvFarqjfj4UA7MIvcfpK6N4YnIxZy9UgURQKhGDV+P1nsVHN1NEb7oF+YDndGMjw/lSF2OUzudX4lvfy4AAEzsp8WYPsE2vd5LpcCMmyOhUshwqaQWKWe4/yB1bQxPRC7m7BXLXXZ9nLjXCQAEQcDM4ZEAgI37s2Ays7ejPQor67H5UA5EAMOi/TGmd1C73ifAS4W7G1aA/z6jEFklNXasksi5MDwRuRCzKOJ8oeXW897Bzh2eAODuQd2gcVcip7QOu8+yt8NWeqMZG/dnQ2c0IyrAE3cODL2h9xsS4YfB4b4QAXxx7DKH76jLYngiciF5ZXWo1ZugVsoQ7u/8ixu6u8nxf/GWpQo4cdx2207mo7haBx+1AtMTI+yyv+EdA0KhVsqQX1GP9OwyO1RJ5HwYnohcSOOQXY8gL6daVfxafnezZehu99kiXCrmUFFb7cq4ggOZpQCA++LD4aWyz7J+nioFbm2YM7Xj5yvQGU12eV8iZ8LwRORCGsOTsy2MeS1RgZ4Y0zsIogjud9dGpTV6PLPlOADglh4B6Bls370Nb44JgL+nG6p0Rvxwtsiu703kDBieiFxErc6I3LI6AK4VngBg1ghL79PHh3JQp2dPx/W8+nUGiqv1CPZWIamf1u7vr5DLcHvD+/50oYTXhLocbs9C5CLOF1VDBBDio4LGXSl1Ofhwf7bd3sssivDzUKKs1oDntp5AQpS/3d67NdMTIzr8HB3hp/PF2HIkF4IA3HtTdyjlHfNv5H5hPgjxUeFKpQ77M0sw1sblD4icGXueiFzEuSuWu+x6ucBddr8mEwQkRgcAAPZdLIHIu7xaVG8w4bmtJwAAM26OREQH3jQgCAJG97Ise7D3QgkMJnOHnYvI0TA8EbkAURRxvqgxPNl3foujSIj0g0Im4HJFPbJLa6UuxyGtSr2ASyW1CPFR4emJfTr8fAO7+0LjrkS1zoj07PIOPx+Ro2B4InIBJTV6VNQZIJcJiAzwlLqcDuGhUmBQd18Alt4naiq3rBard18AALxwZ194qzt+6FYuEzCyZyAAYM+5Iq77RF0GwxORC2hcGDPC3wNuCtf9tr45xjJ0dzKvElX1BomrcSyvbcuAzmhGYrQ/7hhwY4th2iIhyg9qpQwlNXrr1yGRq3Pdn7JEXciFhiG7HkGu2evUqJufO8L93GESRRy8xAUaG+29UIxtJwogE4BFd/eDIHTeGl8qhRxDwv0AAAcvlXbaeYmkxPBE5OTMooiLRZbFI3sGueZ8p6sN72HpfTqQWcL97gCYzSL+/lUGAMsdgnGhPp1ew9CGux8z8tkjSF0DwxORk8uvqEedwQSVQoZufs6/Jcv19A/TwNNNjsp6IzLyK6UuR3KfH8vDqfxKeKsUSL6t4yeJt0SrUSPczx1mEZw4Tl0CwxORk7vQMM8kOtDTZbZkuRaFXIah0Zaejq4+cbzeYMLSb88CAOaM7QF/TzfJamnsfTp4qZRLSZDLY3gicnK/zHdy/SG7RsOi/CEAuFhcgyuV9VKXI5kNaZeQV14HrY8aj9wSLWktA7pr4KawTBzPLOEehOTaGJ6InJjJLOJSwy+qGBefLH41Xw839A2zzO3pqr1P5bV6vPP9eQBAclJvuLvJJa1HpZBjYDcNAOBYTrmktRB1NIYnIieWV1YLg0mEh5scIT5qqcvpVI3LFqTnlKPe0PX2VluZegGV9Ub0CfHG1Ju6S10OAGBQuC8Ay1ISRjNXHCfXxfBE5MQuFlt6naICPCHrxNvTHUFMoCeCvVXQG804kt21li3ILavFB3svAQAWTIp1mLlu0YGe8FYpUGcwcc0ncmkMT0ROLLO46w3ZNRIEwdr7lHahpEutbr1sx1nojWYMjwnA2D5BUpdjJRME9O9uGbo7nlshcTVEHYfhichJmcwishr2eIsO7HrhCQBuivCDu1KOkho9zhRUSV1Opzh1uRJbj+YBABZOju3UBTHbYlDDvKdT+ZXQGzl0R66J4YnISV0ur4PeaIa7suvNd2rkppBhWMOyBT+eL5a4ms7xxvbTEEXgzoGhGNiw158jCff3gK+HEnqjGWeudI1AS10PwxORk2ocsosK7Hrzna52c0wAZILl7yOvrE7qcjrU3gvF2H22CAqZgPlJ0iyIeT2CIGBgN18AwInccklrIeooDE9ETupi8S+LY3ZlGneltQfmpwuu2/skiiLe2H4GgGUbligHvu79u1mWkThbWA2DiUN35HoYnoickMksIqvEMt8pxoF/iXaWW3oGAgCO55ajos4191bbfrIAx3LK4eEmx59v7SV1OdcU5usOH7UCeqMZF4t41x25HoYnIidUUFEPndEMtVIGraZrzne6Wjdfd0QHesIsAmku2PtkNJnx5reWXqfZI6MR5K2SuKJrkwmCdYPiU/mc90SuR/LwtHLlSkRHR0OtViM+Ph579uy5Zvvdu3cjPj4earUaMTExWL16dZPn16xZg1GjRsHPzw9+fn6YMGECDhw4cMPnJXIkWaWW+U4R/h5der7T1UY29D4duFQKndG1Fs38+FAuLhbXwN/TDY+NjpG6nDZpDE+n8yu71DIS1DVIGp42b96MuXPn4rnnnkN6ejpGjRqFSZMmITs7u8X2mZmZmDx5MkaNGoX09HQ8++yzePLJJ7FlyxZrm9TUVDz44INISUlBWloaIiIikJSUhLy8vHafl8jRNA7ZRQZwyK5RH603AjzdUG8w43CW6yyaWac3Yfl3ls1//zSuJ7zVSokrapuYIE+oFDJU6YzIdfGJ/NT1SBqeli1bhkcffRSzZ89GXFwcli9fjvDwcKxatarF9qtXr0ZERASWL1+OuLg4zJ49G4888giWLl1qbfPf//4XTzzxBAYPHozY2FisWbMGZrMZu3btavd5iRyJKIrIatjPLtLfQ+JqHIdMEKxzn/a60KKZ637KRGGVDt393PHbmyOkLqfNFDIZeod4AwAy8islrobIviQLT3q9HocPH0ZSUlKT40lJSdi7d2+Lr0lLS2vWfuLEiTh06BAMhpYnidbW1sJgMMDf37/d5yVyJOV1BlTWGyETgO5+DE9Xa1w0s7RGj5N5zr/CdXmtHqt3XwAAPJXUGyqFtJv/2qqvdd4TwxO5FsnCU3FxMUwmE0JCQpocDwkJQUFBQYuvKSgoaLG90WhEcXHLk0QXLFiAbt26YcKECe0+LwDodDpUVlY2eRBJobHXKczXHW4KyactOhQ3hQzDe1i2bNl9tgiik/c+rUy9gKp6I2K13pgyqJvU5disd4g3ZAJQVKVDWY1e6nKI7Ebyn7y/3lpAFMVrbjfQUvuWjgPAkiVLsGnTJnz66adQq5vekWTreRcvXgyNRmN9hIeHt9qWqCNZ5ztxyK5FI3oEwE0hQ35FvVOvcJ1XXmfd/PeZSbGQOcjmv7Zwd5MjvOHr9Gyh814Lol+TLDwFBgZCLpc36+0pLCxs1ivUSKvVttheoVAgICCgyfGlS5fitddew44dOzBw4MAbOi8ALFy4EBUVFdZHTk5Omz4nkb01hqcIThZvkYebAokNW7aknnHe3qflOy2b/yZG+2Nsb8fZ/NdWfRrmPZ29wvWeyHVIFp7c3NwQHx+PnTt3Njm+c+dOjBgxosXXDB8+vFn7HTt2ICEhAUrlL3egvPnmm3jllVewfft2JCQk3PB5AUClUsHHx6fJg6iz1RtMuFJZDwCIDGDPU2tu6RkIhUxAdmktLjZsY+NMfr5cgS1HcgEACyY53ua/tujVEJ4uFFXDaOZq4+QaJB22S05Oxvvvv49169YhIyMD8+bNQ3Z2NubMmQPA0tszc+ZMa/s5c+YgKysLycnJyMjIwLp167B27VrMnz/f2mbJkiV4/vnnsW7dOkRFRaGgoAAFBQWorq5u83mJHFV2aS1EAP6ebvBxklvWpeCjViIhyg8AsCvjilP1PomiiJe+OAVzw+a/QyL8pC7phoRq1PBSWVYbb+w1JXJ2CilPPm3aNJSUlODll19Gfn4++vfvj23btiEyMhIAkJ+f32TtpejoaGzbtg3z5s3Du+++i7CwMKxYsQJTp061tlm5ciX0ej3uu+++Jud68cUXsWjRojadl8hRcb5T243pHYxDl8pwqaQW5wurrT0gju6r4/k4cKkUaqUMz06Ok7qcGyYTBPQK9kJ6TjnOXqlCjyAvqUsiumGC6Ez/JHMglZWV0Gg0qKio4BAe2d2H+1tesPX9Hy/iYlENpgwOQ2J0QItt6BdfH7+Mny6UoLufO/4wpodNw1/TEzt/TaU6vQnj/5GKyxX1mDehN/4y4cb2sGvt66izHcstx+aDOQjxUeEv43u3+XVSXANyffb4/S353XZE1DYms4jcUstKzVxZvG1G9w6CUi4gt6wOpwsc/26v1bsv4HJFPbr5uuPxMc6xDUtb9AryggDgSqXOZTdupq6F4YnISRRU1ENvsmwGHOzgG8M6Cm+1EsNjLKuO7zhV4NCrjueW1VoXxHx2chzUSudaEPNaPFQKdPNzBwBcKORdd+T8GJ6InMSlEm4G3B6jewfCXSnHlUqdQ+95t3jbaegaliaYPEArdTl21zjX6XwRwxM5P4YnIieRVcrNgNvDw02BcbHBAIDvTl2BzmiSuKLm0i6U4OsT+ZAJwKK7+zn10gSt6RlsCU8Xiqqd6u5HopYwPBE5AVEUkc3NgNvt5hh/+Hu6oUpnxA9nW97KSSr1BhOe/+wEAMsE6bhQ17wBJcLfAwqZgKp6IwqrdFKXQ3RDGJ6InEB5LTcDvhEKmQy397MMhf14vgilDrTP2sqU87hQVIMgbxWeToqVupwOo5TLENXQa3qBQ3fk5BieiJxAVik3A75R/cJ8EBPoCYNJxJfHLjvE0NHpgkqsTLVMEn/57n7QeLj2wqc9ghrDk/Ot+k50Nf4UJnICXBzzxgmCgLsHh0EuCDhzpQo/X66UtB6DyYxnPjkOo1lEUt8Q3N7f9SaJ/1qPhnlPF4uqYTJLH16J2ovhicgJ5JRxM2B7CPZWY3Rvy9IFXx2/jHqDdJPH3951DsdyK6BxV+KV3/R3yUnivxbm6w61Ugad0YzL5XVSl0PUbgxPRA7OYDKjoMKyGXB4w1o51H5j+wTD39MNlfVGfH0iX5IaDl0qxTsp5wEAr90zACE+aknq6GwyQUBM4C933RE5K4YnIgeXX14Hswh4qRTQuLv2nJjOoJTLMPWm7hAAHM4qw6nLFZ16/opaA+Z9fBRmEbj3pm64Y2Bop55fajEN854a1y0jckYMT0QOLqfMMrzR3c+9SwztdIboQE+M6hUEAPg0PQ9V9Z2zZYjZLGLu5nTklNahu587Ft3dr1PO60ga77jLKqnlvCdyWgxPRA4ut2G+E5cosK8JccEI1ahRqzdh04GcTvlFvnzXOaScKYJKIcPq38XDR931ehK1GrV13lPjcDSRs2F4InJwuQ09T5zvZF8KuQzThoZDpZDhUkkNvj5xuUPP9/XxfKzYdQ6AZZ5T/26aDj2fo5IJAiL9Lb1PmRy6IyfF8ETkwGr1RpQ0LOjYjeHJ7oK91bg/IRwAsO9iKQ5mlnbIeX46X4x5m48CAB4aEYWp8d075DzOIjqwITwVMzyRc2J4InJgjb1OAZ5u8HBTSFyNa4oL9cGEOMved58dzcPx3HK7vv+xnHL8fsMh6E1mTOqvxQt39rXr+zujxvB0qbgGZgdYrJTIVvxpTOTAGuc7hXNxzA41rk8wymsNOJRVho8P5UBmp4n5P54rxuP/OYQavQkjegRg+QODIZdx0n+YrzuUcgF1BhMKq3TQdpGlGsh1sOeJyIHllP5ypx11HEEQ8Jsh3TAk3BdmEfjoYDbW/5R5Q1u4fH40Dw9/cMAanN6bmQCVQm7Hqp2XXPbLvKdLHLojJ8TwROSgRFHknXadSCYImBrfHfERfjCLwEtfnsJfPzmOGp3Rpvep0Rnx10+O4S8fHYXBJOKOAaFY//BQeKnY0X+1qEDL1zTnPZEz4nczkYMqrzWgRm+CTABCNRzW6AwyQcC9N3VDiEaN7Sfz8b/DudhzrhjP3RGHOweGXnOdLZNZxOdH8/DP784ip7QOggA8MbYHkm/rw6G6FkQHegEoxKWSGoiiyDXMyKkwPBE5qMb97EI17lDK2UncWQRBwMiegfhtYgQWfnoC2aW1+POmdCzbeRb3DumG0b2DEB3kCS83BarqjbhQXI3UM0X46thlXGzoRQnVqPHPaYNxc0yAxJ/GcXX3c4dcJqCq3nJHaaCXSuqSiNqM4YnIQeWWcb6TlG7pGYgd80bjvR8u4l+7LyCzuAb/2HkW/9h5FgAgE4Bfr6vp66HE70fHYNbwKHhymO6alHIZwv3ccamkFpeKaxieyKnwu5vIQXG+k/TUSjmeHN8Lj46MxvaTBfj82GVk5FeiqEpnDU4adyVu6RmAcX2CcXt/Lby74Krh7RUV6IlLJbXILK5BQpS/1OUQtRnDE5EDMplF5JWz58lReKoUmBrf3bq4ZVW9AbV6E3w9lLyD7gZEB3giFUXcJJicDsMTkQMqrKqHwSRCpZAhyJvDGY7GW61kD5MdRPh7QCYAZbUGlNfq4evhJnVJRG3CWahEDqhxvlM3P3e7LdhI5GhUSjnCfC09q+x9ImfC8ETkgKwri3O+E7m46ADuc0fOh+GJyAHxTjvqKqK4STA5IYYnIgdTqzfiSmU9AN5pR64vqqHnqbhab/Nq7kRSYXgicjA/X66EWQR81Apo3DkpmVybu5scwQ03RWSX1kpcDVHbMDwROZhjOeUA2OtEXUeEv+VrPauE4YmcQ7vCU2Zmpr3rIKIGR63hifOdqGuIDLCEp+xSznsi59Cu8NSzZ0+MGzcOGzduRH19vb1rIurSjuWWA2DPE3UdEf6WeU+5ZXUwms0SV0N0fe0KT8eOHcOQIUPw1FNPQavV4vHHH8eBAwfsXRtRl1NSrUNOKe+0o64l0MsNHm5yGM0i8sv5D3JyfO0KT/3798eyZcuQl5eH9evXo6CgACNHjkS/fv2wbNkyFBUV2btOoi6hsdcpyEsFtZLbflDXIAjCL/OeOGmcnMANTRhXKBS455578PHHH+ONN97AhQsXMH/+fHTv3h0zZ85Efn6+veok6hKO5lQAYK8TdT2RDeEpmyuNkxO4ofB06NAhPPHEEwgNDcWyZcswf/58XLhwAd9//z3y8vIwZcoUe9VJ1CVY77Tz53wn6loiGtZ7yi6thSiKEldDdG3t2hh42bJlWL9+Pc6cOYPJkydjw4YNmDx5MmQySxaLjo7Gv/71L8TGxtq1WCJXJoqiddgunD1P1MV083WHTAAq640orzPAj5sEkwNrV3hatWoVHnnkETz88MPQarUttomIiMDatWtvqDiiriS7tBbltQa4yWXQ+qilLoeoU7kpZAjzdUduWR2yS2oZnsihtSs87dy5ExEREdaepkaiKCInJwcRERFwc3PDrFmz7FIkUVfQuL5TXJgPFHKuXyu1D/dnS11ClxPp74HcsjpkldZiULiv1OUQtapdP6F79OiB4uLiZsdLS0sRHR19w0URdUXHGiaLD+6ukbgSImlY5z1x0jg5uHaFp9Ym81VXV0Ot5nADUXs0zncaHOEraR1EUmlcriC/oh46o0niaohaZ9OwXXJyMgDLmhx/+9vf4OHxyx1BJpMJ+/fvx+DBg+1aIFFXYDCZcTLP0vM0qLsv9l0slbgios6ncVfC112J8joDcsvqpC6HqFU2haf09HQAlp6nEydOwM3tlwl9bm5uGDRoEObPn2/fCom6gDMFVdAZzfBRKxAV4MnwRF1WRIAHynMruEkwOTSbwlNKSgoA4OGHH8Zbb70FHx+fDimKqKtpHLIbFO4LmUyQthgiCUX6e+B4bgU3CSaH1q677davX2/vOoi6tMbFMQd195W0DiKpXb1Yptks8h8T5JDaHJ7uvfdefPDBB/Dx8cG99957zbaffvrpDRdG1JU03mnH27Opq9P6qKGUC6g3mHG+qBq9Q7ylLomomTaHJ41GA0EQrP9PRPZRrTPibGEVAGAQlymgLk4uExDu54GLxTU4dKmM4YkcUpvD09VDdRy2I7Kfk3kVEEUgTKNGMFcWJ0JEgCU8Hckuw/TECKnLIWqmXes81dXVobb2lzshsrKysHz5cuzYscNuhRF1FY0ri3PIjsiicb2nI9llEldC1LJ2hacpU6Zgw4YNAIDy8nIMGzYM//jHPzBlyhSsWrXKrgUSubpjDE9ETUT4WcLTxaIalNXoJa6GqLl2hacjR45g1KhRAIBPPvkEWq0WWVlZ2LBhA1asWGHTe61cuRLR0dFQq9WIj4/Hnj17rtl+9+7diI+Ph1qtRkxMDFavXt3k+Z9//hlTp05FVFQUBEHA8uXLm73HokWLIAhCk0drGxwTdTTeaUfUlIdKgUAvFQAgPYe9T+R42hWeamtr4e1tmcS3Y8cO3HvvvZDJZLj55puRlZXV5vfZvHkz5s6di+eeew7p6ekYNWoUJk2ahOzsljfkzMzMxOTJkzFq1Cikp6fj2WefxZNPPoktW7Y0qS0mJgavv/76NQNRv379kJ+fb32cOHGizXUT2UthZT0uV9RDEIABnCxOZGUdussql7YQoha0Kzz17NkTn332GXJycvDtt98iKSkJAFBYWGjTwpnLli3Do48+itmzZyMuLg7Lly9HeHh4q0N/q1evRkREBJYvX464uDjMnj0bjzzyCJYuXWptM3ToULz55pt44IEHoFKpWj23QqGAVqu1PoKCgtpcN5G9HMu1LFHQK9gLXqp2LbtG5JI474kcWbvC09/+9jfMnz8fUVFRSExMxPDhwwFYeqGGDBnSpvfQ6/U4fPiwNXg1SkpKwt69e1t8TVpaWrP2EydOxKFDh2AwGGz6DOfOnUNYWBiio6PxwAMP4OLFi9dsr9PpUFlZ2eRBdKM4ZEfUsogAS3g6mlMOo8kscTVETbUrPN13333Izs7GoUOHsH37duvx8ePH45///Geb3qO4uBgmkwkhISFNjoeEhKCgoKDF1xQUFLTY3mg0ori4uM31JyYmYsOGDfj222+xZs0aFBQUYMSIESgpKWn1NYsXL4ZGo7E+wsPD23w+otZcvS0LEf0i2FsFb5UCtXoTzlypkrocoibaFZ4AQKvVYsiQIZDJfnmLYcOGITY21qb3aVx4s5Eois2OXa99S8evZdKkSZg6dSoGDBiACRMm4OuvvwYA/Pvf/271NQsXLkRFRYX1kZOT0+bzEbXEbBatPU+DGZ6ImpAJAgZH+AIAjmSXS1oL0a+1a5JFTU0NXn/9dezatQuFhYUwm5t2qV5vCAwAAgMDIZfLm/UyFRYWNutdaqTValtsr1AoEBAQYOOn+IWnpycGDBiAc+fOtdpGpVJdcw4Vka0uldSgst4IN4UMfbRcRZno126K8MOec8U4klWGGTdHSl0OkVW7wtPs2bOxe/duzJgxA6GhoTb1+jRyc3NDfHw8du7ciXvuucd6fOfOnZgyZUqLrxk+fDi+/PLLJsd27NiBhIQEKJVKm2topNPpkJGRYV1+gagzNA7Z9Q/zgVLe7k5gIpd1U6QfAE4aJ8fTrvD0zTff4Ouvv8Ytt9xyQydPTk7GjBkzkJCQgOHDh+O9995DdnY25syZA8AyVJaXl2ddkHPOnDl45513kJycjMceewxpaWlYu3YtNm3aZH1PvV6PU6dOWf8/Ly8PR48ehZeXF3r27AkAmD9/Pu666y5ERESgsLAQf//731FZWYlZs2bd0OchskXjZsCDw/0kroTIMTUOZ2eV1KK4Wmdd+4lIau0KT35+fvD397/hk0+bNg0lJSV4+eWXkZ+fj/79+2Pbtm2IjLR0z+bn5zdZ8yk6Ohrbtm3DvHnz8O677yIsLAwrVqzA1KlTrW0uX77c5I6/pUuXYunSpRgzZgxSU1MBALm5uXjwwQdRXFyMoKAg3Hzzzdi3b5/1vESd4ZdtWbi+E1FLNO5K9A7xwtkr1TiSVYakflzMmByDIDbOuLbBxo0b8fnnn+Pf//43PDw8OqIuh1dZWQmNRoOKigqb1rYiAgC90Yz+L34LvcmM3U+PRWSAZ5PnP9zf8kKxRF3J9MQILNhyHB8dzMGcMT2wYJJtNyQRtcQev7/b1fP0j3/8AxcuXEBISAiioqKazTc6cuRIu4oh6ipOF1RCbzLD10NpXQyQiJq7KcIPHx3M4bwncijtCk+/+c1v7FwGUddy9eKY7bnhgqiraJw0fjy3HAaTmTdXkENoV3h68cUX7V0HUZdytGGyOBfHJLq2mEBPaNyVqKgzICO/EgO5Gj85gHZH+PLycrz//vtYuHAhSktLAViG6/Ly8uxWHJGrOtqwU/xgThYnuiaZTMCQxsUyszh0R46hXeHp+PHj6N27N9544w0sXboU5eXlAICtW7di4cKF9qyPyOVU1htwoagGAPivaKI2uCnCMnR3mCuNk4NoV3hKTk7GQw89hHPnzkGtVluPT5o0CT/88IPdiiNyRSdyLUN23f3cuW4NURvENy6WyZ4nchDtCk8HDx7E448/3ux4t27dWt3Ul4gsflnfyVfSOoicxaBwX8gEIK+8Dlcq66Uuh6h94UmtVqOysrLZ8TNnziAoKOiGiyJyZdbNgDlkR9QmXioFeodY9n9k7xM5gnaFpylTpuDll1+GwWAAAAiCgOzsbCxYsKDJat9E1FzjnnbseSJqu3juc0cOpF3haenSpSgqKkJwcDDq6uowZswY9OzZE97e3nj11VftXSORyyioqMeVSh1kAtC/G1emJ2qrxknjRzhpnBxAu9Z58vHxwY8//oiUlBQcPnwYZrMZN910EyZMmGDv+ohcSuN8p94h3vBwa9e3H1GX1LhY5oncCuiMJqgUcokroq7M5p/eZrMZH3zwAT799FNcunQJgiAgOjoaWq0WoihytWSia2gcshvMITsim0QFeMDf0w2lNXr8fLnS2hNFJAWbhu1EUcTdd9+N2bNnIy8vDwMGDEC/fv2QlZWFhx56CPfcc09H1UnkEo7xTjuidhEEATdxsUxyEDb1PH3wwQf44YcfsGvXLowbN67Jc99//z1+85vfYMOGDZg5c6ZdiyRyBWaziOMNazwN4p12RDYbEuGH7zIKOWmcJGdTz9OmTZvw7LPPNgtOAHDrrbdiwYIF+O9//2u34ohcycXialTrjHBXytE7xEvqcoicjnXSeFa5tIVQl2dTeDp+/Dhuv/32Vp+fNGkSjh07dsNFEbmixs2AB3TTQMGd4YlsNihcA7lMQEFlPS6X10ldDnVhNv0ELy0tRUhISKvPh4SEoKyM3alELfllvhM3AyZqDw83BeJCGxbL5NAdScim8GQymaBQtD5NSi6Xw2g03nBRRK6Ii2MS3TjrJsGcNE4SsmnCuCiKeOihh6BStbyZqU6ns0tRRK6m3mBCRr5lSyNOFidqv/hIP2xIy+JimSQpm8LTrFmzrtuGd9oRNXcqvxIGk4gATzd093OXuhwip9XY83TqcgXqDSaolVwskzqfTeFp/fr1HVUHkUu7en0nLiRL1H7d/dwR6KVCcbUOJ/IqMDTKX+qSqAviLT9EnaBxWxYO2RHdGEEQEB/pC4CLZZJ0GJ6IOkFjeBrSsEIyEbXfL5sEMzyRNBieiDpYSbUOWSW1AHinHZE9NG4SfDirHKIoSlwNdUUMT0QdrHGJgh5BntC4K6UthsgFDOimgVIuoLhah9wyLpZJnY/hiaiDpTfcUj04nLvAE9mDWilH3zDLYrMcuiMpMDwRdTDOdyKyv5savp8OXWJ4os7H8ETUgcxmEUetPU++ktZC5Eoalyg4eKlU4kqoK2J4IupAF4urUaUzQq2UIVbrLXU5RC6jMTyduVKFijqDxNVQV8PwRNSBGreQGNjdFwo5v92I7CXIW4XoQE+IInA4i71P1Ln405yoA1nnO3HIjsjuEhqWLDiQyXlP1LkYnog6UOOddpwsTmR/Q6M574mkwfBE1EFq9UacKagEwGUKiDrCsIZ5T8dzy1FvMElcDXUlDE9EHeR4bgXMIhCqUUOrUUtdDpHLiQzwQJC3CgaTaN18m6gzMDwRdZDG+U5cooCoYwiCYO194tAddSaGJ6IOkt6w8jHnOxF1nKFRDZPGuVgmdSKGJ6IOIIoit2Uh6gQJDT1PR7LKYDJzk2DqHAxPRB0gv6IehVU6yGUCBnTTSF0OkcuKC/WBt0qBap0RGfmVUpdDXQTDE1EHaJzvFBfqDXc3ubTFELkwuUzATQ3rPXHeE3UWhieiDtA434mTxYk63jCu90SdjOGJqAP8srI45zsRdbTGfe4OZJZBFDnviToewxORnRlMZhzPrQAADOaddkQdbmB3DdzkMhRX63CppFbqcqgLYHgisrNTlyuhM5rh66FEdICn1OUQuTy1Uo6B3S03ZhzM5NAddTyGJyI7O5Rlme8UH+EHmUyQuBqirqFxn7sDnPdEnYDhicjODmdZfng33gFERB2vcaXxQwxP1AkYnojsSBRFHGpY6TiB4Ymo09wU6QdBAC6V1OJKZb3U5ZCLY3gisqPcsjoUVumglAsYxGUKiDqNxl2J/mGWeU9pF0okroZcHcMTkR0dahiy6xemgVrJxTGJOtOIHgEAgL0XiiWuhFwdwxORHXHIjkg6w63hiT1P1LEYnojs6HDDnXYJUQxPRJ1taJQ/FDIBuWV1yCnlek/UcSQPTytXrkR0dDTUajXi4+OxZ8+ea7bfvXs34uPjoVarERMTg9WrVzd5/ueff8bUqVMRFRUFQRCwfPlyu5yX6Hoq6gw4c6UKABAf6S9xNURdj6dKYd0SiUN31JEkDU+bN2/G3Llz8dxzzyE9PR2jRo3CpEmTkJ2d3WL7zMxMTJ48GaNGjUJ6ejqeffZZPPnkk9iyZYu1TW1tLWJiYvD6669Dq9Xa5bxEbXE0pxyiCEQGeCDIWyV1OURd0ggO3VEnkDQ8LVu2DI8++ihmz56NuLg4LF++HOHh4Vi1alWL7VevXo2IiAgsX74ccXFxmD17Nh555BEsXbrU2mbo0KF488038cADD0ClavkXmK3nJWqLww3ry8RzvhORZIb3CARgCU/c5446imThSa/X4/Dhw0hKSmpyPCkpCXv37m3xNWlpac3aT5w4EYcOHYLBYOiw8wKATqdDZWVlkwfR1RpXFk/gkB2RZIZE+EKlkKGoSofzhdVSl0MuSrLwVFxcDJPJhJCQkCbHQ0JCUFBQ0OJrCgoKWmxvNBpRXNy28e32nBcAFi9eDI1GY32Eh4e36XzUNRhNZhzNKQfAyeJEUlIr5RjasNo4h+6oo0g+YVwQmu79JYpis2PXa9/ScXufd+HChaioqLA+cnJybDofubaM/CrU6k3wUSvQM8hL6nKIurThXO+JOphCqhMHBgZCLpc36+0pLCxs1ivUSKvVttheoVAgICCgw84LACqVqtU5VESNi2PGR3IzYCKpNU4a33exFCazCDm/J8nOJOt5cnNzQ3x8PHbu3Nnk+M6dOzFixIgWXzN8+PBm7Xfs2IGEhAQolcoOOy/R9TTOd+JkcSLpDeimgZdKgYo6AzLyOT+V7E/SYbvk5GS8//77WLduHTIyMjBv3jxkZ2djzpw5ACxDZTNnzrS2nzNnDrKyspCcnIyMjAysW7cOa9euxfz5861t9Ho9jh49iqNHj0Kv1yMvLw9Hjx7F+fPn23xeIluIoojDlxrDEyeLE0lNIZchMbpx3hOH7sj+JBu2A4Bp06ahpKQEL7/8MvLz89G/f39s27YNkZGRAID8/Pwmay9FR0dj27ZtmDdvHt59912EhYVhxYoVmDp1qrXN5cuXMWTIEOufly5diqVLl2LMmDFITU1t03mJbJFXXoeCynooZIJ1gT4iktbwHgHYdboQey+U4Peje0hdDrkYQeRCGO1SWVkJjUaDiooK+Pj4SF0OSejzo3n4y0dHMai7Bp//aaRd3vPD/VywlWh6YkS7X3vqciUmr9gDDzc5jr2YBKVc8vujyEHY4/c3v5qIbtBB6+KYHLIjchSxWm/4eShRqzfheG651OWQi2F4IrpB+y9awlNiDMMTkaOQyQTrkgU/ned6T2RfDE9EN6C4WodzhdUQBFgnqBKRYxjRsFXLj+c4aZzsi+GJ6AY09jrFan3g6+EmcTVEdLUxvYMAAIezy1BZ37YtvIjaguGJ6Absu2gZDriZQ3ZEDifc3wMxgZ4wmUXsPc/eJ7IfhieiG/BLeGrbCvdE1LlGN/Q+7T7L8ET2w/BE1E6c70Tk+BqH7n44WwSuzEP2wvBE1E6c70Tk+BJj/OGmkCGvvA4XiqqlLodcBMMTUTulXbQMA3C+E5Hj8nBTWHuGOXRH9sLwRNRO+xp6njjficixje5lGbpLPVMocSXkKhieiNqhqEqH85zvROQUxvSxhKf9maWo1RslroZcAcMTUTvsz7TcZcf5TkSOr1ewF7r7uUNvNHO1cbILhieidmhcomA4h+yIHJ4gCBgfGwwA+P70FYmrIVfA8ETUDr/Md+KQHZEzGB8XAgDYlVHIJQvohjE8Edno6vlOwzjficgpJMb4w8NNjsIqHX6+XCl1OeTkGJ6IbNQ43ymO852InIZKIceoXpaNgndl8K47ujEMT0Q24pYsRM5pfGzD0B3nPdENYngishHnOxE5p3ENk8aP51bgSmW9xNWQM2N4IrJBYVU95zsROakgbxWGRPgCAHaeYu8TtR/DE5ENfjpv2d6hXxjnOxE5o4n9tACAb38ukLgScmYMT0Q22NOwN9aohu0eiMi5NIantAslqKg1SFwNOSuGJ6I2EkURPzb0PI3qGShxNUTUHtGBnugT4g2jWeTEcWo3hieiNjp7pRqFVTqolTLER/lJXQ4RtdPE/pbep+0nOXRH7cPwRNRGe84VAQASowOgUsglroaI2mtiP8uSBbvPFnGjYGoXhieiNtpzrnG+E4fsiJxZ31AfhPu7Q2c0Y/eZIqnLISfE8ETUBjqjybqyOCeLEzk3QRAwqX8oAOCrE/kSV0POiOGJqA0OZ5Wh3mBGsLcKvUO8pC6HiG7QnQMt4WlXxhXU6Dh0R7ZheCJqg91nLV37I3sFQhAEiashohs1oJsGkQEeqDeYses097oj2zA8EbVB6mlLeBrbJ1jiSojIHgRBsPY+fXnsssTVkLNheCK6jsvldThzpQoyARjNyeJELuOuQWEAgN1nilBRxwUzqe0YnoiuI7XhbpwhEX7ckoXIhfQJ8UavYC/oTWbudUc2YXgiuo6UM5b5EOP68C47IldiGbqz9D59fjRP4mrImTA8EV2DzmjC3oYtWTjficj1/GaIJTz9dL4YBRX1EldDzoLhiegaDl0qQ43ehCBvFfqG+khdDhHZWWSAJ4ZG+cEsAp+x94naiOGJ6BpSG4bsxvQOgkzGJQqIXNG9N3UHAGw5nAtRFCWuhpwBwxNRK0RRxHcZjfOdOGRH5KruGBgKlUKGc4XVOJFXIXU55AQYnohacaGoGpnFNXCTyzCGk8WJXJaPWomkfloAwKdHOHRH18fwRNSKnacsvU7DewTAS6WQuBoi6khTb+oGwHLXnc5okrgacnQMT0St2HmqAAAwoW+IxJUQUUcb2TMQoRo1ymoN2H6yQOpyyMExPBG1oKhKh/SccgDAhDjOdyJydQq5DPcnhAMANh3IlrgacnQMT0Qt+P70FYiiZfPQUI271OUQUSeYNjQcMgHYd7EUF4uqpS6HHBjDE1ELGuc7TYjjkB1RVxHm6269s5a9T3QtDE9Ev1KjM2LPOct+drdxvhNRlzI9MQIA8MnhXNQbOHGcWsbwRPQrKWcKoTOaERnggbhQb6nLIaJONLZPMMIaJo5/fTxf6nLIQTE8Ef3KNycsd9pM6h8KQeCq4kRdiVwm4Lc3RwIA1u/N5Irj1CKGJ6Kr1OlN+P60Zb7T5AFaiashIilMHxYBlUKGk3mVOJRVJnU55IAYnoiuknqmEHUGE7r7uWNAN43U5RCRBPw83XDPEMuimet/ypS4GnJEDE9EV9nWsDje5AEcsiPqyh66JQoA8O3PV5BXXidtMeRwGJ6IGtQbTPg+4woAYFJ/DtkRdWWxWh+M6BEAk1nE+h/Z+0RNMTwRNUg5XYgavQlhGjUGh/tKXQ4RSeyx0TEAgA8PZKO8Vi9xNeRIJA9PK1euRHR0NNRqNeLj47Fnz55rtt+9ezfi4+OhVqsRExOD1atXN2uzZcsW9O3bFyqVCn379sXWrVubPL9o0SIIgtDkodWyp6Gr++yoZTf1uwaHcciOiDC2dxDiQn1Qqzfh33uzpC6HHIik4Wnz5s2YO3cunnvuOaSnp2PUqFGYNGkSsrNbXtk1MzMTkydPxqhRo5Ceno5nn30WTz75JLZs2WJtk5aWhmnTpmHGjBk4duwYZsyYgfvvvx/79+9v8l79+vVDfn6+9XHixIkO/azk2CpqDUg5bVkY8zeDu0lcDRE5AkEQ8IexPQAAH+zNRK3eKHFF5CgkDU/Lli3Do48+itmzZyMuLg7Lly9HeHg4Vq1a1WL71atXIyIiAsuXL0dcXBxmz56NRx55BEuXLrW2Wb58OW677TYsXLgQsbGxWLhwIcaPH4/ly5c3eS+FQgGtVmt9BAUFdeRHJQe3/ed86E1m9A7xQqyWC2MSkcXk/lpEBnigrNaAjw7kSF0OOQjJwpNer8fhw4eRlJTU5HhSUhL27t3b4mvS0tKatZ84cSIOHToEg8FwzTa/fs9z584hLCwM0dHReOCBB3Dx4sVr1qvT6VBZWdnkQa7js/TLAIApg7txyI6IrBRyGR4fbel9Wr37ArdsIQAShqfi4mKYTCaEhDTdOywkJAQFBQUtvqagoKDF9kajEcXFxddsc/V7JiYmYsOGDfj222+xZs0aFBQUYMSIESgpKWm13sWLF0Oj0Vgf4eHhNn1eclwFFfXYl2m59ncPCpO4GiJyNFPju6GbrzsKq3TYuI9zn8gBJoz/+l/5oihe81/+LbX/9fHrveekSZMwdepUDBgwABMmTMDXX38NAPj3v//d6nkXLlyIiooK6yMnh923ruLzo3kQRSAh0g/h/h5Sl0NEDkalkOPPt/YEYOl94twnkiw8BQYGQi6XN+tlKiwsbNZz1Eir1bbYXqFQICAg4JptWntPAPD09MSAAQNw7ty5VtuoVCr4+Pg0eZDzE0URHx+yBOF7b+oucTVE5KimxndHZIAHiqv1vPOOoJDqxG5uboiPj8fOnTtxzz33WI/v3LkTU6ZMafE1w4cPx5dfftnk2I4dO5CQkAClUmlts3PnTsybN69JmxEjRrRai06nQ0ZGBkaNGnUjH4kcyIf7W75j89eyS2pwoagGSrmAeoOpza8joo7naN+Pw6L8kVVSixW7zsFNLoO7m/ya7acnRnRSZdTZJB22S05Oxvvvv49169YhIyMD8+bNQ3Z2NubMmQPAMlQ2c+ZMa/s5c+YgKysLycnJyMjIwLp167B27VrMnz/f2uYvf/kLduzYgTfeeAOnT5/GG2+8ge+++w5z5861tpk/fz52796NzMxM7N+/H/fddx8qKysxa9asTvvs5BgaN/0c0E0DtfLaPwiJqGsbFO6LYG8V6gwm7D5bKHU5JCHJep4AYNq0aSgpKcHLL7+M/Px89O/fH9u2bUNkZCQAID8/v8maT9HR0di2bRvmzZuHd999F2FhYVixYgWmTp1qbTNixAh89NFHeP755/HCCy+gR48e2Lx5MxITE61tcnNz8eCDD6K4uBhBQUG4+eabsW/fPut5qWvQGU04nlcBAIiP9Je4GiJydDJBwKT+Wvw7LQt7L5QgMToAfp5uUpdFEhDExhnXZJPKykpoNBpUVFRw/pMDakt3/+GsMmw5kosATzck39abSxQQ0XWJooh1P2XiQlENBnbX4IGhrQ/NcdjOMdnj97fkd9sRSeXgpVIAQHykH4MTEbWJIAiY1D8UAoDjuRXILq2VuiSSAMMTdUmXy+uQXVoLmWAJT0REbRXm644hEZafG18cy4OZAzhdDsMTdUn7LloWxewXpoG3WilxNUTkbCb2C4FaKcPl8nprLzZ1HQxP1OXU6U04llsOALg5JkDaYojIKXmrlbgtzrJ+4I6fr6BGx4UzuxKGJ+pyDmeXwWASofVRIyqAK4oTUfsMiw5AqEaNOoMJ35zMl7oc6kQMT9SlmEUR+xuG7BJj/DlRnIjaTS4TLJuJAziSXY5zV6qkLok6CcMTdSmn8ytRUqOHWinD4HBfqcshIicX4e+B4T0sw/9bj+ZBZzRJXBF1BoYn6lJ+OFcMAEiMDoBKwRXFiejG3dY3BL4eSpTXGrDj5ytSl0OdgOGJuoyskhpkl9ZCLhOs/1IkIrpRKoUc9wzuBgBIu1iC84XVEldEHY3hibqMPQ29TkPCfeHD5QmIyI56hXhjWLRlm6ctR3JRp+fwnStjeKIuoahKh4z8SgDAyJ6BEldDRK5ocv9QBHi6oaLOgC+O5UldDnUghifqElLOFEIEEKf1RrCPWupyiMgFuSlk+L+EcAgAjuVW4OODOVKXRB2E4YlcXlGVDsdyygEAtzYsakdE1BEi/D0woa/l58wLn5/EqcuVEldEHYHhiVyetdcp1AfdfN2lLoeIXNyY3kHoHeIFndGMJ/57GJX1BqlLIjtjeCKXVlhVb+11Gh8bLG0xRNQlyAQB98eHo5uvOy6V1OKZT45D5ObBLoXhiVzazlNXrL1OYex1IqJO4qFS4J3pQ6CUC/jmZAHW/3RJ6pLIjhieyGVlldTg58uVEGBZxI6IqDMNifDDc5PjAACvbcvA4axSiSsie2F4IpckiiK+OVkAAIiP9IOWd9gRkQRmjYjCHQNCYTSLePw/h5FTWit1SWQHDE/kkn6+XIns0loo5QIm8A47IpKIIAhYct9A9A31QXG1Ho98cBAVdZxA7uwYnsjl1BtM+OZkPgBgZM8g+LhzNXEiko6nSoG1DyUgxEeFc4XV+ON/j8BgMktdFt0AhidyOStTzqOs1gAftQKje3M1cSKSXqjGHWtnDYW7Uo4fzxfjb5+f5B14TozhiVzKxaJqrN59EQBw58AwqBRyiSsiIrLo302Dtx8cAkEANh3IwXs/XJS6JGonhidyGaIo4sUvfobeZEavYC/0C/ORuiQioiYm9A3BC3f0BQAs/uY0thzOlbgiag+GJ3IZ/zuUiz3niuGmkOGuQWEQBEHqkoiImnn4lig8fEsUAODpT45he8McTXIeDE/kEvLK6/DKV6cAAMm39Uagl0riioiIWiYIAl64oy/+L747zCLw503p2H22SOqyyAYMT+T0RFHEgi3HUaUzYkiELx4bFSN1SURE1ySTCXh96kDcMSAUBpOIx/9zCAcvcRFNZ8HwRE5v/U+XsOdcMVQKGZb+3yDIZRyuIyLHJ5cJ+Oe0wRjbJwj1BjMeWX8Qx3PLpS6L2oDhiZzasZxyLP4mAwDw7OQ49AjykrgiIqK2c1PIsPp38UiM9keVzojfvr8fR7LLpC6LroPhiZxWRZ0Bf9p0BAaTiNv7aTFzeKTUJRER2UytlOP9WQkYGuWHqnojZry/H/svlkhdFl0DwxM5JZNZRPLmo8gprUO4vzveuG8g764jIqflrVbi348Mw4geAajRmzBr/QHsOcdJ5I6K4Ymc0pJvT2PX6UKoFDK8O/0maLgFCxE5OQ83BdY9NBTjGuZAPfrBIXx36orUZVELGJ7I6XxyOBf/alhFfMl9AzGwu6+0BRER2YlaKce/ZiTg9n5a6E1mzNl4GP87lCN1WfQrDE/kVFLOFGLBluMAgD+N64kpg7tJXBERkX25KWR4Z/oQ/GZwGIxmEU9/chxvfXeOe+E5EIYnchqHs0rxh42HYTSLuHtQGJJv6y11SUREHUIhl2HZ/YPxh7E9AAD//O4s/vrJcRhMZokrI4DhiZzE0ZxyPLz+IOoNZoztE4R/3D8IMq7nREQuTCYT8MztsXj1nv6QCcD/DufikQ8OoqreIHVpXR7DEzm8w1ml+N37+1FZb8TQKD+s+m08lHJ+6RJR1/DbxEi8PysB7ko59pwrxj0r9+JCUbXUZXVp/A1EDm3PuSLMWHsA1Tojbo7xxwcPD4O7m1zqsoiIOtWtsSH4+PHhCPZW4XxhNaa88xO2nyyQuqwui+GJHNbHh3Lw8PqDqNWbMLJnINY/NAyeKoXUZRERSWJAdw2+enIkhkX5o1pnxJyNh7Fk+2mYzJxI3tkYnsjhmMwi3th+Gn/95DiMZhFTBodh7UMJ7HEioi4v2FuN/z6WiEduiQYArEy9gFnrDqCwql7iyroWhidyKKU1ejy0/gBWpV4AADwxtgeWTxsMlYLBiYgIAJRyGf52V1+89cBguCvl+PF8MSb+8wdsP5kvdWldBsMTOYy954txx4o92HOuGO5KOd56YDD+ensst10hImrBlMHd8PmfbkFcqA/Kag2Ys/EInvr4GCp5N16HY3giydXpTfj7V6cw/f39yK+oR3SgJ7b+cQQXwCQiuo7eId747I8j8IexPSAIwJYjuZi0fA/2ni+WujSXxvBEkvrhbBGSlu/G+z9mAgCmJ0bg6ydHIlbrI3FlRETOQaWQ45nbY/Hx48MR7u+OvPI6TH9/P/68KR0FFZwL1RF46xJJIqukBou3ncb2ny232oZq1Pj7b/pjfFyIxJURETmnoVH++OYvo7Fk+2ls3JeFL49dxvcZV/Dk+F54+JZouCnYX2IvDE/UqS6X1+G9Hy7iw/3Z0JvMkAnAzOFRmD+xD7y4DAER0Q3xUinw8pT+uD8hHH/7/CSOZJdj8Ten8fGhHMxP6oOJ/bTcncEO+NuKOsWl4hqsSr2AT9NzYTBZ1iQZ1SsQz9/RF3203hJXR0TkWvp30+CTOSOw5UguXv/mNC4U1eAP/z2CWK035k7ojYn9Qngzzg1geKIOI4oi9meW4sP92fjq+GU0ruN2c4w//nxrL4zoEcBvXiKiDiKTCfi/hHAk9dNi7Z6LWPfTJZwuqMKcjYfRN9QHT4zrgYn9tNzuqh0EURS5NGk7VFZWQqPRoKKiAj4+nNx8tSuV9fjkcC7+dygHl0pqrcfH9gnCn8b1REKUf4fX8OH+7A4/BxHRtUxPjJC6hCbKa/V4f08m1v+UiRq9CQAQ7K3CA0PD8WBiBEI17hJX2Dns8fub4amdGJ6ayimtxXcZV/BdxhWkXSix9jJ5uslx9+Aw/DYxEv27aTqtHoYnIpKao4WnRmU1eqzfewkf7s9GcbUOACATgPFxIbh7UBhujQ126a2wGJ4k1NXDU63eiPTscqRdKMF3GVdwuqCqyfNDo/xwf0I47hgYCg+3zv8mZHgiIqk5anhqpDeaseNUATbuy8K+i6XW4yqFDGN6B2HygFCM6xMMjYdSwirtzx6/vyUf6Fy5ciWio6OhVqsRHx+PPXv2XLP97t27ER8fD7VajZiYGKxevbpZmy1btqBv375QqVTo27cvtm7desPn7cpEUUROaS22nyzA4m8ycM/KnzBw0Q789v39eCflPE4XVEEmAMOi/fH8HXHY/fRY/G/OCPxfQrgkwYmIiK7PTSHDnQPD8NHvh2PnvNH4w9geiArwgM5oxo5TVzB381EMfmUH7nx7D/7+1SnsyrjC1csbSPqbbfPmzZg7dy5WrlyJW265Bf/6178wadIknDp1ChERzRN7ZmYmJk+ejMceewwbN27ETz/9hCeeeAJBQUGYOnUqACAtLQ3Tpk3DK6+8gnvuuQdbt27F/fffjx9//BGJiYntOm9XYTSZcbm8HpklNbhUXIPM4hpk5FfiVH4lquqNzdqHatRIjPbHyF5BuDU2GP6ebhJUTUREN6pXiDeeuT0Wf53YBxn5Vdh+Mh/fnCzAucJqnMyrxMm8Srz/YyYEAYgO8ERcmA/6hvqgX5gPeoV4I9RH3aWWQJB02C4xMRE33XQTVq1aZT0WFxeH3/zmN1i8eHGz9s888wy++OILZGRkWI/NmTMHx44dQ1paGgBg2rRpqKysxDfffGNtc/vtt8PPzw+bNm1q13lb4izDdmaziKp6I8pq9Sir1aO81tDw/wZcqaxHQUXDo7Ie+RV11mUEfk0pF9A7xBv9wzQYGu2PxGh/dPdzd9i75ThsR0RSc/Rhu7a4UlmPfRdLGh6lyCyuabGdm1yG7v7uiPT3QGSAJ4J9VAj2ViPIW4VgbxX8Pd3go1ZCrZRJ/nvDHr+/Jet50uv1OHz4MBYsWNDkeFJSEvbu3dvia9LS0pCUlNTk2MSJE7F27VoYDAYolUqkpaVh3rx5zdosX7683eftTJnFNfjxXBH0JhFGkxlGswiDyQyjSYTBbIbBKMJoNsNw1fP1BhNq9SbU6U2oNRh/+X+9CVX1Buvk7bZwU8gQFWD54o8O9ETvEG/0C/NBjyAvrk5LRNTFhPioMWVwN+teo8XVOpy6bBmRaPxvVkkN9CYzLhbV4GJRDYCiVt9PIRPgrVbAW62Et1oBH7USHm5yqJQyqBRyqBQyy0Np+f+4UB9MHhDaSZ+27SQLT8XFxTCZTAgJabodR0hICAoKClp8TUFBQYvtjUYjiouLERoa2mqbxvdsz3kBQKfTQafTWf9cUVEBwJJg7Wnf6ct4bssJu74nAHi4yaBxd4PGQwk/dzf4uCsQ5K2G1keFEB81QnxU0GrcoW2l67W+thrOtENSbU3V9RsREXUge/9+cARuAAZrVRisDQKGBAEATGYR+eV1yCmrQ3ZZDfLK6lFUVY/iaj1KqnUoqtKhos7yD3k9gJI6oKSN55vUX4uRkZ52/QyN1+VGBt4kn8376+47URSv2aXXUvtfH2/Le9p63sWLF+Oll15qdjw8PLzV1xARUdf1mNQFuID3ALw3u2Peu6qqChpN+5bQkSw8BQYGQi6XN+vtKSwsbNYr1Eir1bbYXqFQICAg4JptGt+zPecFgIULFyI5Odn6Z7PZjNLSUgQEcJVse6msrER4eDhycnIceh5ZV8Jr4nh4TRwPr4njudY1EUURVVVVCAsLa/f7Sxae3NzcEB8fj507d+Kee+6xHt+5cyemTJnS4muGDx+OL7/8ssmxHTt2ICEhAUql0tpm586dTeY97dixAyNGjGj3eQFApVJBpVI1Oebr69u2D0s28fHx4Q8gB8Nr4nh4TRwPr4njae2atLfHqZGkw3bJycmYMWMGEhISMHz4cLz33nvIzs7GnDlzAFh6e/Ly8rBhwwYAljvr3nnnHSQnJ+Oxxx5DWloa1q5da72LDgD+8pe/YPTo0XjjjTcwZcoUfP755/juu+/w448/tvm8RERERK2RNDxNmzYNJSUlePnll5Gfn4/+/ftj27ZtiIyMBADk5+cjO/uXW86jo6Oxbds2zJs3D++++y7CwsKwYsUK6xpPADBixAh89NFHeP755/HCCy+gR48e2Lx5s3WNp7acl4iIiKg13J6FHIZOp8PixYuxcOHCZkOkJA1eE8fDa+J4eE0cT0dfE4YnIiIiIhtw1UMiIiIiGzA8EREREdmA4YmIiIjIBgxPRERERDZgeKJOl5eXh9/97ncICAiAh4cHBg8ejMOHD1ufF0URixYtQlhYGNzd3TF27Fj8/PPPElbs2oxGI55//nlER0fD3d0dMTExePnll2E2m61teE063g8//IC77roLYWFhEAQBn332WZPn23INdDod/vznPyMwMBCenp64++67kZub24mfwnVc63oYDAY888wzGDBgADw9PREWFoaZM2fi8uXLTd6D18O+rvc9crXHH38cgiBg+fLlTY7b65owPFGnKisrwy233AKlUolvvvkGp06dwj/+8Y8mq7UvWbIEy5YtwzvvvIODBw9Cq9XitttuQ1UVN/vtCG+88QZWr16Nd955BxkZGViyZAnefPNNvP3229Y2vCYdr6amBoMGDcI777zT4vNtuQZz587F1q1b8dFHH+HHH39EdXU17rzzTphMps76GC7jWtejtrYWR44cwQsvvIAjR47g008/xdmzZ3H33Xc3acfrYV/X+x5p9Nlnn2H//v0tbr9it2siEnWiZ555Rhw5cmSrz5vNZlGr1Yqvv/669Vh9fb2o0WjE1atXd0aJXc4dd9whPvLII02O3XvvveLvfvc7URR5TaQAQNy6dav1z225BuXl5aJSqRQ/+ugja5u8vDxRJpOJ27dv77TaXdGvr0dLDhw4IAIQs7KyRFHk9ehorV2T3NxcsVu3buLJkyfFyMhI8Z///Kf1OXteE/Y8Uaf64osvkJCQgP/7v/9DcHAwhgwZgjVr1lifz8zMREFBAZKSkqzHVCoVxowZg71790pRsssbOXIkdu3ahbNnzwIAjh07hh9//BGTJ08GwGviCNpyDQ4fPgyDwdCkTVhYGPr378/r1AkqKiogCIK1F53Xo/OZzWbMmDEDTz/9NPr169fseXteE0m3Z6Gu5+LFi1i1ahWSk5Px7LPP4sCBA3jyySehUqkwc+ZMFBQUAABCQkKavC4kJARZWVlSlOzynnnmGVRUVCA2NhZyuRwmkwmvvvoqHnzwQQDgNXEAbbkGBQUFcHNzg5+fX7M2ja+njlFfX48FCxZg+vTp1k1oeT063xtvvAGFQoEnn3yyxefteU0YnqhTmc1mJCQk4LXXXgMADBkyBD///DNWrVqFmTNnWtsJgtDkdaIoNjtG9rF582Zs3LgRH374Ifr164ejR49i7ty5CAsLw6xZs6zteE2k155rwOvUsQwGAx544AGYzWasXLnyuu15PTrG4cOH8dZbb+HIkSM2//2255pw2I46VWhoKPr27dvkWFxcnHUDaK1WCwDN/hVQWFjY7F/dZB9PP/00FixYgAceeAADBgzAjBkzMG/ePCxevBgAr4kjaMs10Gq10Ov1KCsra7UN2ZfBYMD999+PzMxM7Ny509rrBPB6dLY9e/agsLAQERERUCgUUCgUyMrKwlNPPYWoqCgA9r0mDE/UqW655RacOXOmybGzZ88iMjISABAdHQ2tVoudO3dan9fr9di9ezdGjBjRqbV2FbW1tZDJmv4okMvl1qUKeE2k15ZrEB8fD6VS2aRNfn4+Tp48yevUARqD07lz5/Ddd98hICCgyfO8Hp1rxowZOH78OI4ePWp9hIWF4emnn8a3334LwL7XhMN21KnmzZuHESNG4LXXXsP999+PAwcO4L333sN7770HwDIsMXfuXLz22mvo1asXevXqhddeew0eHh6YPn26xNW7prvuuguvvvoqIiIi0K9fP6Snp2PZsmV45JFHAPCadJbq6mqcP3/e+ufMzEwcPXoU/v7+iIiIuO410Gg0ePTRR/HUU08hICAA/v7+mD9/PgYMGIAJEyZI9bGc1rWuR1hYGO677z4cOXIEX331FUwmk7VX0N/fH25ubrweHeB63yO/DrBKpRJarRZ9+vQBYOfvEdtvECS6MV9++aXYv39/UaVSibGxseJ7773X5Hmz2Sy++OKLolarFVUqlTh69GjxxIkTElXr+iorK8W//OUvYkREhKhWq8WYmBjxueeeE3U6nbUNr0nHS0lJEQE0e8yaNUsUxbZdg7q6OvFPf/qT6O/vL7q7u4t33nmnmJ2dLcGncX7Xuh6ZmZktPgdATElJsb4Hr4d9Xe975Nd+vVSBKNrvmgiiKIq2xS0iIiKirotznoiIiIhswPBEREREZAOGJyIiIiIbMDwRERER2YDhiYiIiMgGDE9ERERENmB4IiIiIrIBwxMR0XWkpqZCEASUl5dLXQoROQCGJyJyKatXr4a3tzeMRqP1WHV1NZRKJUaNGtWk7Z49eyAIAs6ePXvN9xwxYgTy8/Oh0Wiue34GLSLXx/BERC5l3LhxqK6uxqFDh6zH9uzZA61Wi4MHD6K2ttZ6PDU1FWFhYejdu/c139PNzQ1arRaCIHRY3UTkPBieiMil9OnTB2FhYUhNTbUeS01NxZQpU9CjRw/s3bu3yfFx48Zh48aNSEhIgLe3N7RaLaZPn47CwsIm7a7uTcrKysJdd90FPz8/eHp6ol+/fti2bRsuXbqEcePGAQD8/PwgCAIeeuihzvjYRNSJGJ6IyOWMHTsWKSkp1j+npKRg7NixGDNmjPW4Xq9HWloaxo0bB71ej1deeQXHjh3DZ599hszMzGuGnj/+8Y/Q6XT44YcfcOLECbzxxhvw8vJCeHg4tmzZAgA4c+YM8vPz8dZbb3XoZyWizqeQugAiInsbO3Ys5s2bB6PRiLq6OqSnp2P06NEwmUxYsWIFAGDfvn2oq6vDuHHjEBMTY31tTEwMVqxYgWHDhqG6uhpeXl7N3j87OxtTp07FgAEDrK9p5O/vDwAIDg6Gr69vB35KIpIKe56IyOWMGzcONTU1OHjwIPbs2YPevXsjODgYY8aMwcGDB1FTU4PU1FREREQgJiYG6enpmDJlCiIjI+Ht7Y2xY8cCsISkljz55JP4+9//jltuuQUvvvgijh8/3omfjoikxvBERC6nZ8+e6N69O1JSUpCSkoIxY8YAALRaLaKjo/HTTz8hJSUFt956K2pqapCUlAQvLy9s3LgRBw8exNatWwFYhvZaMnv2bFy8eBEzZszAiRMnkJCQgLfffrvTPh8RSYvhiYhc0rhx45CamorU1FRrTxIAjBkzBt9++y327duHcePG4fTp0yguLsbrr7+OUaNGITY2tslk8daEh4djzpw5+PTTT/HUU09hzZo1ACx35gGAyWTqkM9FRNJjeCIilzRu3Dj8+OOPOHr0qLXnCbCEpzVr1qC+vh7jxo1DREQE3Nzc8Pbbb+PixYv44osv8Morr1zzvefOnYtvv/0WmZmZOHLkCL7//nvExcUBACIjIyEIAr766isUFRWhurq6Qz8nEXU+hicicknjxo1DXV0devbsiZCQEOvxMWPGoKqqCj169EB4eDiCgoLwwQcf4H//+x/69u2L119/HUuXLr3me5tMJvzxj39EXFwcbr/9dvTp0wcrV64EAHTr1g0vvfQSFixYgJCQEPzpT3/q0M9JRJ1PEEVRlLoIIiIiImfBniciIiIiGzA8EREREdmA4YmIiIjIBgxPRERERDZgeCIiIiKyAcMTERERkQ0YnoiIiIhswPBEREREZAOGJyIiIiIbMDwRERER2YDhiYiIiMgGDE9ERERENvh/qIYJYJCphncAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Distplot\n",
    "\n",
    "sns.distplot(wc_at[\"Waist\"])\n",
    "plt.title(\"Histogram of Waist\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d49d5425",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Boxplot\n",
    "\n",
    "sns.boxplot(wc_at[\"Waist\"])\n",
    "plt.title(\"Boxplot of Waist\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "832fe694",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Histplot\n",
    "\n",
    "plt.hist(wc_at[\"Waist\"],edgecolor=\"brown\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "ea52e8cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Boxplot\n",
    "\n",
    "plt.boxplot(x=\"Waist\",data=wc_at,vert=False)\n",
    "plt.title(\"Waist\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "5b3b848a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sm.qqplot(wc_at[\"Waist\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9591a55a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Probability Plot\n",
    "\n",
    "stats.probplot(wc_at[\"Waist\"],dist=\"norm\",plot=plt)\n",
    "plt.xlabel(\"Waist\",color=\"red\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "38fd4079",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Distplot\n",
    "\n",
    "sns.distplot(wc_at[\"AT\"])\n",
    "plt.title(\"Histogram of AT\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1f28d5aa",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Boxplot\n",
    "\n",
    "sns.boxplot(wc_at[\"AT\"])\n",
    "plt.title(\"Boxplot of AT\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "1b445b5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# QQ-Plot\n",
    "\n",
    "sm.qqplot(wc_at[\"AT\"])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "931a4824",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Probability Plot\n",
    "\n",
    "stats.probplot(wc_at[\"AT\"],dist=\"norm\",plot=plt)\n",
    "plt.xlabel(\"AT\",color=\"red\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "662675ab",
   "metadata": {},
   "source": [
    "#  Question.no 22) \n",
    "## Calculate the Z scores of 90% confidence interval,94% confidence interval, 60% confidence interval "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c086a709",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8416212335729143"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Z-score of 60% confidence interval\n",
    "\n",
    "stats.norm.ppf(0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "29417494",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.6448536269514722"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Z-score of 90% confidence interval \n",
    "\n",
    "stats.norm.ppf(0.95)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "781930c2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.8807936081512509"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Z-score of 94% confidence interval\n",
    "\n",
    "stats.norm.ppf(0.97)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "12cf4532",
   "metadata": {},
   "source": [
    "#  Questionno: 23\n",
    "## Calculate the t scores of 95% confidence interval, 96% confidence interval, 99% confidence interval for sample size of 25"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "b6e3521a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0638985616280205"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# t scores of 95% confidence interval for sample size of 25\n",
    "\n",
    "stats.t.ppf(0.975,24) #df-n-1=24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e5a2bbd7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.1715446760080677"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# t scores of 96% confidence interval for sample size of 25\n",
    "\n",
    "stats.t.ppf(0.98,24)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f69bde5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.796939504772804"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# t scores of 99% confidence interval for sample size of 25\n",
    "\n",
    "stats.t.ppf(0.995,24)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3eafcb5f",
   "metadata": {},
   "source": [
    "#    Question no: 24 \n",
    "## A Government company claims that an average light bulb lasts 270 days. A researcher randomly selects 18 bulbs for testing. The sampled bulbs last an average of 260 days, with a standard deviation of 90 days. If the CEO's claim were true, what is the probability that 18 randomly selected bulbs would have an average life of no more than 260 days\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8bb9709a",
   "metadata": {},
   "source": [
    "### Assume Null Hypothesis is: Ho = Avg life of Bulb >= 260 days\n",
    "\n",
    "### Alternate Hypothesis is: Ha = Avg life of Bulb < 260 days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "6d853359",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.4714045207910317"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find t-scores at x=260; t=(s_mean-P_mean)/(s_SD/sqrt(n))\n",
    " \n",
    "t=(260-270)/(90/18**0.5)\n",
    "t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "3faee336",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.4714045207910317"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Method-2 \n",
    "\n",
    "t_value=(260-270)/(90/np.sqrt(18))\n",
    "t_value"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35c22589",
   "metadata": {},
   "source": [
    "### Find P(X>=260) for null hypothesis\n",
    "\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "d31c3051",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.32167411684460556"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# p_value=1-stats.t.cdf(abs(t_scores),df=n-1)... Using cdf function\n",
    "\n",
    "p_value=1-stats.t.cdf(abs(-0.4714),df=17)\n",
    "p_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "5df3df48",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.32167253567098353"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  Method-2\n",
    "\n",
    "1-stats.t.cdf(abs(t_value),df = 17)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "094629c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.32167411684460556"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# p_value=1-stats.t.cdf(abs(t_scores),df=n-1)... Using cdf function\n",
    "\n",
    "p_value=1-stats.t.cdf(abs(-0.4714),df=17)\n",
    "p_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd83d583",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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