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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "e01ffb59-8ea2-4552-93a0-a70b280aeb0f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import scipy.stats as st\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "a47f855a-8a06-4f4f-ba86-2f8db6078eba",
+   "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>Name</th>\n",
+       "      <th>Type 1</th>\n",
+       "      <th>Type 2</th>\n",
+       "      <th>HP</th>\n",
+       "      <th>Attack</th>\n",
+       "      <th>Defense</th>\n",
+       "      <th>Sp. Atk</th>\n",
+       "      <th>Sp. Def</th>\n",
+       "      <th>Speed</th>\n",
+       "      <th>Generation</th>\n",
+       "      <th>Legendary</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Bulbasaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>45</td>\n",
+       "      <td>49</td>\n",
+       "      <td>49</td>\n",
+       "      <td>65</td>\n",
+       "      <td>65</td>\n",
+       "      <td>45</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Ivysaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>60</td>\n",
+       "      <td>62</td>\n",
+       "      <td>63</td>\n",
+       "      <td>80</td>\n",
+       "      <td>80</td>\n",
+       "      <td>60</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Venusaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>80</td>\n",
+       "      <td>82</td>\n",
+       "      <td>83</td>\n",
+       "      <td>100</td>\n",
+       "      <td>100</td>\n",
+       "      <td>80</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Mega Venusaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>80</td>\n",
+       "      <td>100</td>\n",
+       "      <td>123</td>\n",
+       "      <td>122</td>\n",
+       "      <td>120</td>\n",
+       "      <td>80</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Charmander</td>\n",
+       "      <td>Fire</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>39</td>\n",
+       "      <td>52</td>\n",
+       "      <td>43</td>\n",
+       "      <td>60</td>\n",
+       "      <td>50</td>\n",
+       "      <td>65</td>\n",
+       "      <td>1</td>\n",
+       "      <td>False</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>795</th>\n",
+       "      <td>Diancie</td>\n",
+       "      <td>Rock</td>\n",
+       "      <td>Fairy</td>\n",
+       "      <td>50</td>\n",
+       "      <td>100</td>\n",
+       "      <td>150</td>\n",
+       "      <td>100</td>\n",
+       "      <td>150</td>\n",
+       "      <td>50</td>\n",
+       "      <td>6</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>796</th>\n",
+       "      <td>Mega Diancie</td>\n",
+       "      <td>Rock</td>\n",
+       "      <td>Fairy</td>\n",
+       "      <td>50</td>\n",
+       "      <td>160</td>\n",
+       "      <td>110</td>\n",
+       "      <td>160</td>\n",
+       "      <td>110</td>\n",
+       "      <td>110</td>\n",
+       "      <td>6</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>797</th>\n",
+       "      <td>Hoopa Confined</td>\n",
+       "      <td>Psychic</td>\n",
+       "      <td>Ghost</td>\n",
+       "      <td>80</td>\n",
+       "      <td>110</td>\n",
+       "      <td>60</td>\n",
+       "      <td>150</td>\n",
+       "      <td>130</td>\n",
+       "      <td>70</td>\n",
+       "      <td>6</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>798</th>\n",
+       "      <td>Hoopa Unbound</td>\n",
+       "      <td>Psychic</td>\n",
+       "      <td>Dark</td>\n",
+       "      <td>80</td>\n",
+       "      <td>160</td>\n",
+       "      <td>60</td>\n",
+       "      <td>170</td>\n",
+       "      <td>130</td>\n",
+       "      <td>80</td>\n",
+       "      <td>6</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>799</th>\n",
+       "      <td>Volcanion</td>\n",
+       "      <td>Fire</td>\n",
+       "      <td>Water</td>\n",
+       "      <td>80</td>\n",
+       "      <td>110</td>\n",
+       "      <td>120</td>\n",
+       "      <td>130</td>\n",
+       "      <td>90</td>\n",
+       "      <td>70</td>\n",
+       "      <td>6</td>\n",
+       "      <td>True</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>800 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               Name   Type 1  Type 2  HP  Attack  Defense  Sp. Atk  Sp. Def  \\\n",
+       "0         Bulbasaur    Grass  Poison  45      49       49       65       65   \n",
+       "1           Ivysaur    Grass  Poison  60      62       63       80       80   \n",
+       "2          Venusaur    Grass  Poison  80      82       83      100      100   \n",
+       "3     Mega Venusaur    Grass  Poison  80     100      123      122      120   \n",
+       "4        Charmander     Fire     NaN  39      52       43       60       50   \n",
+       "..              ...      ...     ...  ..     ...      ...      ...      ...   \n",
+       "795         Diancie     Rock   Fairy  50     100      150      100      150   \n",
+       "796    Mega Diancie     Rock   Fairy  50     160      110      160      110   \n",
+       "797  Hoopa Confined  Psychic   Ghost  80     110       60      150      130   \n",
+       "798   Hoopa Unbound  Psychic    Dark  80     160       60      170      130   \n",
+       "799       Volcanion     Fire   Water  80     110      120      130       90   \n",
+       "\n",
+       "     Speed  Generation  Legendary  \n",
+       "0       45           1      False  \n",
+       "1       60           1      False  \n",
+       "2       80           1      False  \n",
+       "3       80           1      False  \n",
+       "4       65           1      False  \n",
+       "..     ...         ...        ...  \n",
+       "795     50           6       True  \n",
+       "796    110           6       True  \n",
+       "797     70           6       True  \n",
+       "798     80           6       True  \n",
+       "799     70           6       True  \n",
+       "\n",
+       "[800 rows x 11 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(\"https://raw.githubusercontent.com/data-bootcamp-v4/data/main/pokemon.csv\")\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "de2fe498-2618-422f-a9f3-f89b72da1c55",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### h0: mean hp of dragon == mean hp of grass \n",
+    "### h1: mean hp of dragon != mean hp of grass "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d4006558-ab6c-4c5b-84c0-ac9f7174709f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.stats import ttest_ind"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "fb75bad9-b595-4b6f-b170-6c3a7b02611e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t-statistic: 3.3349632905124063\n",
+      "p-value: 0.0007993609745420599\n"
+     ]
+    }
+   ],
+   "source": [
+    "hp_dragon = df[df['Type 1'] == 'Dragon']['HP']\n",
+    "hp_grass = df[df['Type 1'] == 'Grass']['HP']\n",
+    "\n",
+    "t_stat, p_val = ttest_ind(hp_dragon, hp_grass, equal_var=False, alternative='greater')\n",
+    "\n",
+    "print(\"t-statistic:\", t_stat)\n",
+    "print(\"p-value:\", p_val)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "a541e6f4-ed7b-4ac7-ab83-27d1afa267ba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### reject the null hypothesis, there is statistical evidence to support that dragon type has higher HP "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "efa8bb3e-fa7b-40c1-ad4b-6f1f5d3c1bb9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### h0: mean stats of legendary == stats of non-legendary \n",
+    "### h1: mean stats of legendary != stats of non-legendary"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "68c085cb-96a7-4c8b-9ece-4f413710e0d7",
+   "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>Attack</th>\n",
+       "      <th>Defense</th>\n",
+       "      <th>Sp. Atk</th>\n",
+       "      <th>Sp. Def</th>\n",
+       "      <th>Speed</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>t-statistic</th>\n",
+       "      <td>8.981370e+00</td>\n",
+       "      <td>1.043813e+01</td>\n",
+       "      <td>7.637078e+00</td>\n",
+       "      <td>1.341745e+01</td>\n",
+       "      <td>1.001570e+01</td>\n",
+       "      <td>1.147504e+01</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>p-value</th>\n",
+       "      <td>1.002691e-13</td>\n",
+       "      <td>2.520372e-16</td>\n",
+       "      <td>4.826998e-11</td>\n",
+       "      <td>1.551461e-21</td>\n",
+       "      <td>2.294933e-15</td>\n",
+       "      <td>1.049016e-18</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                       HP        Attack       Defense       Sp. Atk  \\\n",
+       "t-statistic  8.981370e+00  1.043813e+01  7.637078e+00  1.341745e+01   \n",
+       "p-value      1.002691e-13  2.520372e-16  4.826998e-11  1.551461e-21   \n",
+       "\n",
+       "                  Sp. Def         Speed  \n",
+       "t-statistic  1.001570e+01  1.147504e+01  \n",
+       "p-value      2.294933e-15  1.049016e-18  "
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "stats_columns = ['HP', 'Attack', 'Defense', 'Sp. Atk', 'Sp. Def', 'Speed']\n",
+    "\n",
+    "legendary = df[df['Legendary'] == True]\n",
+    "non_legendary = df[df['Legendary'] == False]\n",
+    "\n",
+    "results = {}\n",
+    "for col in stats_columns:\n",
+    "    t_stat, p_val = ttest_ind(legendary[col], non_legendary[col], equal_var=False)\n",
+    "    results[col] = {'t-statistic': t_stat, 'p-value': p_val}\n",
+    "\n",
+    "pd.DataFrame(results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c944ad75-bc98-45f1-8fd2-5c7f6d401c45",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### reject the null hypothesis, there is statistical evidence to support that legendary pokemon\n",
+    "### have higher stats in all categories than non-legendary pokemon"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "e9df60ad-8a06-4a09-8728-f1499dcb2d79",
+   "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>longitude</th>\n",
+       "      <th>latitude</th>\n",
+       "      <th>housing_median_age</th>\n",
+       "      <th>total_rooms</th>\n",
+       "      <th>total_bedrooms</th>\n",
+       "      <th>population</th>\n",
+       "      <th>households</th>\n",
+       "      <th>median_income</th>\n",
+       "      <th>median_house_value</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>-114.31</td>\n",
+       "      <td>34.19</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>5612.0</td>\n",
+       "      <td>1283.0</td>\n",
+       "      <td>1015.0</td>\n",
+       "      <td>472.0</td>\n",
+       "      <td>1.4936</td>\n",
+       "      <td>66900.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>-114.47</td>\n",
+       "      <td>34.40</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>7650.0</td>\n",
+       "      <td>1901.0</td>\n",
+       "      <td>1129.0</td>\n",
+       "      <td>463.0</td>\n",
+       "      <td>1.8200</td>\n",
+       "      <td>80100.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>-114.56</td>\n",
+       "      <td>33.69</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>720.0</td>\n",
+       "      <td>174.0</td>\n",
+       "      <td>333.0</td>\n",
+       "      <td>117.0</td>\n",
+       "      <td>1.6509</td>\n",
+       "      <td>85700.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>-114.57</td>\n",
+       "      <td>33.64</td>\n",
+       "      <td>14.0</td>\n",
+       "      <td>1501.0</td>\n",
+       "      <td>337.0</td>\n",
+       "      <td>515.0</td>\n",
+       "      <td>226.0</td>\n",
+       "      <td>3.1917</td>\n",
+       "      <td>73400.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>-114.57</td>\n",
+       "      <td>33.57</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>1454.0</td>\n",
+       "      <td>326.0</td>\n",
+       "      <td>624.0</td>\n",
+       "      <td>262.0</td>\n",
+       "      <td>1.9250</td>\n",
+       "      <td>65500.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   longitude  latitude  housing_median_age  total_rooms  total_bedrooms  \\\n",
+       "0    -114.31     34.19                15.0       5612.0          1283.0   \n",
+       "1    -114.47     34.40                19.0       7650.0          1901.0   \n",
+       "2    -114.56     33.69                17.0        720.0           174.0   \n",
+       "3    -114.57     33.64                14.0       1501.0           337.0   \n",
+       "4    -114.57     33.57                20.0       1454.0           326.0   \n",
+       "\n",
+       "   population  households  median_income  median_house_value  \n",
+       "0      1015.0       472.0         1.4936             66900.0  \n",
+       "1      1129.0       463.0         1.8200             80100.0  \n",
+       "2       333.0       117.0         1.6509             85700.0  \n",
+       "3       515.0       226.0         3.1917             73400.0  \n",
+       "4       624.0       262.0         1.9250             65500.0  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df = pd.read_csv(\"https://raw.githubusercontent.com/data-bootcamp-v4/data/main/california_housing.csv\")\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "e745a5ae-1f88-4792-b1b3-5239ab2f4abb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### h0: the mean median_house_value close to school/hospital is == the mean median_house_value far to school/hospital \n",
+    "### h1: he mean median_house_value close to school/hospital is != the mean median_house_value far to school/hospital"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "6b24143f-3a18-469d-9b89-e24f7aa50a4d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "### coords\n",
+    "school = (-118, 34)\n",
+    "hospital = (-122, 37)\n",
+    "\n",
+    "### function for euclidean distance\n",
+    "def euclidean_distance(lon, lat, point):\n",
+    "    return np.sqrt((lon - point[0])**2 + (lat - point[1])**2)\n",
+    "\n",
+    "### distances to school and hospital\n",
+    "df['dist_school'] = euclidean_distance(df['longitude'], df['latitude'], school)\n",
+    "df['dist_hospital'] = euclidean_distance(df['longitude'], df['latitude'], hospital)\n",
+    "\n",
+    "### finding out if house is \"close\" (<0.50)\n",
+    "df['close_to_facility'] = ((df['dist_school'] < 0.50) | (df['dist_hospital'] < 0.50))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "85873427-e2eb-47eb-ad68-d1933b6e4e1f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### split df to close and far\n",
+    "close_houses = df[df['close_to_facility'] == True]['median_house_value']\n",
+    "far_houses = df[df['close_to_facility'] == False]['median_house_value']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "f9fc8e5e-7b22-4cca-a929-fa268ff7030c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "t-statistic: 37.992330214201516\n",
+      "p-value: 1.5032478884296307e-301\n"
+     ]
+    }
+   ],
+   "source": [
+    "t_stat, p_val = ttest_ind(close_houses, far_houses, equal_var=False, alternative='greater')\n",
+    "\n",
+    "print(\"t-statistic:\", t_stat)\n",
+    "print(\"p-value:\", p_val)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "5eed0b7e-893b-4660-aef4-42597d94cf31",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "### reject the null hypothesis, there is really strong statistical evidence to support that houses close to a school or hospital are \n",
+    "### much more expensive than houses farther away"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e5366d1b-8718-4e95-85bc-33599391d24a",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:base] *",
+   "language": "python",
+   "name": "conda-base-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}