diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index cdc1acb..ba11aee 100644
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -14,12 +14,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
     "# import numpy and pandas\n",
-    "\n"
+    "import pandas as pd\n",
+    "import numpy as np"
    ]
   },
   {
@@ -35,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -53,12 +54,155 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "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>#</th>\n",
+       "      <th>Name</th>\n",
+       "      <th>Type 1</th>\n",
+       "      <th>Type 2</th>\n",
+       "      <th>Total</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>1</td>\n",
+       "      <td>Bulbasaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>318</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>2</td>\n",
+       "      <td>Ivysaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>405</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>3</td>\n",
+       "      <td>Venusaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>525</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>3</td>\n",
+       "      <td>VenusaurMega Venusaur</td>\n",
+       "      <td>Grass</td>\n",
+       "      <td>Poison</td>\n",
+       "      <td>625</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>4</td>\n",
+       "      <td>Charmander</td>\n",
+       "      <td>Fire</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>309</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",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   #                   Name Type 1  Type 2  Total  HP  Attack  Defense  \\\n",
+       "0  1              Bulbasaur  Grass  Poison    318  45      49       49   \n",
+       "1  2                Ivysaur  Grass  Poison    405  60      62       63   \n",
+       "2  3               Venusaur  Grass  Poison    525  80      82       83   \n",
+       "3  3  VenusaurMega Venusaur  Grass  Poison    625  80     100      123   \n",
+       "4  4             Charmander   Fire     NaN    309  39      52       43   \n",
+       "\n",
+       "   Sp. Atk  Sp. Def  Speed  Generation  Legendary  \n",
+       "0       65       65     45           1      False  \n",
+       "1       80       80     60           1      False  \n",
+       "2      100      100     80           1      False  \n",
+       "3      122      120     80           1      False  \n",
+       "4       60       50     65           1      False  "
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "\n",
+    "pokemon.head()"
    ]
   },
   {
@@ -70,12 +214,60 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "#              int64\n",
+       "Name          object\n",
+       "Type 1        object\n",
+       "Type 2        object\n",
+       "Total          int64\n",
+       "HP             int64\n",
+       "Attack         int64\n",
+       "Defense        int64\n",
+       "Sp. Atk        int64\n",
+       "Sp. Def        int64\n",
+       "Speed          int64\n",
+       "Generation     int64\n",
+       "Legendary       bool\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pokemon.dtypes"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Legendary\n",
+       "False    735\n",
+       "True      65\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "legendary_count = pokemon['Legendary'].value_counts()\n",
+    "legendary_count"
    ]
   },
   {
@@ -87,12 +279,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "legendary_mean is :645.25\n",
+      "legendary_std is :59.7\n",
+      "\n",
+      "non_legendary_mean is :436.45\n",
+      "non_legendary_std is :107.59\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "legendary = pokemon[pokemon[\"Legendary\"] == True].dropna()\n",
+    "non_legendary = pokemon[pokemon[\"Legendary\"] == False].dropna()\n",
+    "\n",
+    "legendary_mean = legendary[\"Total\"].mean()\n",
+    "legendary_std = legendary[\"Total\"].std()\n",
+    "\n",
+    "non_legendary_mean = non_legendary[\"Total\"].mean()\n",
+    "non_legendary_std = non_legendary[\"Total\"].std()\n",
+    "\n",
+    "print(f\"legendary_mean is :{round(legendary_mean,2)}\")\n",
+    "print(f\"legendary_std is :{round(legendary_std,2)}\")\n",
+    "print()\n",
+    "print(f\"non_legendary_mean is :{round(non_legendary_mean,2)}\")\n",
+    "print(f\"non_legendary_std is :{round(non_legendary_std,2)}\")"
    ]
   },
   {
@@ -106,12 +323,35 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tstatistics: 25.83357\n",
+      "P-value: 0.00000\n",
+      "The points difference between legendary and non-legendary Pokemon is statistically significant.\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "from scipy.stats import ttest_ind\n",
+    "\n",
+    "legendary_points = pokemon[pokemon[\"Legendary\"] == True][\"Total\"].dropna()\n",
+    "non_legendary_points = pokemon[pokemon[\"Legendary\"] == False][\"Total\"].dropna()\n",
+    "\n",
+    "t_stat, p_value = ttest_ind(legendary_points, non_legendary_points, equal_var=False)\n",
+    "\n",
+    "print(f\"Tstatistics: {t_stat:.5f}\")\n",
+    "print(f\"P-value: {p_value:.5f}\")\n",
+    "\n",
+    "if p_value < 0.05:\n",
+    "    print(\"The points difference between legendary and non-legendary Pokemon is statistically significant.\")\n",
+    "else:\n",
+    "    print(\"The points difference between legendary and non-legendary Pokemon is not statistically significant.\")"
    ]
   },
   {
@@ -123,12 +363,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Your conclusions here:\n",
-    "\n"
+    "\n",
+    "# From our sample we can conclude that in the sample the difference between points from legendary and non-legendary Pokemon´s \n",
+    "#    are statistical significance since the P-value is less (0%) than 5% (confidence Level).\n",
+    "#    Also the standard deviation of the Total points is bigger on non-legendary Pokemon."
    ]
   },
   {
@@ -140,12 +383,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Type 1\n",
+       "Water       112\n",
+       "Normal       98\n",
+       "Grass        70\n",
+       "Bug          69\n",
+       "Psychic      57\n",
+       "Fire         52\n",
+       "Electric     44\n",
+       "Rock         44\n",
+       "Dragon       32\n",
+       "Ground       32\n",
+       "Ghost        32\n",
+       "Dark         31\n",
+       "Poison       28\n",
+       "Steel        27\n",
+       "Fighting     27\n",
+       "Ice          24\n",
+       "Fairy        17\n",
+       "Flying        4\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "type_1 = pokemon['Type 1'].value_counts()\n",
+    "type_1"
    ]
   },
   {
@@ -157,12 +431,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "water_mean is :449.06\n",
+      "water_std is :109.27\n",
+      "\n",
+      "non_water_mean is :457.74\n",
+      "non_water_std is :122.56\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "water_pokemon = pokemon[pokemon[\"Type 1\"] == \"Water\"].dropna()\n",
+    "non_water_pokemon = pokemon[pokemon[\"Type 1\"] != \"Water\"].dropna()\n",
+    "\n",
+    "water_mean = water_pokemon[\"Total\"].mean()\n",
+    "water_std = water_pokemon[\"Total\"].std()\n",
+    "\n",
+    "non_water_mean = non_water_pokemon[\"Total\"].mean()\n",
+    "non_water_std = non_water_pokemon[\"Total\"].std()\n",
+    "\n",
+    "print(f\"water_mean is :{round(water_mean,2)}\")\n",
+    "print(f\"water_std is :{round(water_std,2)}\")\n",
+    "print()\n",
+    "print(f\"non_water_mean is :{round(non_water_mean,2)}\")\n",
+    "print(f\"non_water_std is :{round(non_water_std,2)}\")"
    ]
   },
   {
@@ -174,12 +473,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tstatistics: 13.25402\n",
+      "P-value: 0.00000\n",
+      "The mean of the points difference between for water Pokemon to all non-water Pokemon is statistically significant.\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "water_pokemon = pokemon[pokemon[\"Type 1\"] == \"Water\"][\"Total\"].dropna()\n",
+    "non_water_pokemon = pokemon[pokemon[\"Type 1\"] != \"Water\"][\"Total\"].dropna()\n",
+    "\n",
+    "t_stat, p_value = ttest_ind(legendary_points, non_water_pokemon, equal_var=True)\n",
+    "\n",
+    "print(f\"Tstatistics: {t_stat:.5f}\")\n",
+    "print(f\"P-value: {p_value:.5f}\")\n",
+    "\n",
+    "if p_value < 0.05:\n",
+    "    print(\"The mean of the points difference between for water Pokemon to all non-water Pokemon is statistically significant.\")\n",
+    "else:\n",
+    "    print(\"The mean of the points difference between for water Pokemon to all non-water Pokemon is not statistically significant.\")"
    ]
   },
   {
@@ -191,12 +511,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Your conclusions here:\n",
-    "\n"
+    "# The P-value is the \"same\" as the differnce between legendary and non-legendary Pokemon with a P-value of 0. \n",
+    "# howhever the mean beteween watwr and non water is very similar\n"
    ]
   },
   {
@@ -210,12 +531,194 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "metadata": {},
-   "outputs": [],
+   "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>count</th>\n",
+       "      <th>mean</th>\n",
+       "      <th>std</th>\n",
+       "      <th>min</th>\n",
+       "      <th>25%</th>\n",
+       "      <th>50%</th>\n",
+       "      <th>75%</th>\n",
+       "      <th>max</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>#</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>362.81375</td>\n",
+       "      <td>208.343798</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>184.75</td>\n",
+       "      <td>364.5</td>\n",
+       "      <td>539.25</td>\n",
+       "      <td>721.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Total</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>435.10250</td>\n",
+       "      <td>119.963040</td>\n",
+       "      <td>180.0</td>\n",
+       "      <td>330.00</td>\n",
+       "      <td>450.0</td>\n",
+       "      <td>515.00</td>\n",
+       "      <td>780.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>HP</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>69.25875</td>\n",
+       "      <td>25.534669</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>50.00</td>\n",
+       "      <td>65.0</td>\n",
+       "      <td>80.00</td>\n",
+       "      <td>255.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Attack</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>79.00125</td>\n",
+       "      <td>32.457366</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>55.00</td>\n",
+       "      <td>75.0</td>\n",
+       "      <td>100.00</td>\n",
+       "      <td>190.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Defense</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>73.84250</td>\n",
+       "      <td>31.183501</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>50.00</td>\n",
+       "      <td>70.0</td>\n",
+       "      <td>90.00</td>\n",
+       "      <td>230.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Sp. Atk</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>72.82000</td>\n",
+       "      <td>32.722294</td>\n",
+       "      <td>10.0</td>\n",
+       "      <td>49.75</td>\n",
+       "      <td>65.0</td>\n",
+       "      <td>95.00</td>\n",
+       "      <td>194.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Sp. Def</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>71.90250</td>\n",
+       "      <td>27.828916</td>\n",
+       "      <td>20.0</td>\n",
+       "      <td>50.00</td>\n",
+       "      <td>70.0</td>\n",
+       "      <td>90.00</td>\n",
+       "      <td>230.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Speed</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>68.27750</td>\n",
+       "      <td>29.060474</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>45.00</td>\n",
+       "      <td>65.0</td>\n",
+       "      <td>90.00</td>\n",
+       "      <td>180.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Generation</th>\n",
+       "      <td>800.0</td>\n",
+       "      <td>3.32375</td>\n",
+       "      <td>1.661290</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>2.00</td>\n",
+       "      <td>3.0</td>\n",
+       "      <td>5.00</td>\n",
+       "      <td>6.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "            count       mean         std    min     25%    50%     75%    max\n",
+       "#           800.0  362.81375  208.343798    1.0  184.75  364.5  539.25  721.0\n",
+       "Total       800.0  435.10250  119.963040  180.0  330.00  450.0  515.00  780.0\n",
+       "HP          800.0   69.25875   25.534669    1.0   50.00   65.0   80.00  255.0\n",
+       "Attack      800.0   79.00125   32.457366    5.0   55.00   75.0  100.00  190.0\n",
+       "Defense     800.0   73.84250   31.183501    5.0   50.00   70.0   90.00  230.0\n",
+       "Sp. Atk     800.0   72.82000   32.722294   10.0   49.75   65.0   95.00  194.0\n",
+       "Sp. Def     800.0   71.90250   27.828916   20.0   50.00   70.0   90.00  230.0\n",
+       "Speed       800.0   68.27750   29.060474    5.0   45.00   65.0   90.00  180.0\n",
+       "Generation  800.0    3.32375    1.661290    1.0    2.00    3.0    5.00    6.0"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pokemon.describe().T"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tstatistics: 4.32557\n",
+      "P-value: 0.00002\n",
+      " Reject null Hypotheses: The defense and attack scores are significant different.\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "from scipy.stats import ttest_rel\n",
+    "\n",
+    "t_stat, p_value = ttest_rel(pokemon[\"Attack\"], pokemon[\"Defense\"])\n",
+    "\n",
+    "print(f\"Tstatistics: {t_stat:.5f}\")\n",
+    "print(f\"P-value: {p_value:.5f}\")\n",
+    "\n",
+    "if p_value < 0.05:\n",
+    "    print(\" Reject null Hypotheses: The defense and attack scores are significant different.\")\n",
+    "else:\n",
+    "    print(\" Fail to Reject null Hypotheses: The defense and attack scores aren´t significant different.\")"
    ]
   },
   {
@@ -227,12 +730,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Your conclusions here:\n",
-    "\n"
+    "# since the p-value is less than the aplha = 0.05 we say that defense and attack scores arent´t correlated\n"
    ]
   },
   {
@@ -244,12 +747,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 30,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tstatistics: 0.85399\n",
+      "P-value: 0.39337\n",
+      "Fail to Reject null Hypotheses: The defense and attack scores aren´t significant different.\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "\n",
+    "t_stat, p_value = ttest_rel(pokemon[\"Sp. Atk\"], pokemon[\"Sp. Def\"])\n",
+    "\n",
+    "print(f\"Tstatistics: {t_stat:.5f}\")\n",
+    "print(f\"P-value: {p_value:.5f}\")\n",
+    "\n",
+    "if p_value < 0.05:\n",
+    "    print(\"Reject the Null Hypoteses: The defense and attack scores are significant different.\")\n",
+    "else:\n",
+    "    print(\"Fail to Reject null Hypotheses: The defense and attack scores aren´t significant different.\")"
    ]
   },
   {
@@ -261,12 +783,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
     "# Your conclusions here:\n",
-    "\n"
+    "# This indicates that there is no statistically significant difference between special attack and special defense scores in this sample"
    ]
   },
   {
@@ -280,13 +802,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 34,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Tstatistics: -4.32557\n",
+      "P-value: 0.00002\n",
+      "Reject the Null Hypoteses: The mean difference is sgnificantly different from 0.\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "    \n",
-    "    "
+    "from scipy.stats import ttest_1samp\n",
+    "poke_differences= pokemon['Defense'] - pokemon['Attack']\n",
+    "\n",
+    "t_stat, p_value = ttest_1samp(poke_differences, 0)\n",
+    "\n",
+    "print(f\"Tstatistics: {t_stat:.5f}\")\n",
+    "print(f\"P-value: {p_value:.5f}\")\n",
+    "\n",
+    "\n",
+    "if p_value < 0.05:\n",
+    "    print(\"Reject the Null Hypoteses: The mean difference is sgnificantly different from 0.\")\n",
+    "else:\n",
+    "    print(\"Fail to Reject null Hypotheses: The mean difference is not sgnificantly different from 0..\")\n"
    ]
   },
   {
@@ -302,12 +845,94 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 36,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['Grass', 'Fire', 'Water', 'Bug', 'Normal', 'Poison', 'Electric',\n",
+       "       'Ground', 'Fairy', 'Fighting', 'Psychic', 'Rock', 'Ghost', 'Ice',\n",
+       "       'Dragon', 'Dark', 'Steel', 'Flying'], dtype=object)"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pokemon['Type 1'].unique()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "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>is_water</th>\n",
+       "      <th>False</th>\n",
+       "      <th>True</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>Legendary</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>False</th>\n",
+       "      <td>627</td>\n",
+       "      <td>108</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>True</th>\n",
+       "      <td>61</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "is_water   False  True \n",
+       "Legendary              \n",
+       "False        627    108\n",
+       "True          61      4"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "pokemon['is_water'] = pokemon['Type 1'] == \"Water\"\n",
+    "\n",
+    "contigency_table = pd.crosstab(pokemon['Legendary'], pokemon['is_water'])\n",
+    "contigency_table"
    ]
   },
   {
@@ -319,12 +944,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 42,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Chi-Squared Statistic: 2.9429200762850503\n",
+      "P-value: 0.08625467249550949\n"
+     ]
+    }
+   ],
    "source": [
     "# Your code here:\n",
-    "\n"
+    "from scipy.stats import chi2_contingency\n",
+    "\n",
+    "chi2, chi_p, __, __  = chi2_contingency(contigency_table)\n",
+    "\n",
+    "print(\"Chi-Squared Statistic:\", chi2)\n",
+    "print(\"P-value:\", chi_p)\n"
    ]
   },
   {
@@ -336,12 +975,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 44,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fail to reject the null hypothesis: There is no significant association between being legendary and being a Water type.\n"
+     ]
+    }
+   ],
    "source": [
     "# Your answer here:\n",
-    "\n"
+    "if chi_p < 0.05:\n",
+    "    print(\"Reject the null hypothesis: There is a significant association between being legendary and being a Water type.\")\n",
+    "else:\n",
+    "    print(\"Fail to reject the null hypothesis: There is no significant association between being legendary and being a Water type.\")\n"
    ]
   },
   {
@@ -354,7 +1004,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -368,9 +1018,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.12.4"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }