From 89ce77d7dbb8082f5b0cebcb29dccdf62eb185ae Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Fran=C3=A7ois=20Laurent?= <francois.laurent@posteo.net>
Date: Sun, 18 Sep 2022 21:07:37 +0200
Subject: [PATCH] lighter

---
 notebooks/scipy_TP_solutions.ipynb | 1531 ++++++++++------------------
 notebooks/statsmodels_cours.ipynb  |    2 +-
 2 files changed, 526 insertions(+), 1007 deletions(-)

diff --git a/notebooks/scipy_TP_solutions.ipynb b/notebooks/scipy_TP_solutions.ipynb
index f1cd821..3ec431b 100644
--- a/notebooks/scipy_TP_solutions.ipynb
+++ b/notebooks/scipy_TP_solutions.ipynb
@@ -55,7 +55,7 @@
    "source": [
     "## Q\n",
     "\n",
-    "Load the `mi.csv` data file located in the `data` directory of the course repository."
+    "Load the `mi.csv` data file, located in the `data` directory of the course repository, into a DataFrame, and show the column names and 5 first rows."
    ]
   },
   {
@@ -70,273 +70,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "00130518",
+   "execution_count": 14,
+   "id": "eefc126c",
    "metadata": {
     "hidden": true
    },
-   "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>Age</th>\n",
-       "      <th>OwnsHouse</th>\n",
-       "      <th>PhysicalActivity</th>\n",
-       "      <th>Sex</th>\n",
-       "      <th>LivesWithPartner</th>\n",
-       "      <th>LivesWithKids</th>\n",
-       "      <th>BornInCity</th>\n",
-       "      <th>Inbreeding</th>\n",
-       "      <th>BMI</th>\n",
-       "      <th>CMVPositiveSerology</th>\n",
-       "      <th>...</th>\n",
-       "      <th>VaccineWhoopingCough</th>\n",
-       "      <th>VaccineYellowFever</th>\n",
-       "      <th>VaccineHepB</th>\n",
-       "      <th>VaccineFlu</th>\n",
-       "      <th>SUBJID</th>\n",
-       "      <th>DepressionScore</th>\n",
-       "      <th>HeartRate</th>\n",
-       "      <th>Temperature</th>\n",
-       "      <th>HourOfSampling</th>\n",
-       "      <th>DayOfSampling</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>22.33</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>94.9627</td>\n",
-       "      <td>20.13</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>2</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>66</td>\n",
-       "      <td>36.8</td>\n",
-       "      <td>8.883</td>\n",
-       "      <td>40</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>28.83</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>79.1024</td>\n",
-       "      <td>21.33</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>3</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>66</td>\n",
-       "      <td>37.4</td>\n",
-       "      <td>9.350</td>\n",
-       "      <td>40</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>23.67</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>117.2540</td>\n",
-       "      <td>22.18</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>4</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>62</td>\n",
-       "      <td>36.9</td>\n",
-       "      <td>8.667</td>\n",
-       "      <td>40</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>21.17</td>\n",
-       "      <td>No</td>\n",
-       "      <td>0.5</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>94.1796</td>\n",
-       "      <td>18.68</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>5</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>64</td>\n",
-       "      <td>36.0</td>\n",
-       "      <td>9.883</td>\n",
-       "      <td>40</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>26.17</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>1.5</td>\n",
-       "      <td>Female</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>105.1250</td>\n",
-       "      <td>29.01</td>\n",
-       "      <td>No</td>\n",
-       "      <td>...</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
-       "      <td>8</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>67</td>\n",
-       "      <td>36.7</td>\n",
-       "      <td>8.550</td>\n",
-       "      <td>81</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5 rows × 43 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     Age OwnsHouse  PhysicalActivity     Sex LivesWithPartner LivesWithKids  \\\n",
-       "1  22.33       Yes               3.0  Female               No            No   \n",
-       "2  28.83       Yes               0.0  Female              Yes            No   \n",
-       "3  23.67       Yes               0.0  Female              Yes            No   \n",
-       "4  21.17        No               0.5  Female               No            No   \n",
-       "5  26.17       Yes               1.5  Female               No            No   \n",
-       "\n",
-       "  BornInCity  Inbreeding    BMI CMVPositiveSerology  ...  \\\n",
-       "1        Yes     94.9627  20.13                  No  ...   \n",
-       "2        Yes     79.1024  21.33                 Yes  ...   \n",
-       "3        Yes    117.2540  22.18                  No  ...   \n",
-       "4         No     94.1796  18.68                  No  ...   \n",
-       "5        Yes    105.1250  29.01                  No  ...   \n",
-       "\n",
-       "   VaccineWhoopingCough  VaccineYellowFever  VaccineHepB  VaccineFlu  SUBJID  \\\n",
-       "1                   Yes                  No          Yes          No       2   \n",
-       "2                   Yes                  No          Yes          No       3   \n",
-       "3                    No                  No          Yes          No       4   \n",
-       "4                    No                  No          Yes          No       5   \n",
-       "5                   Yes                  No          Yes          No       8   \n",
-       "\n",
-       "   DepressionScore  HeartRate Temperature HourOfSampling DayOfSampling  \n",
-       "1              0.0         66        36.8          8.883            40  \n",
-       "2              0.0         66        37.4          9.350            40  \n",
-       "3              0.0         62        36.9          8.667            40  \n",
-       "4              1.0         64        36.0          9.883            40  \n",
-       "5              0.0         67        36.7          8.550            81  \n",
-       "\n",
-       "[5 rows x 43 columns]"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = pd.read_csv('../data/mi.csv', index_col=0)\n",
-    "df.head()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "9cc036b2",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "## Q\n",
-    "\n",
-    "Anything missing?"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "99d5dc74",
-   "metadata": {
-    "heading_collapsed": true
-   },
+   "outputs": [],
    "source": [
-    "## A"
+    "df = pd.read_csv('../data/mi.csv', index_col=0)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "8a648a9b",
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(816, 43)"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df.shape"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "2f0a8116",
+   "id": "00130518",
    "metadata": {
     "hidden": true
    },
@@ -547,78 +294,31 @@
        "      <td>40</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",
-       "      <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",
-       "      <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",
-       "      <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>814</th>\n",
-       "      <td>32.75</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>2.5</td>\n",
+       "      <th>4</th>\n",
+       "      <td>21.17</td>\n",
+       "      <td>No</td>\n",
+       "      <td>0.5</td>\n",
        "      <td>Female</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
-       "      <td>86.6744</td>\n",
-       "      <td>20.07</td>\n",
+       "      <td>94.1796</td>\n",
+       "      <td>18.68</td>\n",
        "      <td>No</td>\n",
-       "      <td>0.252037</td>\n",
+       "      <td>0.404886</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>1.0</td>\n",
-       "      <td>8.00</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>10.00</td>\n",
        "      <td>3</td>\n",
        "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Never</td>\n",
        "      <td>No</td>\n",
-       "      <td>Baccalaureat</td>\n",
+       "      <td>Never</td>\n",
        "      <td>No</td>\n",
-       "      <td>(1000-2000]</td>\n",
+       "      <td>PhD</td>\n",
        "      <td>No</td>\n",
+       "      <td>(3000-inf]</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>Yes</td>\n",
@@ -629,198 +329,125 @@
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
+       "      <td>No</td>\n",
        "      <td>Yes</td>\n",
        "      <td>No</td>\n",
-       "      <td>5279</td>\n",
-       "      <td>3.0</td>\n",
-       "      <td>62</td>\n",
-       "      <td>36.3</td>\n",
-       "      <td>9.800</td>\n",
-       "      <td>278</td>\n",
+       "      <td>5</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>64</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>9.883</td>\n",
+       "      <td>40</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>815</th>\n",
-       "      <td>39.17</td>\n",
-       "      <td>No</td>\n",
-       "      <td>4.0</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>98.9744</td>\n",
-       "      <td>22.77</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>0.264940</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>2.0</td>\n",
-       "      <td>7.50</td>\n",
-       "      <td>0</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>Never</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>PhD</td>\n",
-       "      <td>No</td>\n",
-       "      <td>(2000-3000]</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
+       "      <th>5</th>\n",
+       "      <td>26.17</td>\n",
        "      <td>Yes</td>\n",
-       "      <td>No</td>\n",
+       "      <td>1.5</td>\n",
+       "      <td>Female</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>Yes</td>\n",
+       "      <td>105.1250</td>\n",
+       "      <td>29.01</td>\n",
        "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>No</td>\n",
-       "      <td>5303</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>39</td>\n",
-       "      <td>36.3</td>\n",
-       "      <td>9.583</td>\n",
-       "      <td>277</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>816</th>\n",
-       "      <td>59.00</td>\n",
-       "      <td>No</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>Male</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>84.6433</td>\n",
-       "      <td>27.39</td>\n",
-       "      <td>Yes</td>\n",
-       "      <td>0.281522</td>\n",
+       "      <td>-0.303782</td>\n",
        "      <td>1</td>\n",
        "      <td>0</td>\n",
        "      <td>0</td>\n",
-       "      <td>0.0</td>\n",
-       "      <td>8.00</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>9.00</td>\n",
        "      <td>0</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>Never</td>\n",
-       "      <td>No</td>\n",
+       "      <td>Yes</td>\n",
        "      <td>Baccalaureat</td>\n",
        "      <td>No</td>\n",
-       "      <td>(2000-3000]</td>\n",
-       "      <td>No</td>\n",
+       "      <td>[0-1000]</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
-       "      <td>Yes</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
        "      <td>No</td>\n",
+       "      <td>Yes</td>\n",
        "      <td>No</td>\n",
+       "      <td>Yes</td>\n",
        "      <td>No</td>\n",
-       "      <td>5701</td>\n",
+       "      <td>8</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>61</td>\n",
-       "      <td>36.1</td>\n",
-       "      <td>9.317</td>\n",
-       "      <td>241</td>\n",
+       "      <td>67</td>\n",
+       "      <td>36.7</td>\n",
+       "      <td>8.550</td>\n",
+       "      <td>81</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>816 rows × 43 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "       Age OwnsHouse  PhysicalActivity     Sex LivesWithPartner LivesWithKids  \\\n",
-       "1    22.33       Yes               3.0  Female               No            No   \n",
-       "2    28.83       Yes               0.0  Female              Yes            No   \n",
-       "3    23.67       Yes               0.0  Female              Yes            No   \n",
-       "..     ...       ...               ...     ...              ...           ...   \n",
-       "814  32.75       Yes               2.5  Female               No            No   \n",
-       "815  39.17        No               4.0    Male               No           Yes   \n",
-       "816  59.00        No               0.0    Male              Yes           Yes   \n",
-       "\n",
-       "    BornInCity  Inbreeding    BMI CMVPositiveSerology    FluIgG  \\\n",
-       "1          Yes     94.9627  20.13                  No  0.464319   \n",
-       "2          Yes     79.1024  21.33                 Yes -0.049817   \n",
-       "3          Yes    117.2540  22.18                  No  0.332944   \n",
-       "..         ...         ...    ...                 ...       ...   \n",
-       "814         No     86.6744  20.07                  No  0.252037   \n",
-       "815        Yes     98.9744  22.77                 Yes  0.264940   \n",
-       "816        Yes     84.6433  27.39                 Yes  0.281522   \n",
-       "\n",
-       "     MetabolicScore  LowAppetite  TroubleConcentrating  TroubleSleeping  \\\n",
-       "1                 0            0                     0              1.0   \n",
-       "2                 1            0                     0              1.0   \n",
-       "3                 2            0                     0              1.0   \n",
-       "..              ...          ...                   ...              ...   \n",
-       "814               0            0                     0              1.0   \n",
-       "815               0            0                     0              2.0   \n",
-       "816               1            0                     0              0.0   \n",
+       "     Age OwnsHouse  PhysicalActivity     Sex LivesWithPartner LivesWithKids  \\\n",
+       "1  22.33       Yes               3.0  Female               No            No   \n",
+       "2  28.83       Yes               0.0  Female              Yes            No   \n",
+       "3  23.67       Yes               0.0  Female              Yes            No   \n",
+       "4  21.17        No               0.5  Female               No            No   \n",
+       "5  26.17       Yes               1.5  Female               No            No   \n",
        "\n",
-       "     HoursOfSleep  Listless UsesCannabis RecentPersonalCrisis Smoking  \\\n",
-       "1            9.00         3           No                   No   Never   \n",
-       "2            7.05         3           No                   No  Active   \n",
-       "3            6.50         3          Yes                   No  Active   \n",
-       "..            ...       ...          ...                  ...     ...   \n",
-       "814          8.00         3           No                  Yes   Never   \n",
-       "815          7.50         0           No                   No   Never   \n",
-       "816          8.00         0           No                   No   Never   \n",
+       "  BornInCity  Inbreeding    BMI CMVPositiveSerology    FluIgG  MetabolicScore  \\\n",
+       "1        Yes     94.9627  20.13                  No  0.464319               0   \n",
+       "2        Yes     79.1024  21.33                 Yes -0.049817               1   \n",
+       "3        Yes    117.2540  22.18                  No  0.332944               2   \n",
+       "4         No     94.1796  18.68                  No  0.404886               0   \n",
+       "5        Yes    105.1250  29.01                  No -0.303782               1   \n",
        "\n",
-       "    Employed     Education DustExposure       Income HadMeasles HadRubella  \\\n",
-       "1         No           PhD           No  (1000-2000]         No         No   \n",
-       "2        Yes  Baccalaureat           No  (2000-3000]         No         No   \n",
-       "3        Yes  Baccalaureat      Current  (2000-3000]         No         No   \n",
-       "..       ...           ...          ...          ...        ...        ...   \n",
-       "814       No  Baccalaureat           No  (1000-2000]         No         No   \n",
-       "815      Yes           PhD           No  (2000-3000]         No         No   \n",
-       "816       No  Baccalaureat           No  (2000-3000]         No         No   \n",
+       "   LowAppetite  TroubleConcentrating  TroubleSleeping  HoursOfSleep  Listless  \\\n",
+       "1            0                     0              1.0          9.00         3   \n",
+       "2            0                     0              1.0          7.05         3   \n",
+       "3            0                     0              1.0          6.50         3   \n",
+       "4            0                     0              2.0         10.00         3   \n",
+       "5            0                     0              1.0          9.00         0   \n",
        "\n",
-       "    HadChickenPox HadMumps HadTonsillectomy HadAppendicectomy VaccineHepA  \\\n",
-       "1             Yes       No               No                No          No   \n",
-       "2             Yes       No               No                No          No   \n",
-       "3             Yes       No               No                No          No   \n",
-       "..            ...      ...              ...               ...         ...   \n",
-       "814            No      Yes               No                No          No   \n",
-       "815            No      Yes               No                No          No   \n",
-       "816            No       No              Yes                No          No   \n",
+       "  UsesCannabis RecentPersonalCrisis Smoking Employed     Education  \\\n",
+       "1           No                   No   Never       No           PhD   \n",
+       "2           No                   No  Active      Yes  Baccalaureat   \n",
+       "3          Yes                   No  Active      Yes  Baccalaureat   \n",
+       "4           No                   No   Never       No           PhD   \n",
+       "5           No                   No   Never      Yes  Baccalaureat   \n",
        "\n",
-       "    VaccineMMR VaccineTyphoid VaccineWhoopingCough VaccineYellowFever  \\\n",
-       "1           No             No                  Yes                 No   \n",
-       "2           No             No                  Yes                 No   \n",
-       "3           No             No                   No                 No   \n",
-       "..         ...            ...                  ...                ...   \n",
-       "814         No             No                   No                 No   \n",
-       "815        Yes             No                   No                 No   \n",
-       "816         No             No                   No                 No   \n",
+       "  DustExposure       Income HadMeasles HadRubella HadChickenPox HadMumps  \\\n",
+       "1           No  (1000-2000]         No         No           Yes       No   \n",
+       "2           No  (2000-3000]         No         No           Yes       No   \n",
+       "3      Current  (2000-3000]         No         No           Yes       No   \n",
+       "4           No   (3000-inf]         No         No           Yes       No   \n",
+       "5           No     [0-1000]         No         No            No       No   \n",
        "\n",
-       "    VaccineHepB VaccineFlu  SUBJID  DepressionScore  HeartRate  Temperature  \\\n",
-       "1           Yes         No       2              0.0         66         36.8   \n",
-       "2           Yes         No       3              0.0         66         37.4   \n",
-       "3           Yes         No       4              0.0         62         36.9   \n",
-       "..          ...        ...     ...              ...        ...          ...   \n",
-       "814         Yes         No    5279              3.0         62         36.3   \n",
-       "815          No         No    5303              0.0         39         36.3   \n",
-       "816          No         No    5701              0.0         61         36.1   \n",
+       "  HadTonsillectomy HadAppendicectomy VaccineHepA VaccineMMR VaccineTyphoid  \\\n",
+       "1               No                No          No         No             No   \n",
+       "2               No                No          No         No             No   \n",
+       "3               No                No          No         No             No   \n",
+       "4               No                No          No         No             No   \n",
+       "5               No                No          No         No             No   \n",
        "\n",
-       "     HourOfSampling  DayOfSampling  \n",
-       "1             8.883             40  \n",
-       "2             9.350             40  \n",
-       "3             8.667             40  \n",
-       "..              ...            ...  \n",
-       "814           9.800            278  \n",
-       "815           9.583            277  \n",
-       "816           9.317            241  \n",
+       "  VaccineWhoopingCough VaccineYellowFever VaccineHepB VaccineFlu  SUBJID  \\\n",
+       "1                  Yes                 No         Yes         No       2   \n",
+       "2                  Yes                 No         Yes         No       3   \n",
+       "3                   No                 No         Yes         No       4   \n",
+       "4                   No                 No         Yes         No       5   \n",
+       "5                  Yes                 No         Yes         No       8   \n",
        "\n",
-       "[816 rows x 43 columns]"
+       "   DepressionScore  HeartRate  Temperature  HourOfSampling  DayOfSampling  \n",
+       "1              0.0         66         36.8           8.883             40  \n",
+       "2              0.0         66         37.4           9.350             40  \n",
+       "3              0.0         62         36.9           8.667             40  \n",
+       "4              1.0         64         36.0           9.883             40  \n",
+       "5              0.0         67         36.7           8.550             81  "
       ]
      },
-     "execution_count": 5,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -829,7 +456,8 @@
     "# in Jupyter-lab, pandas is set to display dataframes with a limited number of columns\n",
     "pd.options.display.max_columns = None\n",
     "pd.options.display.max_rows = 6\n",
-    "df"
+    "\n",
+    "df.head()"
    ]
   },
   {
@@ -1127,7 +755,7 @@
    "source": [
     "## Q\n",
     "\n",
-    "Inspect the distribution of variables `Age` and `OwnsHouse`."
+    "Inspect the relationship between variables `Age` and `OwnsHouse`. What type of plots is most suitable?"
    ]
   },
   {
@@ -1142,7 +770,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 15,
    "id": "5de6412d",
    "metadata": {
     "hidden": true
@@ -1150,27 +778,47 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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GDRp0yfZBgwapqKhI0vlXNl34DCYAAID20uqQiY6OVlZW1iXbs7KyFB0dLUn68ssvddNNN137dAAAAFfQ6lNLv/rVrzRu3Djl5eVp6NChkqT9+/fr8OHD2rhxoyRp3759evLJJ9t2UgAAgIu0OmS+//3vq6SkRG+//bY+++wzSVJKSopyc3N1+vRpSdKzzz7btlMCAABcxnd6Q7xevXpp4cKFks6/r8y6dev05JNPav/+/WpsbGzTAQEAAJrznd/oZceOHZo0aZKioqK0aNEiPfjgg9q9e3dbzgYAAHBFrVqRqays1OrVq5WVlaXa2lqNHz9eLpdLubm56t+/f3vNCAAAcFktXpEZNWqU+vXrpz/96U964403VFFRoSVLlrTnbAAAAFfU4hWZvLw8Pf/883r22Wd1++23t+dMAAAALdLiFZmdO3eqrq5OgwcP1rBhw7R06VL97W9/a8/ZAAAArqjFITN8+HCtWrVKJ06c0E9+8hOtX79eUVFRampq0rZt21RXV9eecwIAAFyi1a9a6tKli6ZMmaKdO3fq4MGDmjVrlhYuXKju3bvr+9//fnvMCAAAcFnf+eXXktSvXz/98pe/1PHjx7Vu3bq2mgkAAKBFrilkLvD399fo0aP1hz/8oS0OBwAA0CJtEjIAAABWIGQAAICxCBkAAGAsQgYAABiLkAEAAMYiZAAAgLEIGQAAYCxCBgAAGIuQAQAAxiJkAACAsQgZAABgLEIGAAAYK8DqAQDABK5GmyS31WPcsNxu6WzT+a8D/SSbzdp5bmTnHwu+g5ABgBaYtjPM6hEAXIbPnFpauHChbDabZsyY4dlWX1+vtLQ0hYeHKzg4WKmpqaqqqrJuSAAA4FN8YkVm3759WrlypQYOHOi1febMmdq8ebM2bNigkJAQTZs2TWPHjtWuXbssmhTAjcThcCgvL8/qMaDz/2M7ZswYSVJOTo4cDofFE0GST/wcLA+Z06dPa+LEiVq1apVeffVVz/aamhplZWVp7dq1GjlypCQpOztbcXFx2r17t4YPH27VyABuEDabTUFBQVaPgYs4HA5+LvCw/NRSWlqaHnvsMSUlJXltLy4uVkNDg9f22NhYxcTEqKioqNnjuVwu1dbWel0AAEDHZOmKzPr16/Xf//3f2rdv3yX7KisrFRgYqNDQUK/tERERqqysbPaYmZmZeuWVV9p6VAAA4IMsW5EpLy/Xz372M/32t79t03NsGRkZqqmp8VzKy8vb7NgAAMC3WBYyxcXFOnnypO6++24FBAQoICBAhYWFeuuttxQQEKCIiAidPXtW1dXVXt9XVVWlyMjIZo9rt9vldDq9LgAAoGOy7NTSQw89pIMHD3pt+9GPfqTY2Fi9+OKLio6OVqdOnZSfn6/U1FRJUklJicrKypSQkGDFyAAAwMdYFjJdu3bVHXfc4bWtS5cuCg8P92yfOnWq0tPTFRYWJqfTqenTpyshIYFXLAEAAEk+8PLrK1m8eLH8/PyUmpoql8ul5ORkLV++3OqxAACAj/CpkCkoKPC67nA4tGzZMi1btsyagQAAgE+z/H1kAAAAvitCBgAAGIuQAQAAxiJkAACAsQgZAABgLEIGAAAYy6defm0it9v9jyuNDdYNAviSbz0WvB4jANDGCJlr5HK5PF93/WS9hZMAvsnlcqlz585WjwGgg+LUEgAAMBYrMtfIbrd7vq678ynJv5OF0wA+orHBs0L57ccIALQ1QuYa2Wy2f1zx70TIABfxeowAQBvj1BIAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhAwAAjEXIAAAAYxEyAADAWIQMAAAwFiEDAACMRcgAAABjETIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhAwAAjEXIAAAAYxEyAADAWIQMAAAwFiEDAACMRcgAAABjETIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhAwAAjEXIAAAAYxEyAADAWIQMAAAwFiEDAACMRcgAAABjETIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhAwAAjEXIAAAAYxEyAADAWIQMAAAwFiEDAACMZWnIrFixQgMHDpTT6ZTT6VRCQoLy8vI8++vr65WWlqbw8HAFBwcrNTVVVVVVFk4MAAB8iaUh06NHDy1cuFDFxcXav3+/Ro4cqR/84Af685//LEmaOXOm3n//fW3YsEGFhYWqqKjQ2LFjrRwZAAD4kAAr//FRo0Z5XX/ttde0YsUK7d69Wz169FBWVpbWrl2rkSNHSpKys7MVFxen3bt3a/jw4Zc9psvlksvl8lyvra1tvzsAAAAs5TPPkWlsbNT69et15swZJSQkqLi4WA0NDUpKSvLcJjY2VjExMSoqKmr2OJmZmQoJCfFcoqOjr8f4AADAApaHzMGDBxUcHCy73a6f/vSnysnJUf/+/VVZWanAwECFhoZ63T4iIkKVlZXNHi8jI0M1NTWeS3l5eTvfAwAAYBVLTy1JUr9+/XTgwAHV1NTovffe06RJk1RYWPidj2e322W329twQgAA4KssD5nAwED16dNHkjR48GDt27dPb775pp588kmdPXtW1dXVXqsyVVVVioyMtGhaAADgSyw/tXSxpqYmuVwuDR48WJ06dVJ+fr5nX0lJicrKypSQkGDhhAAAwFdYuiKTkZGhlJQUxcTEqK6uTmvXrlVBQYG2bt2qkJAQTZ06Venp6QoLC5PT6dT06dOVkJDQ7CuWAADAjcXSkDl58qSefvppnThxQiEhIRo4cKC2bt2qhx9+WJK0ePFi+fn5KTU1VS6XS8nJyVq+fLmVIwMAAB9iachkZWVdcb/D4dCyZcu0bNmy6zQRAAAwic89RwYAAKClCBkAAGAsQgYAABiLkAEAAMYiZAAAgLEIGQAAYCxCBgAAGIuQAQAAxiJkAACAsQgZAABgLEIGAAAYi5ABAADGImQAAICxCBkAAGAsQgYAABiLkAEAAMYiZAAAgLEIGQAAYCxCBgAAGIuQAQAAxiJkAACAsQgZAABgrACrB+hIbE3n5LZ6iBuZ2y01nTv/tV+AZLNZO88NzHbh5wAA7YyQaUPBB9ZZPQIAADcUTi0BAABjsSJzjRwOh/Ly8qweA5Lq6+s1ZswYSVJOTo4cDofFE0ESPwcA7YqQuUY2m01BQUFWj4GLOBwOfi4AcAPg1BIAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhAwAAjEXIAAAAYxEyAADAWIQMAAAwFiEDAACMRcgAAABjETIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhAwAAjEXIAAAAYxEyAADAWIQMAAAwFiEDAACMRcgAAABjETIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMFaAlf94ZmamNm3apCNHjigoKEj33nuvXn/9dfXr189zm/r6es2aNUvr16+Xy+VScnKyli9froiICAsnBwAzuN1u1dfXWz3GNfv2fegI90eSHA6HbDab1WMYz9KQKSwsVFpamoYOHapz587p5z//uR555BEdOnRIXbp0kSTNnDlTmzdv1oYNGxQSEqJp06Zp7Nix2rVrl5Wjdyj8ovNd/KLDtaqvr1dKSorVY7SpMWPGWD1Cm8jLy1NQUJDVYxjP5na73VYPccGpU6fUvXt3FRYW6r777lNNTY26deumtWvX6oknnpAkHTlyRHFxcSoqKtLw4cOvesza2lqFhISopqZGTqezve+Ckb755psO94uuo+AXHa4Vj2/fxeP7ylr699vSFZmL1dTUSJLCwsIkScXFxWpoaFBSUpLnNrGxsYqJiWk2ZFwul1wul+d6bW1tO08NAL7L4XAoLy/P6jGumdvt9vxut9vtHWKl0uFwWD1Ch+AzIdPU1KQZM2YoMTFRd9xxhySpsrJSgYGBCg0N9bptRESEKisrL3uczMxMvfLKK+09bofCLzrfxS86XCubzdZh/q+/c+fOVo8AH+QzIZOWlqZPP/1UO3fuvKbjZGRkKD093XO9trZW0dHR1zpeh8YvOgCAqXwiZKZNm6YPPvhAO3bsUI8ePTzbIyMjdfbsWVVXV3utylRVVSkyMvKyx7Lb7bLb7e09MgAA8AGWvo+M2+3WtGnTlJOTo//8z/9U7969vfYPHjxYnTp1Un5+vmdbSUmJysrKlJCQcL3HBQAAPsbSFZm0tDStXbtWv//979W1a1fP815CQkIUFBSkkJAQTZ06Venp6QoLC5PT6dT06dOVkJDQolcsAQCAjs3Sl18392TM7OxsTZ48WdI/3hBv3bp1Xm+I19yppYvx8msAAMzT0r/fPvU+Mu2BkAEAwDwt/fvNZy0BAABjETIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhAwAAjOUTHxrZni68319tba3FkwAAgJa68Hf7au/b2+FDpq6uTpIUHR1t8SQAAKC16urqFBIS0uz+Dv8RBU1NTaqoqFDXrl2b/WwndBy1tbWKjo5WeXk5H0kBdDA8vm8sbrdbdXV1ioqKkp9f88+E6fArMn5+furRo4fVY+A6czqd/KIDOige3zeOK63EXMCTfQEAgLEIGQAAYCxCBh2K3W7X3LlzZbfbrR4FQBvj8Y3L6fBP9gUAAB0XKzIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMjCC2+1WUlKSkpOTL9m3fPlyhYaG6vjx4xZMBqAtTZ48WTabTQsXLvTanpuby7uz47IIGRjBZrMpOztbe/bs0cqVKz3bjx07phdeeEFLlizhHZyBDsLhcOj111/X119/bfUoMAAhA2NER0frzTff1OzZs3Xs2DG53W5NnTpVjzzyiAYNGqSUlBQFBwcrIiJCP/zhD/W3v/3N873vvfee4uPjFRQUpPDwcCUlJenMmTMW3hsAzUlKSlJkZKQyMzObvc3GjRs1YMAA2e129erVS4sWLbqOE8KXEDIwyqRJk/TQQw9pypQpWrp0qT799FOtXLlSI0eO1KBBg7R//35t2bJFVVVVGj9+vCTpxIkTmjBhgqZMmaLDhw+roKBAY8eOvepHwwOwhr+/vxYsWKAlS5Zc9pRxcXGxxo8fr6eeekoHDx7UvHnz9Itf/EKrV6++/sPCcrwhHoxz8uRJDRgwQF999ZU2btyoTz/9VB999JG2bt3quc3x48cVHR2tkpISnT59WoMHD9Zf//pX9ezZ08LJAVzN5MmTVV1drdzcXCUkJKh///7KyspSbm6uxowZI7fbrYkTJ+rUqVP68MMPPd/3wgsvaPPmzfrzn/9s4fSwAisyME737t31k5/8RHFxcRo9erQ++eQT/dd//ZeCg4M9l9jYWEnS0aNHdeedd+qhhx5SfHy8xo0bp1WrVnHuHTDA66+/rjVr1ujw4cNe2w8fPqzExESvbYmJiSotLVVjY+P1HBE+gJCBkQICAhQQECBJOn36tEaNGqUDBw54XUpLS3XffffJ399f27ZtU15envr3768lS5aoX79+OnbsmMX3AsCV3HfffUpOTlZGRobVo8CHBVg9AHCt7r77bm3cuFG9evXyxM3FbDabEhMTlZiYqJdfflk9e/ZUTk6O0tPTr/O0AFpj4cKFuuuuu9SvXz/Ptri4OO3atcvrdrt27VLfvn3l7+9/vUeExViRgfHS0tL01VdfacKECdq3b5+OHj2qrVu36kc/+pEaGxu1Z88eLViwQPv371dZWZk2bdqkU6dOKS4uzurRAVxFfHy8Jk6cqLfeesuzbdasWcrPz9e//uu/6rPPPtOaNWu0dOlSzZ4928JJYRVCBsaLiorSrl271NjYqEceeUTx8fGaMWOGQkND5efnJ6fTqR07dujRRx9V3759NWfOHC1atEgpKSlWjw6gBebPn6+mpibP9bvvvlu/+93vtH79et1xxx16+eWXNX/+fE2ePNm6IWEZXrUEAACMxYoMAAAwFiEDAACMRcgAAABjETIAAMBYhAwAADAWIQMAAIxFyAAAAGMRMgAAwFiEDAAAMBYhA6BFysvLNWXKFEVFRSkwMFA9e/bUz372M3355ZeWzDNv3jzdddddl2z/61//KpvNpgMHDlz3mQBcf4QMgKv6/PPPNWTIEJWWlmrdunX6y1/+orffflv5+flKSEjQV199ZfWIAG5QhAyAq0pLS1NgYKA+/PBD3X///YqJiVFKSoq2b9+uL774Qi+99JKWLl2qO+64w/M9ubm5stlsevvttz3bkpKSNGfOHEn/WFH59a9/rV69eikkJERPPfWU6urqPLd/7733FB8fr6CgIIWHhyspKUlnzpxp9fyFhYW65557ZLfbdfPNN+tf/uVfdO7cOc/+Xr166Y033vD6nrvuukvz5s2TJLndbs2bN08xMTGy2+2KiorS888/77mty+XS7Nmzdcstt6hLly4aNmyYCgoKWj0ngNYjZABc0VdffaWtW7fqueeeU1BQkNe+yMhITZw4Ue+++67uv/9+HTp0SKdOnZJ0Ph7+6Z/+yfMHvaGhQUVFRXrggQc833/06FHl5ubqgw8+0AcffKDCwkItXLhQknTixAlNmDBBU6ZM0eHDh1VQUKCxY8eqtZ9z+8UXX+jRRx/V0KFD9cknn2jFihXKysrSq6++2uJjbNy4UYsXL9bKlStVWlqq3NxcxcfHe/ZPmzZNRUVFWr9+vf70pz9p3Lhx+ud//meVlpa2alYArRdg9QAAfFtpaancbrfi4uIuuz8uLk5ff/21unfvrrCwMBUWFuqJJ55QQUGBZs2apTfffFOStHfvXjU0NOjee+/1fG9TU5NWr16trl27SpJ++MMfKj8/X6+99ppOnDihc+fOaezYserZs6ckecWDJB08eFDBwcFe2y4OneXLlys6OlpLly6VzWZTbGysKioq9OKLL+rll1+Wn9/V/3+urKxMkZGRSkpKUqdOnRQTE6N77rnHsy87O1tlZWWKioqSJM2ePVtbtmxRdna2FixYcNXjA/juWJEB0CJXWwmx2Wy67777VFBQoOrqah06dEjPPfecXC6Xjhw5osLCQg0dOlSdO3f2fE+vXr08ESNJN998s06ePClJuvPOO/XQQw8pPj5e48aN06pVq/T11197/Zv9+vXTgQMHvC5//OMfvW5z+PBhJSQkyGazebYlJibq9OnTOn78eIvu+7hx4/TNN9/o1ltv1Y9//GPl5OR4Tk0dPHhQjY2N6tu3r4KDgz2XwsJCHT16tEXHB/DdsSID4Ir69Okjm82mw4cPa8yYMZfsP3z4sG666SZ169ZNDzzwgN555x199NFHGjRokJxOpyduCgsLdf/993t9b6dOnbyu22w2NTU1SZL8/f21bds2ffzxx/rwww+1ZMkSvfTSS9qzZ4969+4tSQoMDFSfPn28jhEQ0Ppfa35+fpeEWkNDg+fr6OholZSUaPv27dq2bZuee+45/du//ZsKCwt1+vRp+fv7q7i4WP7+/l7HuHi1CEDbY0UGwBWFh4fr4Ycf1vLly/XNN9947ausrNRvf/tbPfnkk7LZbJ7nyWzYsMHzXJgHHnhA27dv165du7yeH9MSNptNiYmJeuWVV/Q///M/CgwMVE5OTquOERcXp6KiIq9Q2bVrl7p27aoePXpIkrp166YTJ0549tfW1urYsWNexwkKCtKoUaP01ltvqaCgQEVFRTp48KAGDRqkxsZGnTx5Un369PG6REZGtmpWAK1HyAC4qqVLl8rlcik5OVk7duxQeXm5tmzZoocffli33HKLXnvtNUnSwIEDddNNN2nt2rVeIZObmyuXy6XExMQW/5t79uzRggULtH//fpWVlWnTpk06depUs8/Vac5zzz2n8vJyTZ8+XUeOHNHvf/97zZ07V+np6Z7nx4wcOVK//vWv9dFHH+ngwYOaNGmS1+rK6tWrlZWVpU8//VSff/65fvOb3ygoKEg9e/ZU3759NXHiRD399NPatGmTjh07pr179yozM1ObN29u1awAWo+QAXBVt99+u/bv369bb71V48eP12233aZnnnlGDz74oIqKihQWFibp/ArK9773PdlsNo0YMULS+bhxOp0aMmSIunTp0uJ/0+l0aseOHXr00UfVt29fzZkzR4sWLVJKSkqrZr/lllv0xz/+UXv37tWdd96pn/70p5o6darnZeCSlJGRofvvv1+PP/64HnvsMY0ePVq33XabZ39oaKhWrVqlxMREDRw4UNu3b9f777+v8PBwSVJ2draefvppzZo1S/369dPo0aO1b98+xcTEtGpWAK1nc7f2tYwAAAA+ghUZAABgLEIGAAAYi5ABAADGImQAAICxCBkAAGAsQgYAABiLkAEAAMYiZAAAgLEIGQAAYCxCBgAAGIuQAQAAxvo/3nhej2ufkLAAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "# categorical vs continuous => boxplot, violinplot\n",
+    "sns.boxplot(x='OwnsHouse', y='Age', data=df);"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "ee08a262",
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
     "sns.boxplot(x='OwnsHouse', y='Age', data=df);\n",
-    "# optional\n",
-    "sns.swarmplot(x='OwnsHouse', y='Age', data=df, linewidth=1, size=3);"
+    "sns.swarmplot(x='OwnsHouse', y='Age', hue='OwnsHouse', data=df, linewidth=1, size=3, legend=False);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 17,
    "id": "f793503f",
    "metadata": {
     "hidden": true
@@ -1180,32 +828,65 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " _________________________________________\n",
-      "/ Where on Earth ALL younger people own a \\\n",
-      "\\ house while elder people do not?        /\n",
-      " -----------------------------------------\n",
-      "        \\   ^__^\n",
-      "         \\  (oo)\\_______\n",
-      "            (__)\\       )\\/\\\n",
-      "                ||----w |\n",
-      "                ||     ||\n"
+      " ________________________________________\r\n",
+      "/ Where on Earth do younger people own a \\\r\n",
+      "\\ house while elder people do not?       /\r\n",
+      " ----------------------------------------\r\n",
+      "        \\   ^__^\r\n",
+      "         \\  (oo)\\_______\r\n",
+      "            (__)\\       )\\/\\\r\n",
+      "                ||----w |\r\n",
+      "                ||     ||\r\n"
      ]
     }
    ],
    "source": [
-    "!cowsay \"Where on Earth ALL younger people own a house while elder people do not?\""
+    "!cowsay \"Where on Earth do younger people own a house while elder people do not?\""
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "1e94c17b",
+   "id": "fbe5459a",
    "metadata": {
-    "heading_collapsed": true
+    "hidden": true
+   },
+   "source": [
+    "Alternative representation:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "3d1a44e6",
+   "metadata": {
+    "hidden": true
    },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sns.histplot(hue='OwnsHouse', y='Age', data=df, kde=True);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e94c17b",
+   "metadata": {},
    "source": [
     "## Q\n",
     "\n",
-    "Isolate the house-owners group from the others, draw their respective age distributions and report their mean ages as $99\\%$ confidence intervals."
+    "Isolate the house-owners group from the others, and report their mean ages as $99\\%$ confidence intervals."
    ]
   },
   {
@@ -1220,7 +901,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 19,
    "id": "55d18f16",
    "metadata": {
     "hidden": true
@@ -1236,27 +917,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "id": "3d1a44e6",
+   "execution_count": 31,
+   "id": "4f129b2a",
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [],
+   "source": [
+    "mean = np.mean(house_owners_age)\n",
+    "sem = stats.sem(house_owners_age)\n",
+    "distribution_of_the_mean = stats.norm(mean, sem)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "9613dc45-cdac-4932-b646-d36965d2d4e6",
    "metadata": {
     "hidden": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "(37.56221005578753, 42.072095499768025)"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "sns.histplot(hue='OwnsHouse', y='Age', data=df, kde=True);"
+    "distribution_of_the_mean.interval(.99)"
    ]
   },
   {
@@ -1266,12 +959,14 @@
     "hidden": true
    },
    "source": [
-    "For the confidence intervals, we need to evaluate the inverse survival function of the standard normal distribution at $0.5\\%$."
+    "Alternative calculation, for both groups:\n",
+    "\n",
+    "First we need to evaluate the inverse survival function of the standard normal distribution at $0.5\\%$."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 20,
    "id": "1fca5a60",
    "metadata": {
     "hidden": true
@@ -1284,7 +979,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 21,
    "id": "9f044f06",
    "metadata": {
     "hidden": true
@@ -1309,29 +1004,6 @@
     "    print(f'{group_name}: {m:.2f} ± {z_times_sem:.2f} years old on average')"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "9613dc45-cdac-4932-b646-d36965d2d4e6",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(37.56221005578753, 42.072095499768025)"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "mean = np.mean(house_owners_age)\n",
-    "sem = stats.sem(house_owners_age)\n",
-    "stats.norm(mean, sem).interval(.99)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "ea79970d",
@@ -1341,7 +1013,7 @@
    "source": [
     "## Q\n",
     "\n",
-    "Check the age is normally distributed in any one group, first following a graphical approach."
+    "Check whether the age is normally distributed in a group, first following a graphical approach."
    ]
   },
   {
@@ -1351,43 +1023,20 @@
     "heading_collapsed": true
    },
    "source": [
-    "## A (with nested Q&A)"
+    "## A"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 13,
    "id": "6ec85793-d159-47ac-bf2e-d28778dbb865",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "stats.probplot(house_owners_age, fit=True, plot=plt);"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "id": "ddf5d4b0",
    "metadata": {
     "hidden": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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d9+qV+DDN9WWQTy0KhfU7doSXXoJbb4VXXw2tfkmbVCb+ukAX4P+5+x7AT5To1okmAy61TJO7j3T3fHfPb968eQrDFJGSip/Ajbd1X6xu3dCnv2gR9Oz6CRx6KAwYAF27wvvvhye86tRJScwSv1Qm/qXAUnd/K1p/nPCLYLmZtQSI3r9OYQwiUgmVeQK3QQMYNw56nrIWRoyA3XaDuXPDqJ2pU2HHHVMRqlRCyhK/u38FfG5m7aNN3YD5wFNA72hbb+DJVMUgIvGL7ctPtGtnwAD45Rfo2eld2HtvuOgiOOIImD8f+vQJJ5UaI9UPcJ0LFJhZfWAhcAbhl82jZtYXWAycnOIYRKQCAweGwpeJatw4dOH3POk3uOJquP56aNYMHn0UTjpJCb+GSmnid/e5QGljtbql8roiEr/KJP3c3DBip2dP4I03YI++8OGHcPrpcPPNYQepsVSyQSSLFRSEFnu8cnPD9IZAuPM7ZCjcfjtsvz1MmQJHHpmSOCW5lPhFstjgwfFPf1i/fsy4/GnT4Mwzw/CdQYPguuugSZNUhSlJplo9Illq4MD4b+I2bhzV2TnqO+jbFw47LPwmeOUVuPNOJf0Mo8QvkkViR+7E06/fuHEYl//jj9Cz4aTw4NX48XDJJaGo2gEHpD5oSTp19YhkiURv4q4vrrZ8OZx8Ljz2GHTuDM88A126pCpMqQZK/CJZIJFqmhBKLvT8m8P9D8CQIeFG7jXXhPLJ9eqlLE6pHgklfjPLARq7+w8pikdEkizRpF+/Ptxy/hI46ix47jnYd9/w9O3OO6cuSKlWFfbxm9mDZrZFVGBtHjDfzC5MfWgiUlWJJv0mjYp49dS7OOHyjjBzZhiqOXOmkn4tE8/N3Q5RC78H8Cyh6uZpqQxKRKpm4MBwAzeRpN9774/5YY+D+OP4c0Irf948OPdcyNEYkNomnq6eemZWj5D473T3380szpG/IlLdOnYMJXLiVY/feXSvm+gx59+hiP64ceEJXJVbqLXi+VV+L2GKxEbAK2aWB6iPX6SGKW7lx5v0GzSAZ66ew5o99qLHW5fCMceEg3v3VtKv5Sps8bv77cDtMZsWm9khqQtJRBKVaF/+EQf/yrP7DoMrbwgD+x9/HP7859QFKDVKPDd3W5jZGDN7NlrvwIayyiKSZokm/fP2fI1nv+wM114Lp50WWvlK+lklnq6eccDzwLbR+gJgSIriEZE4FHfrJHIDtxGreWL787ht9gHw66/w/PNw332hjLJklXgS/9bu/ihQBODua4F1KY1KRMrUsWPiZZSPzHme5bkdOWHZnWGkzrx58Kc/pSZAqfHiSfw/mVku0dy4ZrY38H08JzezRWb2vpnNNbPCaFszM5tqZp9E700rHb1Ilhg4MIyqTOTmLUBTvuW5ln9nStERNGreMIzJv+22UIRHslY8wzkvIEyX2NbMXgOaAyclcI1D3P2bmPVLgOnufr2ZXRKtX5zA+USySqLDM4udyEQmbDmIzb/+BoYOhcsvD0N5JOvFM6pntpkdBLQHDPjY3ROchnkjxwMHR8vjgRko8YuUqnv3xJP+NnzJnZzDn3kCdtwDxj4XiquJRCpM/GZ2eolNXcwMd78/jvM78EL0wNe97j4SaOHuX0affwW0KOO6/YH+AK1atYrjUiK1S6KjdcDpzXhu4Xy2qPcLDLse/vEPqKtajLKxeP5F/DFmuQFhvtzZQDyJf393X2ZmfwCmmtlHsR+6u5f1FHD0S2IkQH5+vp4UlqxRmTlw81jEmDr96bZuaqiRP2oUtG+fmgAl48XT1XNu7LqZbQU8HM/J3X1Z9P61mU0CugLLzaylu39pZi2BrxOOWqSWSrQ/P4d1DGtxF5etvizc+b3hLjj7bNXXkXJV5l/HT4RCbeUys0Zm1qR4GfgTobrnU2x4AKw38GQlYhCpVQoKQo9MIkm/g33Igm0O5LLlg0Mr/4MPNgz/ESlHPH38TxMN5ST8ougAPBrHuVsAkyzU/KgLPOjuz5nZO8CjZtYXWAycXJnARWqDggLo0wfWrIn/mIb1fuenK4fDVVfBmsZw//3Qq5fq60jc4unjvzFmeS2w2N2XVnSQuy8Edi9l+0rCfQKRrJb4zVvowmymtuwDl78LJ58c6uW3KHV8hEiZ4unjf7k6AhHJJokm/Qb8wn/sP/zTbiRnTXOYNAl69EhZfFK7lZn4zexHNnTxbPQRYUDOFimLSqQWGzgwsaR/AK/w2Jb9aPH9J9CnL4wYAU31wLtUXpmJ392bVGcgItmgoCD+oZpN+IF7m17Kqd/dDc3awMRp0E29pFJ1cT/ZEY3FX/+8t7svSUlEIrXY0KHx7XcEzzJ+s7P4w6qlMGQIXH01NGqU0tgke8RTj/84M/sE+B/wMmE2rmdTHJdIrbR4cfmfN2MlE3JO51mO4g9tm8Drr8MttyjpS1LFM+B3GLA3sMDd2xBG5LyZ0qhEaqHu3cv71PkLj7Jsi13omfMQXHEFzJ4Ne+9dXeFJFokn8f8eDcHMMbMcd38JyE9xXCK1Snk3dFvyBZM4gUc5hQbtWsGsWWGM/mabVW+QkjXi6eNfZWaNgVeAAjP7mvD0rojE6Z57Stvq9GEsN/EPNuO3MFpnyBAVVZOUK7PFb2Z/MbMGhDLKPwPnA88BnwHHVk94Iplv4EDwEgOj27CQaXRnDP2YS2deuPF9+Oc/lfSlWpiX/BdZ/EEoqrYfYb7dh4Dn3T0tUy7m5+d7YWFhOi4tUmU5ORsSfw7rOJc7uIahrKMOFzKCBxueyY8/qb6OJJ+ZzXL3Tbrmy/zX5u4nADsB04BzgaVmdk80KYuIVKC48Fpx0u/AB7zGftzK+bzEIXRgPqPsLO4ZqaQv1avcf3Hu/oO7j3f3I4FOwBzgdjP7vFqiE8lQBQVw2mmwbh3UYw1XcBVz2IOd+JS/UcCxPM0ytueBB6Bnz3RHK9kmrg7FaEL0E4FTgGbA46kMSiTT9esXWvr5vMMY+rIb7/MQf+U8bucbmgMwYICSvqRHeTd3G5vZaWY2BZhPGMI5DGjl7udXV4AimWbgQLBff2Y4F/Ime5PLSo7jSf7GQ+uTPsDdd6cxSMlq5bX4FxFG8dxNuLFblQnWRbLGx/fO4F3OpB2fci/9uYjh/MCWG+0zYECaghOh/MS/g7v/UtULmFkdoBBY5u7HmFkbwtSNucAs4DR3T2AaCpEa6vvv4eKLmV50L5/SlkN4kRkcssluHTqotS/pVd6onion/chg4MOY9RuAW9x9J+A7oG+SriOSPs88Ax07UjRyFDfyD3bjvVKTfrduYYZEkXRK6TgyM9seOBoYHa0bcCgbbg6PB3qkMgaRlFqxItyhPeYYVllT9vE3uJAb+YWGpe4+bVo1xydSilQPIL4VuAgoitZzgVXuvjZaXwpsl+IYRJLPHR56KPTbPPYY7534b1osncXbdC3zkLy86gtPpDzlzcAVO8n6Jtz9uPJObGbHAF+7+ywzOzjRwMysP9AfoFWrVokeLpI6S5eGu7OTJ0PXrjBmDHv9sRMV3ai65ppqiU6kQuW1+G8EbiLU4f8FGBW9VhPq9VRkP+A4M1tEuJl7KHAbsJWZFf/C2R5YVtrB7j7S3fPdPb958+al7SJSvYqKYORI6NgxlNq8+WYG7fE6tmsnfv214sM1Zl9qivKmXnwZwMxuKlHr4Wkzq7BwjrtfClwaneNg4J/u3tPMHgNOIvwy6A08WenoRarLp5/CmWfCjBlwyCH8q+Uohl3QNu7D1c0jNUk8ffyNzGzH4pVoOGZVpgO6GLjAzD4l9PmPqcK5RFJr7Vq46SbYbbcwMcqoUQxsP51hD8af9OvWVTeP1CzxlGw4H5hhZgsBA/KAsxK5iLvPAGZEywuhnDtgIjXF++9D377wzjtw7LFhlvTttuOe/vGfokEDGD1a3TxSs1SY+N39OTNrB+wcbfrI3X9LbVgiafTbb3DtteHVtCk8/DCcfDKYUVCwaW39snTrpuGbUjNVmPjNrCFwAZDn7meaWTsza+/uk1Mfnkg1e+ut0Mr/4APo1StMdL711us/7tcvvtN06KCkLzVXPH389wFrgH2i9WXA1SmLSCQdfvoJLrgA9tknlF6YPBkeeGB90i+urR/P6J0BA/R0rtRs8fTxt3X3U8zsVAB3/zl6AlekdnjxxTBiZ+HCkLWvvx622GL9x8W19Svq4lHXjmSKeFr8a8xsc6KHucysLaA+fsl8q1aFhN+tW5gfccaMUD0tJukDDB5ccdJv1EhJXzJHPIn/SkJ55h3MrACYTijDIJK5nnwydMSPHQsXXQTvvQcHlT6r6MqVFZ/u3nuTHJ9ICpXb1WNmOUDx7Ft7E4ZzDnb3b6ohNpHk+/prOO88eOSRMDb/qacgf5O5qNfr3r3iU3brpuGaklkqmnO3CLjI3Ve6+zPuPllJXzKSO0yYALvsApMmwbBhUFhYZtIvKIDNNguVGcqj0TuSieK5uTvNzP4JPAL8VLzR3b9NWVQiyfT553D22TBlCuy9N4wZEzJ2Gbp3rzjhg27mSuaKJ/GfEr0PitnmwI6l7CtScxQVhc73iy+Gdevg1lvhnHOgTp1Sdx84MDycGw8zJX3JXPE8udumOgIRSaoFC8LTVjNnhib8yJHQpux/yh07wvz58Z/+7LOTEKNImlQ4qsfMGprZ5WY2MlpvF9XaF6l51q6F4cNh991DrZ2xY+GFF5Ka9OvX15y5ktkSeXJ332hdT+5KzfTuu7DXXqFr58gjQzY/44zQL1OK4qdxE0n6ZuF3iUgmiyfxt3X34cDvEJ7cJQzrFKkZfvsNrrgijNBZuhQeewwmToSWLUvdfeDAkMB79Qpd//GqWzdUcdDQTcl08dzc1ZO7UnO98UYoqvbhh3D66XDzzZCbW+bu8Y7YKWnAAHXvSO2hJ3clM61eDUOGwH77hQJrzz4L48eXmfSLW/mJJv0BA8IjAEr6UpvEM6pnqpnNJsEnd82sAfAKsFl0ncfd/cpoBq+HCbNvzQJOc/eK5qkW2WDqVOjfHxYtgkGD4LrroEmTMndP9OYthGH+qrAptVWZLX4z61L8Isy69SXwBdAq2laR34BD3X13oDNwhJntDdwA3OLuOwHfAX2r+B0kW3z3HfTpA3/6Uxha88orcOedSvoiCSqvxX9T9N4AyAfeJbT4dwMK2VCfv1Tu7sDqaLVe9HLgUOBv0fbxwL+BOB+bkaw1aVLor1mxAi69FP71rzCvYTm6d0886etpXMkGZbb43f0Qdz+E0NLv4u757r4nsAdhSGeFzKyOmc0FvgamAp8Bq9x9bbTLUmC7Mo7tb2aFZla4YsWKuL+Q1DJffQV/+QuceCJssw28/XaYErGcpB9vnZ1YjRuHUj5K+pIN4rm5297d3y9ecfd5wC7xnNzd17l7Z2B7wgTrO5d/xEbHjox+2eQ3b9483sOktnAPN2s7dICnnw7J/u23oUv5vYzFk6asifOukVlI+D/+qGGakj3iGc75vpmNBiZE6z2B9xK5iLuvMrOXCN1DW5lZ3ajVvz1x/vUgWWTxYjjrLHj+edh331BUbef42gz9+sU/GXrjxnDPPUr4kn3iafH/HfgAGBy95gNnVHSQmTU3s62i5c2Bw4APgZeAk6LdegNPJhq01FJFReFmbceO8OqrcMcdodZOnEm/Y8f45sTt0CH8clArX7JVRROx1AGejfr6b0nw3C2B8dE5coBH3X2ymc0HHjazq4E5wJhKxC21zccfhwexXnsNDj88VNXMy4vr0IKCMNgnnu6d+vU1Ykek3MTv7uvMrMjMtnT37xM5sbu/R7gRXHL7QkJ/vwj8/jvceCP85z/QsCGMGxeewC2jvk6sRMoog+rsiBSLp49/NaGffyobT8RyXsqikuwwZ05o5c+ZAyedFLp2ttkmrkMTLb3QoAGMHq2uHRGIL/E/Eb1EkuPXX+Gqq0L55K23DgXVTjwxrkMTbeWDxuaLlBRP4n8E2Cla/tTd47h9JlKGV18NrfwFC0LJ5JtugqZNKzysoAB6906smiZoTlyR0pRXsqGumQ0nPGQ1Hrgf+NzMhptZveoKUGqJH38M0x4ecEAoo/z886HDvYKkX1AQhl0mWkIZQktfN3JFNlXecM4RQDOgjbvv6e5dgLbAVsCN1RCb1BbPPw+dOoUSl+edB/PmhXo75Sh++rZXr1B8M1EDBqilL1KW8hL/McCZ7v5j8QZ3/wEYAByV6sCkFvj229A/c8QRYcTOq6/CbbeFJnyMgQMhJyeMuil+9eoV/9O3sYpLL6iMskjZyuvj96jQWsmN68wszmcjJWs9/ngomfzttzB0KA+1vZxzj2vAypWpuVydOqHCg0btiFSsvMQ/38xOd/f7YzeaWS/go9SGJRnryy9ZctwgWhVOYhZd6MvzvHtN55ReMjc3/CGhpC8Sn/IS/yDgCTPrQ5gwBUJ55s2BE1IdmGSGggIYPBhWrnT+zjhu5gL+wC9czPXcxD9YF9fAscrRME2Ryinz/0p3XwbsZWaHAh2jzVPcvRIzlkptsCHJb7y9Nf/jIfpzGNN4hQPox2g+4f9SFoeKq4lUTTxTL74IvFgNsUgNUlaSj5XDOgZxF9dxKUXkMIC7uZez8Lhq/yVOCV8kOVL3d7jUeAUFMHRoqIJsFn85Y4Cd+ZAx9GVf3mAKR3I29/A5rZIeY05OqNCsUToiyZOappnUKAUF0Lp1SO6xwyZ79QpJH+JP+nX5naFczVw6056P6cUDHM0zSUn6xUMx3Te81q1T0hdJNrX4a4nY1nudOiFhFr/HSqRVX1IXZjGWPuzOezzCyZzLHazgDwmfR6NwRNJLLf4UKW5l5+SE94KCTbcNHFj2+tZbh1fsshnUrRveY7fl5Gzcei9O9omWOChLA37hei7mbbrSnBX0YBJ/5ZEKk35u7qYteHf45hslfZG0cveUvIAdCLNtzSeawSva3oww8fon0XvTis615557eqImTHDPy3M3C+8TJiT/+LL2mTDBvWHDjdNdvXru9euXTIE1/3UAL/vHtHMHH0k/35LvSt0vNzfxn7GIpBZQ6KXl59I2JuNFmIGrS7TcBFgAdACGA5dE2y8BbqjoXIkm/tISb8OG8SemeI4vb5+8vPQn7Kq+mvC938UAd/DPaOOHMk1JXiTDlJX4LXyWemb2JHBn9DrY3b80s5bADHdvX96x+fn5XlhYGPe1Wrfe0O0RKy8PFi1KzvHl7bNkSdX60tPtSKZwD2ezPUv5+Igh7PL4MGjUKN1hiUiCzGyWu+eX3F4tffxm1powDeNbQAt3/zL66CugRRnH9DezQjMrXLFiRULXW7Ikse2VOb68fVolf1RjSuRE//Xz8qK++BXf4L1OYwpH06pDE3LeeJ1dnr1ZSV+klkl54jezxsBEYIiH6p7rRX+KlNo2dveR7p7v7vnNmzdP6JplJd54E3I8x5e3zzXXhGKUserVCxN9V4fihF6nzsbv6xO8bxgq6Q6L/uf0rPtImLXk4YfhX/+C2bNh772rJ2ARqVYpTfzRhC0TgQJ3L56+cXnUxUP0/nWyr1ta4m3YMGxP1vHl7dOzJ4wcGRKtWXi/774w70jstgEDyl7PzQ2v2GXYkMRL21ac2IsT+tq1G78vWlTKaJovvoAePeCvfw0nmDUrTHy+2Wbx/bBEJPOU1vGfjBdghFm7bi2xfQQb39wdXtG5Mm1UT0YoKnIfNcp9yy3dGzRwHzHC/fff0x2ViCQR1X1z18z2B2YC7wNF0ebLCP38jwKtgMXAye7+bXnnSvTmrlRg4UI480x48UU46CAYPRp22qni40Qko5R1czdlT+66+6uEVn9puqXqulKOdevg9tvDI75168K990K/fhtuCohIVlDJhmwxbx707Qtvvw1HHx3KXG6/fbqjEpE0UFOvtluzJtys7dIldPE8+CA8/bSSvkgWU4u/NnvnHejTJ7T2Tz01VEZLcGisiNQ+avHXRj//DP/8ZxiH/9138NRToaWvpC8iqMVf+8yYEW7YfvZZmMHkhhtgyy3THZWI1CBq8dcW338fEv0hh4T1F18MN3CV9EWkBCX+2uDpp0O5hdGjQxfPe+9t+AUgIlKCEn8mW7EC/vY3OO44aNYM3ngDRozYtJaEiEgMJf5M5B5u1u6yCzz+eBiuOWsWdO2a7shEJAPo5m6mWbo0VHObPBn22gvGjIGOHdMdlYhkELX4M0VRUSix0KEDTJ8ON98Mr72mpC8iCVOLPxN88kkoqvbyy3DooTBqFOy4Y7qjEpEMpRZ/TbZ2Ldx4I+y2G8yZExL+tGlK+iJSJWrx11TvvReKqhUWhlE7d98N222X7qhEpBZQi7+m+e03uPJK2HPPMJv7I4/Af/+rpC8iSaMWf03y5puhlT9/PvTqBbfeumF+RRGRJElZi9/MxprZ12Y2L2ZbMzObamafRO9NU3X9jPLTT3DBBbDvvvDDD/DMM/DAA0r6IpISqezqGQccUWLbJcB0d28HTI/Ws9v06bDrrnDLLXD22fDBB3DUUemOSkRqsZQlfnd/BSg5l+7xwPhoeTzQI1XXr/FWrQpVNLt3D9MgvvxyuIG7xRbpjkxEarnqvrnbwt2/jJa/AlqUtaOZ9TezQjMrXLFiRfVEV12efDI8iHXffXDRRfDuu3DggemOSkSyRNpG9bi7A17O5yPdPd/d85vXlglEli+HU06BHj3CpChvvRXq5W++ebojE5EsUt2Jf7mZtQSI3r+u5uunhztMmBBa+f/9L1x9dRifn5+f7shEJAtVd+J/CugdLfcGnqzm61e/JUvg6KPhtNOgfXuYOxeGDoV69dIdmYhkqVQO53wIeANob2ZLzawvcD1wmJl9AnSP1munoqJws7Zjx3Dj9rbbYObMUEpZRCSNUvYAl7ufWsZH3VJ1zRpjwYIwYmfmzDBqZ+RIaNMm3VGJiAAq2ZBca9eGm7W77Qbvvw9jx8ILLyjpi0iNopINyfLuu9CnD8yeDSecAHfdBS1bpjsqEZFNqMVfVb/+CpdfHkboLFsWpkJ84gklfRGpsdTir4rXXw9F1T76CHr3DrNiNWuW7qhERMqlFn9lrF4N550H++8PP/8Mzz0H48Yp6YtIRlDiT9QLL0CnTnDHHTBoEMybB4cfnu6oRETipsQfr+++gzPOCEm+QYMwVPOOO6BJk3RHJiKSECX+eDzxRCi38MADcOml4enb/fdPd1QiIpWim7vl+eorOOccmDgROneGKVNgjz3SHZWISJWoxV8a93CztkMHmDwZrr0W3n5bSV9EagW1+EtatAjOOivcxN1vPxg9GnbeOd1RiYgkjVr8xYqKws3aTp3gtdfC8iuvKOmLSK2jFj+EB7D69QsJ//DD4d57IS8v3VGJiKREdrf4f/899N/vvjvMnw/jx8Ozzyrpi0itlr0t/tmzQ7mFuXPhpJPgzjuhRZlTAIuI1BppafGb2RFm9rGZfWpml1TrxX/5JYzF79o1DNecOBEee0xJX0SyRrW3+M2sDnAXcBiwFHjHzJ5y9/kpv/irr4ZW/oIF4Sncm26Cpk1TflkRkZokHS3+rsCn7r7Q3dcADwPHp/SKP/4YHsQ64ABYsyYM1Rw7VklfRLJSOhL/dsDnMetLo20bMbP+ZlZoZoUrVqyo/NWeey4M0bz7bhg8OMyMddhhlT+fiEiGq7Gjetx9pLvnu3t+8+bNK3eSs86CI4+ERo3CUM1bb4XGjZMap4hIpklH4l8G7BCzvn20Lfl22inMjjVnDuyzT0ouISKSadIxnPMdoJ2ZtSEk/L8Cf0vJlS68MCWnFRHJZNWe+N19rZmdAzwP1AHGuvsH1R2HiEi2SssDXO4+BZiSjmuLiGS7GntzV0REUkOJX0Qkyyjxi4hkGSV+EZEso8QvIpJllPhFRLKMuXu6Y6iQma0AFpfYvDXwTRrCSTV9r8yi75VZsu175bn7JjVvMiLxl8bMCt09P91xJJu+V2bR98os+l6BunpERLKMEr+ISJbJ5MQ/Mt0BpIi+V2bR98os+l5kcB+/iIhUTia3+EVEpBKU+EVEskxGJ34zG2Zm75nZXDN7wcy2TXdMyWBmI8zso+i7TTKzrdIdUzKY2V/M7AMzKzKzjB9SZ2ZHmNnHZvapmV2S7niSwczGmtnXZjYv3bEkk5ntYGYvmdn86N/g4HTHlAxm1sDM3jazd6Pv9Z+4jsvkPn4z28Ldf4iWzwM6uPvZaQ6ryszsT8CL0aQ1NwC4+8VpDqvKzGwXoAi4F/inuxemOaRKM7M6wALgMGApYWa5U919floDqyIzOxBYDdzv7p3SHU+ymFlLoKW7zzazJsAsoEct+O9lQCN3X21m9YBXgcHu/mZ5x2V0i7846UcaAZn7WyyGu7/g7muj1TcJ8xJnPHf/0N0/TnccSdIV+NTdF7r7GuBh4Pg0x1Rl7v4K8G2640g2d//S3WdHyz8CHwLbpTeqqvNgdbRaL3pVmAczOvEDmNk1ZvY50BP4V7rjSYE+wLPpDkI2sR3wecz6UmpBIskGZtYa2AN4K82hJIWZ1TGzucDXwFR3r/B71fjEb2bTzGxeKa/jAdx9qLvvABQA56Q32vhV9L2ifYYCawnfLSPE871E0sXMGgMTgSElegwylruvc/fOhJ6BrmZWYRddWubcTYS7d49z1wLCPL5XpjCcpKnoe5nZ34FjgG6eQTdiEvjvlemWATvErG8fbZMaKuoDnwgUuPsT6Y4n2dx9lZm9BBwBlHtzvsa3+MtjZu1iVo8HPkpXLMlkZkcAFwHHufvP6Y5HSvUO0M7M2phZfeCvwFNpjknKEN0EHQN86O43pzueZDGz5sWj/sxsc8JggwrzYKaP6pkItCeMFFkMnO3uGd/qMrNPgc2AldGmN2vJaKUTgDuA5sAqYK67H57WoKrAzI4CbgXqAGPd/Zr0RlR1ZvYQcDChzO9y4Ep3H5PWoJLAzPYHZgLvE/IFwGXuPiV9UVWdme0GjCf8G8wBHnX3qyo8LpMTv4iIJC6ju3pERCRxSvwiIllGiV9EJMso8YuIZBklfhGRLKPEL9XKzHKjaqpzzewrM1sWLa8ys2otmGVmPcysQ8z6VWaW8ANoZtY6ndUszeyyEuuvR+9pjUtqLiV+qVbuvtLdO0ePmN8D3BItd2bD+OqkMbPynk7vAaxP/O7+L3efluwYqsFGid/d901XIJIZlPilJqljZqOiuuIvRE8iYmZtzew5M5tlZjPNbOdoe2szezGat2C6mbWKto8zs3vM7C1geGnHm9m+wHHAiOgvjrbRcSdF5/ijmb0e1Tl/28yaRNebaWazo1e5CdaCOy3U7J9mZlNizr/IzLaOlvPNbEa03NXM3jCzOdH120fb/25mT0Tf4xMzGx5tvx7YPPoOBdG21aXEUsfCPA/vRD+vs6LtLc3slej4eWZ2QBX/G0omcHe99ErLC/g3oS4/QGtCQbrO0fqjQK9oeTrQLlreizBXAcDTQO9ouQ/w32h5HDAZqFPB8eOAk2LiGQecBNQHFgJ/jLZvQahr1RBoEG1rBxTGxD6vlO93IjCV8FTltoSnlU+KPlsEbB0t5wMzYq8VLXcHJkbLf49i2hJoQHhSfYfos9Ulrru6ZFxAf+DyaHkzoBBoA/wDGBptrwM0Sfe/C71S/6rxRdokq/zP3edGy7OA1lE1xX2Bx0K5FSAkLoB9CMkV4AFgeMy5HnP3dRUcX5b2wJfu/g5smPfBzBoBd5pZZ2Ad8H8VnOdA4CF3Xwd8YWYvVrA/hMQ+PqpD5YT66sWmu/v3USzzgTw2Lg1dnj8BuxX/xRFdpx2h5tDYqIDZf2N+/lKLKfFLTfJbzPI6YHNCd+QqD/cBEvFT9F7Z40tzPqF+ze7ReX+twrnWsqGrtUHM9mHAS+5+goW68TNiPiv580nk/18DznX35zf5IMy6dTQwzsxudvf7EzivZCD18UuNFrW2/2dmf4H1/ea7Rx+/TqiKCWEinpkJHv8j0KSUy34MtDSzP0bHNIluEm9J+EugCDiN0DVSnleAU6L+9ZbAITGfLQL2jJb/HLN9SzaUd/57Becv9nvUYi/P88CA4v3M7P/MrJGZ5QHL3X0UMBroEuc1JYMp8Usm6An0NbN3gQ/YMMXhucAZZvYeIRGXNYF2Wcc/DFwY3UhtW7yzh6kUTwHuiI6ZSmiV3w30jrbtzIa/KsoyCfgEmA/cD7wR89l/gNvMrJDQei82HLjOzOYQf4t+JPBe8c3dMoyO4pgdDfG8Nzr/wcC70fVOAW6L85qSwVSdU6SamNk4YLK7P57uWCS7qcUvIpJl1OIXEckyavGLiGQZJX4RkSyjxC8ikmWU+EVEsowSv4hIlvn/8GFUaAmGuzwAAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -1399,141 +1048,190 @@
     }
    ],
    "source": [
-    "(theoretical_quantiles, observed_quantiles), (slope, intercept, _) = stats.probplot(house_owners_age, fit=True)\n",
-    "plt.scatter(theoretical_quantiles, observed_quantiles, marker='+', color='b')\n",
-    "plt.axline((0, intercept), slope=slope, color='r')\n",
-    "plt.xlabel('theoretical quantiles')\n",
-    "plt.ylabel('ordered observations (age)');"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 18,
-   "id": "bc84e35b-fb1b-456c-9ce5-82cd77efe4a0",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "3"
-      ]
-     },
-     "execution_count": 18,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "a = ((1, None, 3), 'odfh', dict())\n",
-    "(e, f, g), c, d = a\n",
-    "g"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "24b49c4c",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "The red line is fitted to the blue points and does not align well on the linear part.\n",
-    "\n",
-    "### Q\n",
-    "\n",
-    "To better illustrate that the central part is approximately linear, perform a linear regression with the observations whose corresponding theoretical quantiles (abscissa) fall in the $[-1,1]$ interval, and make a probability plot replacing the default regression line by your regression line."
+    "stats.probplot(house_owners_age, fit=True, plot=plt);"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "153d570e",
+   "id": "f9008612",
    "metadata": {
-    "heading_collapsed": true,
     "hidden": true
    },
    "source": [
-    "### A"
+    "`probplot` does not allow customizing the plot, but conveniently provides the elements to reproduce the plot with lower-level functions."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
-   "id": "0f888c53",
+   "execution_count": 34,
+   "id": "5575fa6c",
    "metadata": {
     "hidden": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "central_part = (-1<theoretical_quantiles) & (theoretical_quantiles<1)\n",
-    "b, a, _, _, _ = stats.linregress(theoretical_quantiles[central_part], observed_quantiles[central_part])\n",
-    "plt.scatter(theoretical_quantiles, observed_quantiles, marker='+', color='b')\n",
-    "plt.axline((0, a), slope=b, color='r');"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "id": "f976e7bb-9713-4e6c-8853-e226a3f8c5d0",
-   "metadata": {},
+   },
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "array([-0.98673271,  0.98673271])"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on function probplot in module scipy.stats._morestats:\n",
+      "\n",
+      "probplot(x, sparams=(), dist='norm', fit=True, plot=None, rvalue=False)\n",
+      "    Calculate quantiles for a probability plot, and optionally show the plot.\n",
+      "    \n",
+      "    Generates a probability plot of sample data against the quantiles of a\n",
+      "    specified theoretical distribution (the normal distribution by default).\n",
+      "    `probplot` optionally calculates a best-fit line for the data and plots the\n",
+      "    results using Matplotlib or a given plot function.\n",
+      "    \n",
+      "    Parameters\n",
+      "    ----------\n",
+      "    x : array_like\n",
+      "        Sample/response data from which `probplot` creates the plot.\n",
+      "    sparams : tuple, optional\n",
+      "        Distribution-specific shape parameters (shape parameters plus location\n",
+      "        and scale).\n",
+      "    dist : str or stats.distributions instance, optional\n",
+      "        Distribution or distribution function name. The default is 'norm' for a\n",
+      "        normal probability plot.  Objects that look enough like a\n",
+      "        stats.distributions instance (i.e. they have a ``ppf`` method) are also\n",
+      "        accepted.\n",
+      "    fit : bool, optional\n",
+      "        Fit a least-squares regression (best-fit) line to the sample data if\n",
+      "        True (default).\n",
+      "    plot : object, optional\n",
+      "        If given, plots the quantiles.\n",
+      "        If given and `fit` is True, also plots the least squares fit.\n",
+      "        `plot` is an object that has to have methods \"plot\" and \"text\".\n",
+      "        The `matplotlib.pyplot` module or a Matplotlib Axes object can be used,\n",
+      "        or a custom object with the same methods.\n",
+      "        Default is None, which means that no plot is created.\n",
+      "    \n",
+      "    Returns\n",
+      "    -------\n",
+      "    (osm, osr) : tuple of ndarrays\n",
+      "        Tuple of theoretical quantiles (osm, or order statistic medians) and\n",
+      "        ordered responses (osr).  `osr` is simply sorted input `x`.\n",
+      "        For details on how `osm` is calculated see the Notes section.\n",
+      "    (slope, intercept, r) : tuple of floats, optional\n",
+      "        Tuple  containing the result of the least-squares fit, if that is\n",
+      "        performed by `probplot`. `r` is the square root of the coefficient of\n",
+      "        determination.  If ``fit=False`` and ``plot=None``, this tuple is not\n",
+      "        returned.\n",
+      "    \n",
+      "    Notes\n",
+      "    -----\n",
+      "    Even if `plot` is given, the figure is not shown or saved by `probplot`;\n",
+      "    ``plt.show()`` or ``plt.savefig('figname.png')`` should be used after\n",
+      "    calling `probplot`.\n",
+      "    \n",
+      "    `probplot` generates a probability plot, which should not be confused with\n",
+      "    a Q-Q or a P-P plot.  Statsmodels has more extensive functionality of this\n",
+      "    type, see ``statsmodels.api.ProbPlot``.\n",
+      "    \n",
+      "    The formula used for the theoretical quantiles (horizontal axis of the\n",
+      "    probability plot) is Filliben's estimate::\n",
+      "    \n",
+      "        quantiles = dist.ppf(val), for\n",
+      "    \n",
+      "                0.5**(1/n),                  for i = n\n",
+      "          val = (i - 0.3175) / (n + 0.365),  for i = 2, ..., n-1\n",
+      "                1 - 0.5**(1/n),              for i = 1\n",
+      "    \n",
+      "    where ``i`` indicates the i-th ordered value and ``n`` is the total number\n",
+      "    of values.\n",
+      "    \n",
+      "    Examples\n",
+      "    --------\n",
+      "    >>> from scipy import stats\n",
+      "    >>> import matplotlib.pyplot as plt\n",
+      "    >>> nsample = 100\n",
+      "    >>> rng = np.random.default_rng()\n",
+      "    \n",
+      "    A t distribution with small degrees of freedom:\n",
+      "    \n",
+      "    >>> ax1 = plt.subplot(221)\n",
+      "    >>> x = stats.t.rvs(3, size=nsample, random_state=rng)\n",
+      "    >>> res = stats.probplot(x, plot=plt)\n",
+      "    \n",
+      "    A t distribution with larger degrees of freedom:\n",
+      "    \n",
+      "    >>> ax2 = plt.subplot(222)\n",
+      "    >>> x = stats.t.rvs(25, size=nsample, random_state=rng)\n",
+      "    >>> res = stats.probplot(x, plot=plt)\n",
+      "    \n",
+      "    A mixture of two normal distributions with broadcasting:\n",
+      "    \n",
+      "    >>> ax3 = plt.subplot(223)\n",
+      "    >>> x = stats.norm.rvs(loc=[0,5], scale=[1,1.5],\n",
+      "    ...                    size=(nsample//2,2), random_state=rng).ravel()\n",
+      "    >>> res = stats.probplot(x, plot=plt)\n",
+      "    \n",
+      "    A standard normal distribution:\n",
+      "    \n",
+      "    >>> ax4 = plt.subplot(224)\n",
+      "    >>> x = stats.norm.rvs(loc=0, scale=1, size=nsample, random_state=rng)\n",
+      "    >>> res = stats.probplot(x, plot=plt)\n",
+      "    \n",
+      "    Produce a new figure with a loggamma distribution, using the ``dist`` and\n",
+      "    ``sparams`` keywords:\n",
+      "    \n",
+      "    >>> fig = plt.figure()\n",
+      "    >>> ax = fig.add_subplot(111)\n",
+      "    >>> x = stats.loggamma.rvs(c=2.5, size=500, random_state=rng)\n",
+      "    >>> res = stats.probplot(x, dist=stats.loggamma, sparams=(2.5,), plot=ax)\n",
+      "    >>> ax.set_title(\"Probplot for loggamma dist with shape parameter 2.5\")\n",
+      "    \n",
+      "    Show the results with Matplotlib:\n",
+      "    \n",
+      "    >>> plt.show()\n",
+      "\n"
+     ]
     }
    ],
    "source": [
-    "i = np.flatnonzero(theoretical_quantiles>-1)[0]\n",
-    "j = np.flatnonzero(theoretical_quantiles<=1)[-1]\n",
-    "theoretical_quantiles[i:j+1][[0,-1]]"
+    "help(stats.probplot)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
-   "id": "3e95412d-2d79-4c42-81d1-e6dd21499d0c",
-   "metadata": {},
+   "execution_count": 19,
+   "id": "ddf5d4b0",
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [
     {
      "data": {
+      "image/png": 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\n",
       "text/plain": [
-       "array([-0.98673271,  0.98673271])"
+       "<Figure size 432x288 with 1 Axes>"
       ]
      },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
     }
    ],
    "source": [
-    "theoretical_quantiles[central_part][[0,-1]]"
+    "(theoretical_quantiles, observed_quantiles), (slope, intercept, _) = stats.probplot(house_owners_age, fit=True)\n",
+    "# blue crosses\n",
+    "plt.scatter(theoretical_quantiles, observed_quantiles, marker='+', color='b')\n",
+    "# red line\n",
+    "plt.axline((0, intercept), slope=slope, color='r')\n",
+    "# axis labels\n",
+    "plt.xlabel('theoretical quantiles')\n",
+    "plt.ylabel('ordered observations (age)');"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "7981096d",
+   "id": "24b49c4c",
    "metadata": {
     "hidden": true
    },
    "source": [
-    "The misalignment of the default regression line on the central part of the distribution is indicative of some asymmetry, while the diverging tails also hint at some departure from normality (kurtosis). The sampling procedure clearly excluded people younger than 20 years old or elder than 70, which results in truncated distributions.\n",
+    "The red line is fitted to the blue points and does not align well on the linear part.\n",
     "\n",
     "We can seek confirmation with a normality test, although it is already clear the age is not normally distributed in our sample:"
    ]
@@ -1636,7 +1334,7 @@
    "source": [
     "## Q\n",
     "\n",
-    "Test the group mean ages equal."
+    "Test whether the group mean ages equal."
    ]
   },
   {
@@ -1651,7 +1349,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 36,
    "id": "1d238900",
    "metadata": {
     "hidden": true
@@ -1663,7 +1361,7 @@
        "Ttest_indResult(statistic=-10.858676761684935, pvalue=9.562420864768222e-26)"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1676,6 +1374,30 @@
     "stats.ttest_ind(house_owners_age, others_age)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "472c03d6",
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "_, pvalue = stats.ttest_ind(house_owners_age, others_age)\n",
+    "pvalue <= significance_level"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "62b30b76",
@@ -1700,7 +1422,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 47,
    "id": "341157b6",
    "metadata": {
     "hidden": true
@@ -1712,7 +1434,7 @@
        "(814, -10.305953282828284, -0.7954424784394866, -0.7954424784394866)"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 47,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1730,11 +1452,11 @@
     "t, _ = stats.ttest_ind(house_owners_age, others_age)\n",
     "cohen_d = t * np.sqrt(1/n1 + 1/n2)\n",
     "\n",
-    "#   alternatively:\n",
+    "#   alternatively, for the lazy people:\n",
     "import pingouin as pg\n",
-    "unbiased_cohen_d = pg.compute_effsize(house_owners_age, others_age)\n",
+    "cohen_d_again = pg.compute_effsize(house_owners_age, others_age)\n",
     "\n",
-    "degrees_of_freedom, mean_difference, cohen_d, unbiased_cohen_d"
+    "degrees_of_freedom, mean_difference, cohen_d, cohen_d_again"
    ]
   },
   {
@@ -1749,348 +1471,167 @@
     "Note: as we report the sample size for each group, we may omit the (still nice-to-have) information of the number of degrees of freedom."
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "f72698b7",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "## Q\n",
-    "\n",
-    "\\[optional; good for playing with Python rather than statistical methods\\]\n",
-    "\n",
-    "Although tractable in principle, the group difference in variance is quite large and -- had we smaller samples -- we could instead use the Welch's $t$ test that is known to better control for type-1 errors in cases of differing variances, but also a slightly lower power.\n",
-    "\n",
-    "As it is now clear we have a relationship between age and owning a house, let us compute the rejection rate (or power) as a function of sample size.\n",
-    "\n",
-    "Proposal:\n",
-    "* loop over decreasing sample sizes (*e.g.* 200, 50, 20, 10, 5),\n",
-    "* randomly pick a subsample of that size from each group,\n",
-    "* compare their means using the standard Student $t$-test and Welch $t$-test,\n",
-    "* observe whether each test successfully rejects $H_0$ for a constant significance level (*e.g.* 5%),\n",
-    "* replicate this procedure many times (*e.g.* 100)\n",
-    "* and compute the rejection rate for each sample size and type of test."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "6b7d5d56",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "## Help: subsampling"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "ee947953",
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX4AAAEGCAYAAABiq/5QAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8rg+JYAAAACXBIWXMAAAsTAAALEwEAmpwYAAAQ1klEQVR4nO3de6xlZXnH8e8PxqkK6nCZTMe5OGMkWCoVZERuMRbaBlsr1FIusXZisENStVCtivYPQhuTkhgvMa0yAS1tqYKIAYmBUkRTSzN2uBiEkUoRmOE6XpDWJtKRp3/sNXA4czmbM2ftPWe/309ysvdaa++znjdnn99Z59lrvTtVhSSpHfuMuwBJ0mgZ/JLUGINfkhpj8EtSYwx+SWrMgnEXMIyDDz64Vq1aNe4yJGleufXWW39YVYunr58Xwb9q1So2btw47jIkaV5J8sDO1tvqkaTGGPyS1BiDX5IaY/BLUmMMfklqjMEvSY0x+CWpMQa/JDXG4Jekxhj8kuaNZStWkmTkX8tWrBz30OfUvJiyQZIAHt6ymTMuvmXk+73inONGvs8+ecQvSY0x+CWpMQa/JDXG4Jekxhj8ktQYg1+SGmPwS1JjDH5JaozBL0mNMfglqTEGvyQ1xuCXpMYY/JLUGINfkhpj8EtSYwx+SWqMwS9JjTH4JakxvQZ/kj9LcleS7yb5QpIXJlmdZEOSe5NckWRhnzVIkp6rt+BPsgz4U2BNVb0G2Bc4E7gI+ERVvQr4CXB2XzVIknbUd6tnAfCiJAuAFwOPACcCV3XbLwNO7bkGSdIUvQV/VT0EfAx4kEHg/xS4FXiiqrZ1D9sCLNvZ85OsS7IxycatW7f2VaYkNafPVs8BwCnAauDlwH7AycM+v6rWV9WaqlqzePHinqqUpPb02er5DeAHVbW1qv4PuBo4HljUtX4AlgMP9ViDJGmaPoP/QeCYJC9OEuAk4G7gZuC07jFrgWt6rEGSNE2fPf4NDN7EvQ24s9vXeuBDwPuS3AscBFzaVw2SpB0tmPkhs1dVFwAXTFt9H3B0n/uVJO2aV+5KUmMMfklqjMEvSY0x+CWpMQa/JDXG4Jekxhj8ktQYg1+SGmPwS1JjDH5JaozBL0mNMfglqTEGvyQ1xuCXpMYY/JoIy1asJMnIv5atWDnuoUvPW6/z8Uuj8vCWzZxx8S0j3+8V5xw38n1Ke8ojfklqjEf8kp6XZStW8vCWzeMuQ3vA4Jf0vIyrrQa21uaKrR5JaozBL0mNMfglqTEGvyQ1xuCXpMYY/JLUGINfkhrjefyaM17YI80PBr/mjBf2SPODwS/NU/6Hpdky+KV5yhlJNVu+uStJjTH4JakxBr8kNcbgl6TGGPyS1BiDX5IaY/BLUmN6Df4ki5JcleR7STYlOTbJgUluTPL97vaAPmuQJD1X30f8nwKur6pXA68FNgHnAzdV1SHATd2yJGlEegv+JC8D3ghcClBVT1XVE8ApwGXdwy4DTu2rBknSjvo84l8NbAU+n+T2JJck2Q9YUlWPdI95FFiysycnWZdkY5KNW7du7bFMSWpLn8G/AHgd8JmqOhL4GdPaOlVVQO3syVW1vqrWVNWaxYsX91imJLWlz+DfAmypqg3d8lUM/hA8lmQpQHf7eI81SJKm6S34q+pRYHOSQ7tVJwF3A9cCa7t1a4Fr+qpBkrSjvqdlfi9weZKFwH3AOxn8sbkyydnAA8DpPdcgSZqi1+CvqjuANTvZdFKf+5Uk7ZpX7kpSYwx+SWqMwS9JjTH4JakxBr8kNabv0zmlybbPApKMuwrpeTH4pT3x9DbOuPiWsez6inOOG8t+Nf/Z6pGkxnjEL0kzGVNL7+XLV/DQ5gfn/Psa/JI0kzG19Ppq59nqkaTGDBX8SY4fZp0kae837BH/p4dcJ0nay+22x5/kWOA4YHGS903Z9FJg3z4LkyT1Y6Y3dxcC+3ePe8mU9U8Cp/VVlCSpP7sN/qr6JvDNJH9XVQ+MqCZJUo+GPZ3zl5KsB1ZNfU5VndhHUZKk/gwb/F8CPgtcAvyiv3IkSX0bNvi3VdVneq1EkjQSw57O+dUkf5JkaZIDt3/1WpkkqRfDHvGv7W4/MGVdAa+c23IkSX0bKviranXfhUiSRmOo4E/yRztbX1V/P7flSJL6Nmyr5/VT7r8QOAm4DTD4JWmeGbbV896py0kWAV/soyBJUr9mOy3zzwD7/pI0Dw3b4/8qg7N4YDA5268AV/ZVlCSpP8P2+D825f424IGq2tJDPZKkng3V6ukma/segxk6DwCe6rMoSVJ/hv0ErtOBbwN/AJwObEjitMySNA8N2+r5C+D1VfU4QJLFwL8AV/VVmCSpH8Oe1bPP9tDv/Oh5PFeStBcZ9oj/+iQ3AF/ols8AvtZPSZKkPs30mbuvApZU1QeSvA04odv078DlfRcnSZp7Mx3xfxL4MEBVXQ1cDZDk8G7b7/ZYmySpBzP16ZdU1Z3TV3brVvVSkSSpVzMF/6LdbHvRHNYhSRqRmYJ/Y5I/nr4yybuAW4fZQZJ9k9ye5LpueXWSDUnuTXJFkoXPv2xJ0mzN1OM/D/hKkrfzbNCvARYCvzfkPs4FNgEv7ZYvAj5RVV9M8lngbMDP85WkEdntEX9VPVZVxwEXAvd3XxdW1bFV9ehM3zzJcuB3gEu65QAn8uyFX5cBp86ydknSLAw7H//NwM2z+P6fBD7IYI4fgIOAJ6pqW7e8BVi2sycmWQesA1i5cuUsdi1J2pnerr5N8hbg8aoa6r2A6apqfVWtqao1ixcvnuPqJKldw165OxvHA29N8tsMPq7xpcCngEVJFnRH/cuBh3qsQZI0TW9H/FX14apaXlWrgDOBr1fV2xm0jLbP7LkWuKavGiRJOxrHRGsfAt6X5F4GPf9Lx1CDJDWrz1bPM6rqG8A3uvv3AUePYr+SpB05tbIkNcbgl6TGGPyS1JiR9Pg1WstWrOThLZvHXYakvZTBP4Ee3rKZMy6+ZeT7veKc40a+T0nPn8Evaf7YZ8F4DjD2mayonKzRSJpsT2/j8AuuH/lu77zw5JHvs0++uStJjTH4JakxBr8kNcbgl6TGGPyS1BiDX5IaY/BLUmMMfklqjMEvSY0x+CWpMQa/JDXG4Jekxhj8ktQYg1+SGmPwS1JjDH5JaozBL0mN8RO4NHfG9bF43b4lDcffFs2dMX0sHkzeR+NJfTL4NRn8EO7RGed/dpoTDb5qNZH8EO7R8T+7ec83dyWpMQa/JDXG4Jekxhj8ktQYg1+SGuNZPdKe8KI1zUO+cqQ94amNmocMfkmayYRdIGjwS9JMJuwCwd7e3E2yIsnNSe5OcleSc7v1Bya5Mcn3u9sD+qpBkrSjPs/q2Qa8v6oOA44B3p3kMOB84KaqOgS4qVuWJI1Ib8FfVY9U1W3d/f8GNgHLgFOAy7qHXQac2lcNkqQdjaTHn2QVcCSwAVhSVY90mx4FluziOeuAdQArV64cQZUTxNkTJe1G78GfZH/gy8B5VfVkkme2VVUlqZ09r6rWA+sB1qxZs9PHaBcm7I0oSXOr1yt3k7yAQehfXlVXd6sfS7K0274UeLzPGiRJz9XnWT0BLgU2VdXHp2y6Fljb3V8LXNNXDZKkHfXZ6jkeeAdwZ5I7unUfAf4auDLJ2cADwOk91iBJmqa34K+qbwHZxeaT+tqvJGn3nJ1Tkhpj8EtSYwx+SWqMwS9JjTH4JakxTssszVdOzaFZMvil+cqpOTRLtnokqTEGvyQ1xuCXpMbY4+/JshUreXjL5nGXIUk7MPh78vCWzZxx8S1j2bdnekjaHVs9ktQYg1+SGmPwS1JjDH5JaozBL0mNMfglqTEGvyQ1xuCXpMYY/JLUmIm/ctepEyTpuSY++Mc1dYLTJkjaW9nqkaTGGPyS1BiDX5IaY/BLUmMMfklqjMEvSY0x+CWpMQa/JDXG4Jekxhj8ktSYiZ+ygX0WjGf6hHHtV5JmMPnB//Q2Dr/g+pHv9s4LTx7LfrfvW5J2xVaPJDXG4Jekxowl+JOcnOSeJPcmOX8cNUhSq0Ye/En2Bf4GeDNwGHBWksNGXYcktWocR/xHA/dW1X1V9RTwReCUMdQhSU1KVY12h8lpwMlV9a5u+R3AG6rqPdMetw5Y1y0eCtwzy10eDPxwls+drxxzGxzz5NvT8b6iqhZPX7nXns5ZVeuB9Xv6fZJsrKo1c1DSvOGY2+CYJ19f4x1Hq+chYMWU5eXdOknSCIwj+P8DOCTJ6iQLgTOBa8dQhyQ1aeStnqraluQ9wA3AvsDnququHne5x+2iecgxt8ExT75exjvyN3clSePllbuS1BiDX5IaMzHBn2RFkpuT3J3kriTndusPTHJjku93tweMu9a5kuSFSb6d5DvdmC/s1q9OsqGbEuOK7k30iZJk3yS3J7muW57oMSe5P8mdSe5IsrFbN7GvbYAki5JcleR7STYlOXaSx5zk0O7nu/3rySTn9THmiQl+YBvw/qo6DDgGeHc3FcT5wE1VdQhwU7c8KX4OnFhVrwWOAE5OcgxwEfCJqnoV8BPg7PGV2JtzgU1TllsY869X1RFTzuue5Nc2wKeA66vq1cBrGfy8J3bMVXVP9/M9AjgK+F/gK/Qx5qqayC/gGuA3GVzxu7RbtxS4Z9y19TTeFwO3AW9gcKXfgm79scAN465vjse6vPsFOBG4DkgDY74fOHjauol9bQMvA35AdwJKC2OeNs7fAv6trzFP0hH/M5KsAo4ENgBLquqRbtOjwJJx1dWHruVxB/A4cCPwX8ATVbWte8gWYNmYyuvLJ4EPAk93ywcx+WMu4J+T3NpNZwKT/dpeDWwFPt+19C5Jsh+TPeapzgS+0N2f8zFPXPAn2R/4MnBeVT05dVsN/mRO1PmrVfWLGvxruJzBBHivHm9F/UryFuDxqrp13LWM2AlV9ToGs9q+O8kbp26cwNf2AuB1wGeq6kjgZ0xrcUzgmAHo3p96K/Cl6dvmaswTFfxJXsAg9C+vqqu71Y8lWdptX8rgyHjiVNUTwM0M2hyLkmy/OG/SpsQ4HnhrkvsZzOx6IoNe8CSPmap6qLt9nEHf92gm+7W9BdhSVRu65asY/CGY5DFv92bgtqp6rFue8zFPTPAnCXApsKmqPj5l07XA2u7+Wga9/4mQZHGSRd39FzF4T2MTgz8Ap3UPm6gxV9WHq2p5Va1i8O/w16vq7UzwmJPsl+Ql2+8z6P9+lwl+bVfVo8DmJId2q04C7maCxzzFWTzb5oEexjwxV+4mOQH4V+BOnu39foRBn/9KYCXwAHB6Vf14LEXOsSS/BlzGYOqLfYArq+ovk7ySwdHwgcDtwB9W1c/HV2k/krwJ+POqesskj7kb21e6xQXAP1XVR5McxIS+tgGSHAFcAiwE7gPeSfc6Z3LHvB/wIPDKqvppt27Of84TE/ySpOFMTKtHkjQcg1+SGmPwS1JjDH5JaozBL0mNMfilGSQ5NUklmeirotUOg1+a2VnAt7pbad4z+KXd6OZ+OoHBNM9nduv2SfK33TzxNyb5WpLTum1HJflmN5naDdsvtZf2Jga/tHunMJgT/j+BHyU5CngbsAo4DHgHg/mRts8V9WngtKo6Cvgc8NFxFC3tzoKZHyI17SwGk8DBYEqIsxj83nypqp4GHk1yc7f9UOA1wI2DqaPYF3gEaS9j8Eu7kORABrN/Hp6kGAR58ey8OTs8Bbirqo4dUYnSrNjqkXbtNOAfquoVVbWqqlYw+FSoHwO/3/X6lwBv6h5/D7A4yTOtnyS/Oo7Cpd0x+KVdO4sdj+6/DPwyg/ni7wb+kcFHXv60qp5i8MfioiTfAe4AjhtZtdKQnJ1TmoUk+1fV/3RT5n4bOL6bQ17a69njl2bnuu5DcBYCf2Xoaz7xiF+SGmOPX5IaY/BLUmMMfklqjMEvSY0x+CWpMf8P/S1i2GC7UfwAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# let us consider an example sample\n",
-    "sample = others_age\n",
-    "\n",
-    "# and a subsample size\n",
-    "n = 200\n",
-    "\n",
-    "# we need a random generator\n",
-    "rng = np.random.default_rng()\n",
-    "\n",
-    "# now we can pick n observations from the original sample\n",
-    "# calling the `choice` method of the random generator\n",
-    "subsample = rng.choice(sample, n)\n",
-    "\n",
-    "# in principle the smaller sample will exhibit similar\n",
-    "# properties as the original sample; both are drawn from\n",
-    "# the population in similar ways\n",
-    "bins = np.arange(20, 70+1, 5)\n",
-    "sns.histplot(sample, bins=bins)\n",
-    "sns.histplot(subsample, bins=bins);"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "b44a7b2b",
-   "metadata": {
-    "heading_collapsed": true
-   },
-   "source": [
-    "## A"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 36,
-   "id": "81e31c08",
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [],
-   "source": [
-    "significance_level = 0.05\n",
-    "\n",
-    "sample1 = house_owners_age\n",
-    "sample2 = others_age\n",
-    "sample_size = min(len(sample1), len(sample2))"
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 37,
-   "id": "2ae175e5",
+   "execution_count": 48,
+   "id": "c45d530a",
    "metadata": {
     "hidden": true
    },
-   "outputs": [],
-   "source": [
-    "from collections import defaultdict\n",
-    "\n",
-    "sample_sizes = []\n",
-    "test_types = []\n",
-    "rejection_rates = []\n",
-    "\n",
-    "rng = np.random.default_rng()\n",
-    "\n",
-    "for relative_sample_size in (1, .2, .1, .05, .025):\n",
-    "    n = int(relative_sample_size * sample_size)\n",
-    "    nreplicates = 100\n",
-    "    rejections = defaultdict(lambda: 0)\n",
-    "    for _ in range(nreplicates):\n",
-    "        subsample1 = rng.choice(sample1, n)\n",
-    "        subsample2 = rng.choice(sample2, n)\n",
-    "        for test_type in ('Student', 'Welch'):\n",
-    "            t, pv = stats.ttest_ind(subsample1, subsample2, equal_var=test_type=='Student')\n",
-    "            if pv <= significance_level:\n",
-    "                rejections[test_type] = rejections[test_type] + 1\n",
-    "    for test_type in rejections:\n",
-    "        rejection_rates.append(rejections[test_type] / nreplicates)\n",
-    "        sample_sizes.append(n)\n",
-    "        test_types.append(test_type)\n",
-    "            \n",
-    "result = pd.DataFrame({'sample size': sample_sizes, 'test': test_types, 'power': rejection_rates})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "id": "37b3e673-be8b-4f6d-92ca-ee13c5a7eca7",
-   "metadata": {},
    "outputs": [
     {
-     "data": {
-      "text/plain": [
-       "1"
-      ]
-     },
-     "execution_count": 34,
-     "metadata": {},
-     "output_type": "execute_result"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on function compute_effsize in module pingouin.effsize:\n",
+      "\n",
+      "compute_effsize(x, y, paired=False, eftype='cohen')\n",
+      "    Calculate effect size between two set of observations.\n",
+      "    \n",
+      "    Parameters\n",
+      "    ----------\n",
+      "    x : np.array or list\n",
+      "        First set of observations.\n",
+      "    y : np.array or list\n",
+      "        Second set of observations.\n",
+      "    paired : boolean\n",
+      "        If True, uses Cohen d-avg formula to correct for repeated measurements\n",
+      "        (see Notes).\n",
+      "    eftype : string\n",
+      "        Desired output effect size.\n",
+      "        Available methods are:\n",
+      "    \n",
+      "        * ``'none'``: no effect size\n",
+      "        * ``'cohen'``: Unbiased Cohen d\n",
+      "        * ``'hedges'``: Hedges g\n",
+      "        * ``'r'``: correlation coefficient\n",
+      "        * ``'eta-square'``: Eta-square\n",
+      "        * ``'odds-ratio'``: Odds ratio\n",
+      "        * ``'AUC'``: Area Under the Curve\n",
+      "        * ``'CLES'``: Common Language Effect Size\n",
+      "    \n",
+      "    Returns\n",
+      "    -------\n",
+      "    ef : float\n",
+      "        Effect size\n",
+      "    \n",
+      "    See Also\n",
+      "    --------\n",
+      "    convert_effsize : Conversion between effect sizes.\n",
+      "    compute_effsize_from_t : Convert a T-statistic to an effect size.\n",
+      "    \n",
+      "    Notes\n",
+      "    -----\n",
+      "    Missing values are automatically removed from the data. If ``x`` and ``y``\n",
+      "    are paired, the entire row is removed.\n",
+      "    \n",
+      "    If ``x`` and ``y`` are independent, the Cohen :math:`d` is:\n",
+      "    \n",
+      "    .. math::\n",
+      "    \n",
+      "        d = \\frac{\\overline{X} - \\overline{Y}}\n",
+      "        {\\sqrt{\\frac{(n_{1} - 1)\\sigma_{1}^{2} + (n_{2} - 1)\n",
+      "        \\sigma_{2}^{2}}{n1 + n2 - 2}}}\n",
+      "    \n",
+      "    If ``x`` and ``y`` are paired, the Cohen :math:`d_{avg}` is computed:\n",
+      "    \n",
+      "    .. math::\n",
+      "    \n",
+      "        d_{avg} = \\frac{\\overline{X} - \\overline{Y}}\n",
+      "        {\\sqrt{\\frac{(\\sigma_1^2 + \\sigma_2^2)}{2}}}\n",
+      "    \n",
+      "    The Cohen’s d is a biased estimate of the population effect size,\n",
+      "    especially for small samples (n < 20). It is often preferable\n",
+      "    to use the corrected Hedges :math:`g` instead:\n",
+      "    \n",
+      "    .. math:: g = d \\times (1 - \\frac{3}{4(n_1 + n_2) - 9})\n",
+      "    \n",
+      "    The common language effect size is the proportion of pairs where ``x`` is\n",
+      "    higher than ``y`` (calculated with a brute-force approach where\n",
+      "    each observation of ``x`` is paired to each observation of ``y``,\n",
+      "    see :py:func:`pingouin.wilcoxon` for more details):\n",
+      "    \n",
+      "    .. math:: \\text{CL} = P(X > Y) + .5 \\times P(X = Y)\n",
+      "    \n",
+      "    For other effect sizes, Pingouin will first calculate a Cohen :math:`d` and\n",
+      "    then use the :py:func:`pingouin.convert_effsize` to convert to the desired\n",
+      "    effect size.\n",
+      "    \n",
+      "    References\n",
+      "    ----------\n",
+      "    * Lakens, D., 2013. Calculating and reporting effect sizes to\n",
+      "      facilitate cumulative science: a practical primer for t-tests and\n",
+      "      ANOVAs. Front. Psychol. 4, 863. https://doi.org/10.3389/fpsyg.2013.00863\n",
+      "    \n",
+      "    * Cumming, Geoff. Understanding the new statistics: Effect sizes,\n",
+      "      confidence intervals, and meta-analysis. Routledge, 2013.\n",
+      "    \n",
+      "    * https://osf.io/vbdah/\n",
+      "    \n",
+      "    Examples\n",
+      "    --------\n",
+      "    1. Cohen d from two independent samples.\n",
+      "    \n",
+      "    >>> import numpy as np\n",
+      "    >>> import pingouin as pg\n",
+      "    >>> x = [1, 2, 3, 4]\n",
+      "    >>> y = [3, 4, 5, 6, 7]\n",
+      "    >>> pg.compute_effsize(x, y, paired=False, eftype='cohen')\n",
+      "    -1.707825127659933\n",
+      "    \n",
+      "    The sign of the Cohen d will be opposite if we reverse the order of\n",
+      "    ``x`` and ``y``:\n",
+      "    \n",
+      "    >>> pg.compute_effsize(y, x, paired=False, eftype='cohen')\n",
+      "    1.707825127659933\n",
+      "    \n",
+      "    2. Hedges g from two paired samples.\n",
+      "    \n",
+      "    >>> x = [1, 2, 3, 4, 5, 6, 7]\n",
+      "    >>> y = [1, 3, 5, 7, 9, 11, 13]\n",
+      "    >>> pg.compute_effsize(x, y, paired=True, eftype='hedges')\n",
+      "    -0.8222477210374874\n",
+      "    \n",
+      "    3. Common Language Effect Size.\n",
+      "    \n",
+      "    >>> pg.compute_effsize(x, y, eftype='cles')\n",
+      "    0.2857142857142857\n",
+      "    \n",
+      "    In other words, there are ~29% of pairs where ``x`` is higher than ``y``,\n",
+      "    which means that there are ~71% of pairs where ``x`` is *lower* than ``y``.\n",
+      "    This can be easily verified by changing the order of ``x`` and ``y``:\n",
+      "    \n",
+      "    >>> pg.compute_effsize(y, x, eftype='cles')\n",
+      "    0.7142857142857143\n",
+      "\n"
+     ]
     }
    ],
    "source": [
-    "from collections import defaultdict\n",
-    "a = defaultdict(lambda: 0)\n",
-    "a['Student'] += 1\n",
-    "a['Student']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 39,
-   "id": "420b4aea-7d0f-4bb5-8e33-ddac0af11981",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "sample_sizes = []\n",
-    "test_types = []\n",
-    "rejection_rates = []\n",
-    "\n",
-    "rng = np.random.default_rng()\n",
-    "\n",
-    "for relative_sample_size in (1, .2, .1, .05, .025):\n",
-    "    n = int(relative_sample_size * sample_size)\n",
-    "    nreplicates = 100\n",
-    "    nStudent = nWelch = 0\n",
-    "    for _ in range(nreplicates):\n",
-    "        subsample1 = rng.choice(sample1, n)\n",
-    "        subsample2 = rng.choice(sample2, n)\n",
-    "        \n",
-    "        t, pv = stats.ttest_ind(subsample1, subsample2, equal_var=True)\n",
-    "        if pv<=significance_level:\n",
-    "            nStudent += 1\n",
-    "        \n",
-    "        t, pv = stats.ttest_ind(subsample1, subsample2, equal_var=False)\n",
-    "        if pv<=significance_level:\n",
-    "            nWelch += 1\n",
-    "            \n",
-    "    rejection_rates += [nStudent / nreplicates, nWelch / nreplicates]\n",
-    "    sample_sizes += [n, n]\n",
-    "    test_types += ['Student', 'Welch']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 40,
-   "id": "dc4fc10a-efa4-46c3-8c86-410f46b290c6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "\n",
-    "result = pd.DataFrame({'sample size': sample_sizes, 'test': test_types, 'power': rejection_rates})"
+    "help(pg.compute_effsize)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
-   "id": "d15c23da",
+   "execution_count": 49,
+   "id": "3b123c41",
    "metadata": {
     "hidden": true
    },
    "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>sample size</th>\n",
-       "      <th>test</th>\n",
-       "      <th>power</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>288</td>\n",
-       "      <td>Student</td>\n",
-       "      <td>1.00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>288</td>\n",
-       "      <td>Welch</td>\n",
-       "      <td>1.00</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>57</td>\n",
-       "      <td>Student</td>\n",
-       "      <td>0.97</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>57</td>\n",
-       "      <td>Welch</td>\n",
-       "      <td>0.97</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>28</td>\n",
-       "      <td>Student</td>\n",
-       "      <td>0.75</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>5</th>\n",
-       "      <td>28</td>\n",
-       "      <td>Welch</td>\n",
-       "      <td>0.75</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>6</th>\n",
-       "      <td>14</td>\n",
-       "      <td>Student</td>\n",
-       "      <td>0.46</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>7</th>\n",
-       "      <td>14</td>\n",
-       "      <td>Welch</td>\n",
-       "      <td>0.46</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>8</th>\n",
-       "      <td>7</td>\n",
-       "      <td>Student</td>\n",
-       "      <td>0.18</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>9</th>\n",
-       "      <td>7</td>\n",
-       "      <td>Welch</td>\n",
-       "      <td>0.16</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
       "text/plain": [
-       "   sample size     test  power\n",
-       "0          288  Student   1.00\n",
-       "1          288    Welch   1.00\n",
-       "2           57  Student   0.97\n",
-       "3           57    Welch   0.97\n",
-       "4           28  Student   0.75\n",
-       "5           28    Welch   0.75\n",
-       "6           14  Student   0.46\n",
-       "7           14    Welch   0.46\n",
-       "8            7  Student   0.18\n",
-       "9            7    Welch   0.16"
+       "-0.7947093517312473"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "pd.options.display.max_rows = 20\n",
-    "result"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c4c702bc",
-   "metadata": {
-    "hidden": true
-   },
-   "source": [
-    "Both tests give similar results and quickly loose quite a lot of power as the sample size decreases.\n",
-    "$0.8$ is often considered as a reasonnable (some would say «minimal») power for a(ny) test.\n",
-    "\n",
-    "Here, the quick decrease in power is likely to be intensified by the asymmetries in opposite directions, known to be deleterous for the $t$-tests."
+    "pg.compute_effsize(house_owners_age, others_age, eftype='hedges')"
    ]
   },
   {
@@ -2112,26 +1653,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 59,
    "id": "0aeaeee7",
    "metadata": {},
    "outputs": [
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "sns.boxplot(x='LivesWithKids', y='Age', data=df)\n",
-    "sns.swarmplot(x='LivesWithKids', y='Age', data=df, linewidth=1, size=3);"
+    "sns.swarmplot(x='LivesWithKids', y='Age', hue='LivesWithKids', data=df, linewidth=1, size=3, legend=False);"
    ]
   },
   {
@@ -2158,7 +1697,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 58,
    "id": "e9c1cc3c",
    "metadata": {
     "hidden": true
@@ -2170,7 +1709,7 @@
        "(47.758187772925766, 44.85779329608938, 16.298908849529322, 9.611832029475966)"
       ]
      },
-     "execution_count": 45,
+     "execution_count": 58,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2375,36 +1914,15 @@
     "print(f'χ²({dof}) = {chi2:.1f}, p-value = {pvalue:.3g}')"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "id": "fbdbb32d-6595-40dd-88e4-8f6bb2947e71",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array([[ 2, 12, 44, 67, 65, 53, 57, 34, 16,  8],\n",
-       "       [75, 32, 26, 23, 22, 30, 39, 56, 94, 61]])"
-      ]
-     },
-     "execution_count": 51,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "np.stack((lives_with_kids_freqs, lives_without_kids_freqs), axis=0)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "218a59ec",
    "metadata": {
-    "heading_collapsed": true
+    "heading_collapsed": true,
+    "hidden": true
    },
    "source": [
-    "## Q\n",
+    "### Q\n",
     "\n",
     "Are all the assumptions met? Adjust the procedure if necessary. Any interpretation?"
    ]
@@ -2413,10 +1931,11 @@
    "cell_type": "markdown",
    "id": "abdce59a",
    "metadata": {
-    "heading_collapsed": true
+    "heading_collapsed": true,
+    "hidden": true
    },
    "source": [
-    "## A"
+    "### A"
    ]
   },
   {
@@ -2524,9 +2043,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "scientific_python",
    "language": "python",
-   "name": "python3"
+   "name": "scientific_python"
   },
   "language_info": {
    "codemirror_mode": {
@@ -2538,7 +2057,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.4"
   },
   "toc": {
    "base_numbering": 1,
diff --git a/notebooks/statsmodels_cours.ipynb b/notebooks/statsmodels_cours.ipynb
index 67ba987..1e7c29e 100644
--- a/notebooks/statsmodels_cours.ipynb
+++ b/notebooks/statsmodels_cours.ipynb
@@ -5539,7 +5539,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.4"
   },
   "toc": {
    "base_numbering": 1,
-- 
GitLab