From dcd3819cfcf3b2fcf72363a1006e7675f954a54c Mon Sep 17 00:00:00 2001
From: 3eb2734abf9c03158722854f9624a07d
 <3eb2734abf9c03158722854f9624a07d@app-learninglab.inria.fr>
Date: Wed, 7 Dec 2022 16:03:11 +0000
Subject: [PATCH] done

---
 module2/exo5/exo5_fr.ipynb | 815 +++++++++++++++++++++++++++++++------
 1 file changed, 692 insertions(+), 123 deletions(-)

diff --git a/module2/exo5/exo5_fr.ipynb b/module2/exo5/exo5_fr.ipynb
index 26ad6d9..44fc98a 100644
--- a/module2/exo5/exo5_fr.ipynb
+++ b/module2/exo5/exo5_fr.ipynb
@@ -1,5 +1,18 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "pd.set_option('mode.chained_assignment',None) # this removes a useless warning from pandas"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -40,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -261,40 +274,38 @@
        "</div>"
       ],
       "text/plain": [
-       "         Date  Count  Temperature  Pressure  Malfunction\n",
-       "0     4/12/81      6           66        50            0\n",
-       "1    11/12/81      6           70        50            1\n",
-       "2     3/22/82      6           69        50            0\n",
-       "3    11/11/82      6           68        50            0\n",
-       "4     4/04/83      6           67        50            0\n",
-       "5     6/18/82      6           72        50            0\n",
-       "6     8/30/83      6           73       100            0\n",
-       "7    11/28/83      6           70       100            0\n",
-       "8     2/03/84      6           57       200            1\n",
-       "9     4/06/84      6           63       200            1\n",
-       "10    8/30/84      6           70       200            1\n",
-       "11   10/05/84      6           78       200            0\n",
-       "12   11/08/84      6           67       200            0\n",
-       "13    1/24/85      6           53       200            2\n",
-       "14    4/12/85      6           67       200            0\n",
-       "15    4/29/85      6           75       200            0\n",
-       "16    6/17/85      6           70       200            0\n",
-       "17  7/29/85      6           81       200            0\n",
-       "18    8/27/85      6           76       200            0\n",
-       "19   10/03/85      6           79       200            0\n",
-       "20   10/30/85      6           75       200            2\n",
-       "21   11/26/85      6           76       200            0\n",
-       "22    1/12/86      6           58       200            1"
+       "        Date  Count  Temperature  Pressure  Malfunction\n",
+       "0    4/12/81      6           66        50            0\n",
+       "1   11/12/81      6           70        50            1\n",
+       "2    3/22/82      6           69        50            0\n",
+       "3   11/11/82      6           68        50            0\n",
+       "4    4/04/83      6           67        50            0\n",
+       "5    6/18/82      6           72        50            0\n",
+       "6    8/30/83      6           73       100            0\n",
+       "7   11/28/83      6           70       100            0\n",
+       "8    2/03/84      6           57       200            1\n",
+       "9    4/06/84      6           63       200            1\n",
+       "10   8/30/84      6           70       200            1\n",
+       "11  10/05/84      6           78       200            0\n",
+       "12  11/08/84      6           67       200            0\n",
+       "13   1/24/85      6           53       200            2\n",
+       "14   4/12/85      6           67       200            0\n",
+       "15   4/29/85      6           75       200            0\n",
+       "16   6/17/85      6           70       200            0\n",
+       "17   7/29/85      6           81       200            0\n",
+       "18   8/27/85      6           76       200            0\n",
+       "19  10/03/85      6           79       200            0\n",
+       "20  10/30/85      6           75       200            2\n",
+       "21  11/26/85      6           76       200            0\n",
+       "22   1/12/86      6           58       200            1"
       ]
      },
-     "execution_count": 1,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "import numpy as np\n",
-    "import pandas as pd\n",
     "data = pd.read_csv(\"shuttle.csv\")\n",
     "data"
    ]
@@ -314,15 +325,17 @@
    "metadata": {},
    "source": [
     "## Inspection graphique des données\n",
-    "Les vols où aucun incident n'est relevé n'apportant aucun information\n",
+    "~~Les vols où aucun incident n'est relevé n'apportant aucun information\n",
     "sur l'influence de la température ou de la pression sur les\n",
     "dysfonctionnements, nous nous concentrons sur les expériences où au\n",
-    "moins un joint a été défectueux.\n"
+    "moins un joint a été défectueux.~~\n",
+    "\n",
+    "**Faux ! Le fait qu'aucun incident soit arrivé est au contraire une information très importante.**"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -351,16 +364,81 @@
        "      <th>Temperature</th>\n",
        "      <th>Pressure</th>\n",
        "      <th>Malfunction</th>\n",
+       "      <th>MalfunctionHappen</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>4/12/81</td>\n",
+       "      <td>6</td>\n",
+       "      <td>66</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>11/12/81</td>\n",
        "      <td>6</td>\n",
        "      <td>70</td>\n",
        "      <td>50</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3/22/82</td>\n",
+       "      <td>6</td>\n",
+       "      <td>69</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>11/11/82</td>\n",
+       "      <td>6</td>\n",
+       "      <td>68</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4/04/83</td>\n",
+       "      <td>6</td>\n",
+       "      <td>67</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>6/18/82</td>\n",
+       "      <td>6</td>\n",
+       "      <td>72</td>\n",
+       "      <td>50</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>8/30/83</td>\n",
+       "      <td>6</td>\n",
+       "      <td>73</td>\n",
+       "      <td>100</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>11/28/83</td>\n",
+       "      <td>6</td>\n",
+       "      <td>70</td>\n",
+       "      <td>100</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>8</th>\n",
@@ -369,6 +447,7 @@
        "      <td>57</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
@@ -377,6 +456,7 @@
        "      <td>63</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
@@ -385,6 +465,25 @@
        "      <td>70</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>10/05/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>78</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>11/08/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>67</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>13</th>\n",
@@ -393,6 +492,61 @@
        "      <td>53</td>\n",
        "      <td>200</td>\n",
        "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>4/12/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>67</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>4/29/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>75</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>6/17/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>70</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>7/29/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>81</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>8/27/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>76</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>10/03/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>79</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>20</th>\n",
@@ -401,6 +555,16 @@
        "      <td>75</td>\n",
        "      <td>200</td>\n",
        "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>21</th>\n",
+       "      <td>11/26/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>76</td>\n",
+       "      <td>200</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>22</th>\n",
@@ -409,93 +573,48 @@
        "      <td>58</td>\n",
        "      <td>200</td>\n",
        "      <td>1</td>\n",
+       "      <td>1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "        Date  Count  Temperature  Pressure  Malfunction\n",
-       "1   11/12/81      6           70        50            1\n",
-       "8    2/03/84      6           57       200            1\n",
-       "9    4/06/84      6           63       200            1\n",
-       "10   8/30/84      6           70       200            1\n",
-       "13   1/24/85      6           53       200            2\n",
-       "20  10/30/85      6           75       200            2\n",
-       "22   1/12/86      6           58       200            1"
+       "        Date  Count  Temperature  Pressure  Malfunction  MalfunctionHappen\n",
+       "0    4/12/81      6           66        50            0                  0\n",
+       "1   11/12/81      6           70        50            1                  1\n",
+       "2    3/22/82      6           69        50            0                  0\n",
+       "3   11/11/82      6           68        50            0                  0\n",
+       "4    4/04/83      6           67        50            0                  0\n",
+       "5    6/18/82      6           72        50            0                  0\n",
+       "6    8/30/83      6           73       100            0                  0\n",
+       "7   11/28/83      6           70       100            0                  0\n",
+       "8    2/03/84      6           57       200            1                  1\n",
+       "9    4/06/84      6           63       200            1                  1\n",
+       "10   8/30/84      6           70       200            1                  1\n",
+       "11  10/05/84      6           78       200            0                  0\n",
+       "12  11/08/84      6           67       200            0                  0\n",
+       "13   1/24/85      6           53       200            2                  1\n",
+       "14   4/12/85      6           67       200            0                  0\n",
+       "15   4/29/85      6           75       200            0                  0\n",
+       "16   6/17/85      6           70       200            0                  0\n",
+       "17   7/29/85      6           81       200            0                  0\n",
+       "18   8/27/85      6           76       200            0                  0\n",
+       "19  10/03/85      6           79       200            0                  0\n",
+       "20  10/30/85      6           75       200            2                  1\n",
+       "21  11/26/85      6           76       200            0                  0\n",
+       "22   1/12/86      6           58       200            1                  1"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "data = data[data.Malfunction>0]\n",
-    "data"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Très bien, nous avons une variabilité de température importante mais\n",
-    "la pression est quasiment toujours égale à 200, ce qui devrait\n",
-    "simplifier l'analyse.\n",
-    "\n",
-    "Comment la fréquence d'échecs varie-t-elle avec la température ?\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "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": [
-    "%matplotlib inline\n",
-    "pd.set_option('mode.chained_assignment',None) # this removes a useless warning from pandas\n",
-    "import matplotlib.pyplot as plt\n",
-    "\n",
-    "data[\"Frequency\"]=data.Malfunction/data.Count\n",
-    "data.plot(x=\"Temperature\",y=\"Frequency\",kind=\"scatter\",ylim=[0,1])\n",
-    "plt.grid(True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "À première vue, ce n'est pas flagrant mais bon, essayons quand même\n",
-    "d'estimer l'impact de la température $t$ sur la probabilité de\n",
-    "dysfonctionnements d'un joint. \n"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Estimation de l'influence de la température\n",
-    "\n",
-    "Supposons que chacun des 6 joints toriques est endommagé avec la même\n",
-    "probabilité et indépendamment des autres et que cette probabilité ne\n",
-    "dépend que de la température. Si on note $p(t)$ cette probabilité, le\n",
-    "nombre de joints $D$ dysfonctionnant lorsque l'on effectue le vol à\n",
-    "température $t$ suit une loi binomiale de paramètre $n=6$ et\n",
-    "$p=p(t)$. Pour relier $p(t)$ à $t$, on va donc effectuer une\n",
-    "régression logistique."
+    "real_data = data\n",
+    "real_data[\"MalfunctionHappen\"] = real_data['Malfunction'].apply(lambda x: 1 if x > 0 else 0)\n",
+    "real_data"
    ]
   },
   {
@@ -506,15 +625,289 @@
     {
      "data": {
       "text/html": [
-       "<table class=\"simpletable\">\n",
-       "<caption>Generalized Linear Model Regression Results</caption>\n",
-       "<tr>\n",
-       "  <th>Dep. Variable:</th>      <td>Frequency</td>    <th>  No. Observations:  </th>  <td>     7</td>  \n",
-       "</tr>\n",
-       "<tr>\n",
-       "  <th>Model:</th>                 <td>GLM</td>       <th>  Df Residuals:      </th>  <td>     5</td>  \n",
-       "</tr>\n",
-       "<tr>\n",
+       "<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>Date</th>\n",
+       "      <th>Count</th>\n",
+       "      <th>Temperature</th>\n",
+       "      <th>Pressure</th>\n",
+       "      <th>Malfunction</th>\n",
+       "      <th>MalfunctionHappen</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>11/12/81</td>\n",
+       "      <td>6</td>\n",
+       "      <td>70</td>\n",
+       "      <td>50</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>2/03/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>57</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>4/06/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>63</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>8/30/84</td>\n",
+       "      <td>6</td>\n",
+       "      <td>70</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>1/24/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>53</td>\n",
+       "      <td>200</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>20</th>\n",
+       "      <td>10/30/85</td>\n",
+       "      <td>6</td>\n",
+       "      <td>75</td>\n",
+       "      <td>200</td>\n",
+       "      <td>2</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>22</th>\n",
+       "      <td>1/12/86</td>\n",
+       "      <td>6</td>\n",
+       "      <td>58</td>\n",
+       "      <td>200</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "        Date  Count  Temperature  Pressure  Malfunction  MalfunctionHappen\n",
+       "1   11/12/81      6           70        50            1                  1\n",
+       "8    2/03/84      6           57       200            1                  1\n",
+       "9    4/06/84      6           63       200            1                  1\n",
+       "10   8/30/84      6           70       200            1                  1\n",
+       "13   1/24/85      6           53       200            2                  1\n",
+       "20  10/30/85      6           75       200            2                  1\n",
+       "22   1/12/86      6           58       200            1                  1"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data = data[data.Malfunction>0]\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "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": [
+    "plt.hist(real_data['Pressure'])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Pourcentage des essais ayant une pressions différente a 200 psi:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "35"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "round(len(real_data[real_data.Pressure != 200]) * 100 / len(real_data))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "~~Très bien, nous avons une variabilité de température importante mais\n",
+    "la pression est quasiment toujours égale à 200, ce qui devrait\n",
+    "simplifier l'analyse.~~\n",
+    "\n",
+    "**Avec l'ensemble des données 35% des essais ont une pression différente de 200 psi. Se serai un erreur de négliger l'analyse de son impact.**\n",
+    "\n",
+    "Comment la fréquence d'échecs varie-t-elle avec la température ?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "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": [
+    "%matplotlib inline\n",
+    "\n",
+    "\n",
+    "data[\"Frequency\"]=data.Malfunction/data.Count\n",
+    "data.plot(x=\"Temperature\",y=\"Frequency\",kind=\"scatter\",ylim=[0,1])\n",
+    "plt.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "À première vue, ce n'est pas flagrant mais bon, essayons quand même\n",
+    "d'estimer l'impact de la température $t$ sur la probabilité de\n",
+    "dysfonctionnements d'un joint. \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Voici le vrai plot avec toute les données :**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "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": [
+    "real_data.plot(x=\"Temperature\", y=\"Malfunction\", kind=\"scatter\")\n",
+    "plt.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Là on peut deviner un impact de la température malgré un outlier à 2 Malfunction pour 75°F**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Estimation de l'influence de la température\n",
+    "\n",
+    "Supposons que chacun des 6 joints toriques est endommagé avec la même\n",
+    "probabilité et indépendamment des autres et que cette probabilité ne\n",
+    "dépend que de la température. Si on note $p(t)$ cette probabilité, le\n",
+    "nombre de joints $D$ dysfonctionnant lorsque l'on effectue le vol à\n",
+    "température $t$ suit une loi binomiale de paramètre $n=6$ et\n",
+    "$p=p(t)$. Pour relier $p(t)$ à $t$, on va donc effectuer une\n",
+    "régression logistique."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table class=\"simpletable\">\n",
+       "<caption>Generalized Linear Model Regression Results</caption>\n",
+       "<tr>\n",
+       "  <th>Dep. Variable:</th>      <td>Frequency</td>    <th>  No. Observations:  </th>  <td>     7</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Model:</th>                 <td>GLM</td>       <th>  Df Residuals:      </th>  <td>     5</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
        "  <th>Model Family:</th>       <td>Binomial</td>     <th>  Df Model:          </th>  <td>     1</td>  \n",
        "</tr>\n",
        "<tr>\n",
@@ -524,10 +917,10 @@
        "  <th>Method:</th>               <td>IRLS</td>       <th>  Log-Likelihood:    </th> <td> -2.5250</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Date:</th>           <td>Sat, 13 Apr 2019</td> <th>  Deviance:          </th> <td> 0.22231</td> \n",
+       "  <th>Date:</th>           <td>Wed, 07 Dec 2022</td> <th>  Deviance:          </th> <td> 0.22231</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>               <td>19:11:24</td>     <th>  Pearson chi2:      </th>  <td> 0.236</td>  \n",
+       "  <th>Time:</th>               <td>15:54:33</td>     <th>  Pearson chi2:      </th>  <td> 0.236</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>No. Iterations:</th>         <td>4</td>        <th>  Covariance Type:   </th> <td>nonrobust</td>\n",
@@ -555,8 +948,8 @@
        "Model Family:                Binomial   Df Model:                            1\n",
        "Link Function:                  logit   Scale:                          1.0000\n",
        "Method:                          IRLS   Log-Likelihood:                -2.5250\n",
-       "Date:                Sat, 13 Apr 2019   Deviance:                      0.22231\n",
-       "Time:                        19:11:24   Pearson chi2:                    0.236\n",
+       "Date:                Wed, 07 Dec 2022   Deviance:                      0.22231\n",
+       "Time:                        15:54:33   Pearson chi2:                    0.236\n",
        "No. Iterations:                     4   Covariance Type:             nonrobust\n",
        "===============================================================================\n",
        "                  coef    std err          z      P>|z|      [0.025      0.975]\n",
@@ -567,7 +960,7 @@
        "\"\"\""
       ]
      },
-     "execution_count": 4,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -593,6 +986,89 @@
     "estimations avec des pincettes.\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<table class=\"simpletable\">\n",
+       "<caption>Generalized Linear Model Regression Results</caption>\n",
+       "<tr>\n",
+       "  <th>Dep. Variable:</th>  <td>MalfunctionHappen</td> <th>  No. Observations:  </th>  <td>    23</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Model:</th>                 <td>GLM</td>        <th>  Df Residuals:      </th>  <td>    21</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Model Family:</th>       <td>Binomial</td>      <th>  Df Model:          </th>  <td>     1</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Link Function:</th>        <td>logit</td>       <th>  Scale:             </th> <td>  1.0000</td> \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Method:</th>               <td>IRLS</td>        <th>  Log-Likelihood:    </th> <td> -10.158</td> \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Date:</th>           <td>Wed, 07 Dec 2022</td>  <th>  Deviance:          </th> <td>  20.315</td> \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Time:</th>               <td>15:54:51</td>      <th>  Pearson chi2:      </th>  <td>  23.2</td>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>No. Iterations:</th>         <td>5</td>         <th>  Covariance Type:   </th> <td>nonrobust</td>\n",
+       "</tr>\n",
+       "</table>\n",
+       "<table class=\"simpletable\">\n",
+       "<tr>\n",
+       "       <td></td>          <th>coef</th>     <th>std err</th>      <th>z</th>      <th>P>|z|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Intercept</th>   <td>   15.0429</td> <td>    7.379</td> <td>    2.039</td> <td> 0.041</td> <td>    0.581</td> <td>   29.505</td>\n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Temperature</th> <td>   -0.2322</td> <td>    0.108</td> <td>   -2.145</td> <td> 0.032</td> <td>   -0.444</td> <td>   -0.020</td>\n",
+       "</tr>\n",
+       "</table>"
+      ],
+      "text/plain": [
+       "<class 'statsmodels.iolib.summary.Summary'>\n",
+       "\"\"\"\n",
+       "                 Generalized Linear Model Regression Results                  \n",
+       "==============================================================================\n",
+       "Dep. Variable:      MalfunctionHappen   No. Observations:                   23\n",
+       "Model:                            GLM   Df Residuals:                       21\n",
+       "Model Family:                Binomial   Df Model:                            1\n",
+       "Link Function:                  logit   Scale:                          1.0000\n",
+       "Method:                          IRLS   Log-Likelihood:                -10.158\n",
+       "Date:                Wed, 07 Dec 2022   Deviance:                       20.315\n",
+       "Time:                        15:54:51   Pearson chi2:                     23.2\n",
+       "No. Iterations:                     5   Covariance Type:             nonrobust\n",
+       "===============================================================================\n",
+       "                  coef    std err          z      P>|z|      [0.025      0.975]\n",
+       "-------------------------------------------------------------------------------\n",
+       "Intercept      15.0429      7.379      2.039      0.041       0.581      29.505\n",
+       "Temperature    -0.2322      0.108     -2.145      0.032      -0.444      -0.020\n",
+       "===============================================================================\n",
+       "\"\"\""
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "real_data[\"Success\"] = real_data.Count-real_data.Malfunction\n",
+    "real_data[\"Intercept\"]=1\n",
+    "\n",
+    "real_logmodel=sm.GLM(real_data['MalfunctionHappen'], real_data[['Intercept','Temperature']], family=sm.families.Binomial(sm.families.links.logit)).fit()\n",
+    "\n",
+    "real_logmodel.summary()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -605,12 +1081,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -648,7 +1124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -686,6 +1162,99 @@
     "analyse et de regarder ce jeu de données sous tous les angles afin\n",
     "d'expliquer ce qui ne va pas."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Et maintenant la vrai probabilité en fonction de la température"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "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": [
+    "data_pred = pd.DataFrame({'Temperature': np.linspace(start=30, stop=90, num=121), 'Intercept': 1})\n",
+    "data_pred['MalfunctionHappen'] = real_logmodel.predict(data_pred[['Intercept','Temperature']])\n",
+    "data_pred.plot(x=\"Temperature\",y=\"MalfunctionHappen\",kind=\"line\")\n",
+    "plt.scatter(x=real_data[\"Temperature\"],y=real_data[\"MalfunctionHappen\"])\n",
+    "plt.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0.99960878])"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "real_logmodel.predict([1, 31])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "La probabilité qu'un incident arrive à 31°F est tellement haute que s'en est ridicule."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Probabilité qu'au moins un joint lache: 0.30434782608695654\n",
+      "Probabilité que 2 joint lache: 0.09262759924385634\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"Probabilité qu'au moins un joint lache:\", np.sum(real_data.MalfunctionHappen)/len(real_data))\n",
+    "print(\"Probabilité que 2 joint lache:\", (np.sum(real_data.MalfunctionHappen)/len(real_data)) ** 2)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Même sans prendre en compte la température, je trouve ça beaucoup trop élevé pour lancer une fusée avec des êtres humains à l'intérieur."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -705,7 +1274,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
-- 
2.18.1