diff --git a/notebooks/statsmodels_TP_solutions.ipynb b/notebooks/statsmodels_TP_solutions.ipynb
index cc99a3991a34be312e14337434162a90ffd8364e..94b9daea061b0fd885851b292156d23573c0da17 100644
--- a/notebooks/statsmodels_TP_solutions.ipynb
+++ b/notebooks/statsmodels_TP_solutions.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "4e16caf7",
    "metadata": {},
    "outputs": [],
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c63b94db",
+   "id": "4f4198c3",
    "metadata": {},
    "source": [
     "# Toy dataset for ANOVAs"
@@ -28,7 +28,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d294fe11",
+   "id": "4b5a7dba",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -38,17 +38,21 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98dd9392",
-   "metadata": {},
+   "id": "8e90dac4",
+   "metadata": {
+    "heading_collapsed": true
+   },
    "source": [
     "## A"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1143,
-   "id": "ed3d513e",
-   "metadata": {},
+   "execution_count": 2,
+   "id": "5b4a7e26",
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [
     {
      "data": {
@@ -295,7 +299,7 @@
        "29       E         6   36.1"
       ]
      },
-     "execution_count": 1143,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -308,14 +312,16 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "78d65bc6",
-   "metadata": {},
+   "id": "ce3c48fc",
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "c29161d4",
+   "id": "5d17c0ff",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -325,17 +331,21 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c49d16f2",
-   "metadata": {},
+   "id": "ca353d75",
+   "metadata": {
+    "heading_collapsed": true
+   },
    "source": [
     "## A"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1145,
-   "id": "ff79b8f0",
-   "metadata": {},
+   "execution_count": 3,
+   "id": "7af3849e",
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [],
    "source": [
     "df.rename(columns={'yield': 'Yield'}, inplace=True)"
@@ -343,9 +353,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1146,
-   "id": "1b72ed71",
-   "metadata": {},
+   "execution_count": 4,
+   "id": "4015b5ee",
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [
     {
      "data": {
@@ -365,7 +377,7 @@
        "  <th>Date:</th>             <td>Mon, 26 Sep 2022</td> <th>  Prob (F-statistic):</th>  <td>0.0688</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>                 <td>14:37:39</td>     <th>  Log-Likelihood:    </th> <td> -61.811</td>\n",
+       "  <th>Time:</th>                 <td>15:17:00</td>     <th>  Log-Likelihood:    </th> <td> -61.811</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>No. Observations:</th>      <td>    30</td>      <th>  AIC:               </th> <td>   133.6</td>\n",
@@ -424,7 +436,7 @@
        "Model:                            OLS   Adj. R-squared:                  0.171\n",
        "Method:                 Least Squares   F-statistic:                     2.492\n",
        "Date:                Mon, 26 Sep 2022   Prob (F-statistic):             0.0688\n",
-       "Time:                        14:37:39   Log-Likelihood:                -61.811\n",
+       "Time:                        15:17:00   Log-Likelihood:                -61.811\n",
        "No. Observations:                  30   AIC:                             133.6\n",
        "Df Residuals:                      25   BIC:                             140.6\n",
        "Df Model:                           4                                         \n",
@@ -449,7 +461,7 @@
        "\"\"\""
       ]
      },
-     "execution_count": 1146,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -461,17 +473,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b55d606e",
-   "metadata": {},
+   "id": "827155ea",
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "There is no need to print an ANOVA table using `anova_lm`. All the information is already provided by the summary tables."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 941,
-   "id": "4be08184",
+   "execution_count": 5,
+   "id": "656bda87",
    "metadata": {
+    "hidden": true,
     "scrolled": true
    },
    "outputs": [
@@ -535,7 +550,7 @@
        "Residual     108.205000  25.0          NaN           NaN"
       ]
      },
-     "execution_count": 941,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -547,14 +562,16 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "03c5778b",
-   "metadata": {},
+   "id": "1ede2496",
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [],
    "source": []
   },
   {
    "cell_type": "markdown",
-   "id": "eaa2b679",
+   "id": "f024bed7",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -564,17 +581,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3fcf7e63",
-   "metadata": {},
+   "id": "6b946a85",
+   "metadata": {
+    "heading_collapsed": true
+   },
    "source": [
     "## A"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1150,
-   "id": "f453ee96",
+   "execution_count": 6,
+   "id": "b478ee2e",
    "metadata": {
+    "hidden": true,
     "scrolled": true
    },
    "outputs": [
@@ -596,7 +616,7 @@
        "  <th>Date:</th>             <td>Mon, 26 Sep 2022</td> <th>  Prob (F-statistic):</th>  <td>0.0118</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>                 <td>14:40:23</td>     <th>  Log-Likelihood:    </th> <td> -53.081</td>\n",
+       "  <th>Time:</th>                 <td>15:17:01</td>     <th>  Log-Likelihood:    </th> <td> -53.081</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>No. Observations:</th>      <td>    30</td>      <th>  AIC:               </th> <td>   126.2</td>\n",
@@ -670,7 +690,7 @@
        "Model:                            OLS   Adj. R-squared:                  0.421\n",
        "Method:                 Least Squares   F-statistic:                     3.340\n",
        "Date:                Mon, 26 Sep 2022   Prob (F-statistic):             0.0118\n",
-       "Time:                        14:40:23   Log-Likelihood:                -53.081\n",
+       "Time:                        15:17:01   Log-Likelihood:                -53.081\n",
        "No. Observations:                  30   AIC:                             126.2\n",
        "Df Residuals:                      20   BIC:                             140.2\n",
        "Df Model:                           9                                         \n",
@@ -700,7 +720,7 @@
        "\"\"\""
       ]
      },
-     "execution_count": 1150,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -712,9 +732,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1151,
-   "id": "623f55a4",
+   "execution_count": 7,
+   "id": "4b7e44f7",
    "metadata": {
+    "hidden": true,
     "scrolled": true
    },
    "outputs": [
@@ -786,7 +807,7 @@
        "Residual       60.463333  20.0          NaN           NaN"
       ]
      },
-     "execution_count": 1151,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -797,7 +818,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "efe38dd7",
+   "id": "479601d6",
    "metadata": {
     "heading_collapsed": true
    },
@@ -809,17 +830,20 @@
   },
   {
    "cell_type": "markdown",
-   "id": "33527d94",
-   "metadata": {},
+   "id": "8caafefb",
+   "metadata": {
+    "heading_collapsed": true
+   },
    "source": [
     "## A"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 937,
-   "id": "9f5945af",
+   "execution_count": 8,
+   "id": "66bf1fec",
    "metadata": {
+    "hidden": true,
     "scrolled": false
    },
    "outputs": [
@@ -995,7 +1019,7 @@
        "E-D   0.058608      False  "
       ]
      },
-     "execution_count": 937,
+     "execution_count": 8,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1006,8 +1030,10 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b83e6070",
-   "metadata": {},
+   "id": "02b5fc83",
+   "metadata": {
+    "hidden": true
+   },
    "source": [
     "We performed too many comparisons! We should have been more careful in choosing varieties of interest."
    ]
@@ -1015,8 +1041,10 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a06e55df",
-   "metadata": {},
+   "id": "049f323a",
+   "metadata": {
+    "hidden": true
+   },
    "outputs": [],
    "source": []
   },
@@ -1030,7 +1058,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5a8fb393",
+   "id": "143dff65",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -1042,7 +1070,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "fa73ad1b",
+   "id": "9c8a8d0f",
    "metadata": {
     "heading_collapsed": true
    },
@@ -1052,8 +1080,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1127,
-   "id": "e9bf82b1",
+   "execution_count": 31,
+   "id": "f06ebd84",
    "metadata": {
     "hidden": true
    },
@@ -1282,7 +1310,7 @@
        "[929 rows x 11 columns]"
       ]
      },
-     "execution_count": 1127,
+     "execution_count": 31,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1294,7 +1322,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1128,
+   "execution_count": 32,
    "id": "78c8e549",
    "metadata": {
     "hidden": true,
@@ -1522,7 +1550,7 @@
        "LINE               0         0      0      0  "
       ]
      },
-     "execution_count": 1128,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1533,8 +1561,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1129,
-   "id": "9b95655a",
+   "execution_count": 33,
+   "id": "de15fca7",
    "metadata": {
     "hidden": true
    },
@@ -1545,7 +1573,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "11309422",
+   "id": "046cf0bd",
    "metadata": {},
    "source": [
     "##"
@@ -1553,7 +1581,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "70418637",
+   "id": "0e6efdb8",
    "metadata": {},
    "source": [
     "Meaning of some columns:\n",
@@ -1570,14 +1598,14 @@
     "\n",
     "Instead of the classical `Survived` variable, we will try to explain the variations in `Fare`.\n",
     "\n",
-    "Let us first consider the first-class tickets only. In order not to loose many data, replace the missing deck information by an empty string.\n",
+    "Let us first consider the first-class tickets only. In order not to loose many data, replace the missing deck information by an empty string (`''`).\n",
     "\n",
     "Fit a _standard_ linear model for `Fare` as response variable, using `Embarked`, `Deck`, `Cabins`, `Passengers` and `Children` as independent variables (no interaction), and print the summary tables."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "1fac1025",
+   "id": "ae10616e",
    "metadata": {
     "heading_collapsed": true
    },
@@ -1587,8 +1615,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1130,
-   "id": "2e76273a",
+   "execution_count": 34,
+   "id": "6be244ef",
    "metadata": {
     "hidden": true
    },
@@ -1817,7 +1845,7 @@
        "[182 rows x 11 columns]"
       ]
      },
-     "execution_count": 1130,
+     "execution_count": 34,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1830,8 +1858,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1131,
-   "id": "cb997538",
+   "execution_count": 54,
+   "id": "583888a9",
    "metadata": {
     "hidden": true
    },
@@ -1842,28 +1870,28 @@
        "<table class=\"simpletable\">\n",
        "<caption>OLS Regression Results</caption>\n",
        "<tr>\n",
-       "  <th>Dep. Variable:</th>          <td>Fare</td>       <th>  R-squared:         </th> <td>   0.708</td>\n",
+       "  <th>Dep. Variable:</th>          <td>Fare</td>       <th>  R-squared:         </th> <td>   0.772</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.691</td>\n",
+       "  <th>Model:</th>                   <td>OLS</td>       <th>  Adj. R-squared:    </th> <td>   0.754</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   41.43</td>\n",
+       "  <th>Method:</th>             <td>Least Squares</td>  <th>  F-statistic:       </th> <td>   43.65</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Date:</th>             <td>Mon, 26 Sep 2022</td> <th>  Prob (F-statistic):</th> <td>1.30e-40</td>\n",
+       "  <th>Date:</th>             <td>Mon, 26 Sep 2022</td> <th>  Prob (F-statistic):</th> <td>5.51e-47</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>                 <td>01:31:39</td>     <th>  Log-Likelihood:    </th> <td> -883.75</td>\n",
+       "  <th>Time:</th>                 <td>16:47:16</td>     <th>  Log-Likelihood:    </th> <td> -861.37</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>No. Observations:</th>      <td>   182</td>      <th>  AIC:               </th> <td>   1789.</td>\n",
+       "  <th>No. Observations:</th>      <td>   182</td>      <th>  AIC:               </th> <td>   1751.</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Df Residuals:</th>          <td>   171</td>      <th>  BIC:               </th> <td>   1825.</td>\n",
+       "  <th>Df Residuals:</th>          <td>   168</td>      <th>  BIC:               </th> <td>   1796.</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Df Model:</th>              <td>    10</td>      <th>                     </th>     <td> </td>   \n",
+       "  <th>Df Model:</th>              <td>    13</td>      <th>                     </th>     <td> </td>   \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>Covariance Type:</th>      <td>nonrobust</td>    <th>                     </th>     <td> </td>   \n",
@@ -1874,51 +1902,60 @@
        "          <td></td>            <th>coef</th>     <th>std err</th>      <th>t</th>      <th>P>|t|</th>  <th>[0.025</th>    <th>0.975]</th>  \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Intercept</th>        <td>  -19.9204</td> <td>    7.232</td> <td>   -2.755</td> <td> 0.007</td> <td>  -34.195</td> <td>   -5.645</td>\n",
+       "  <th>Intercept</th>        <td>  -11.6346</td> <td>    6.807</td> <td>   -1.709</td> <td> 0.089</td> <td>  -25.073</td> <td>    1.804</td>\n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>C(Embarked)[T.Q]</th> <td>  -23.9597</td> <td>   29.490</td> <td>   -0.812</td> <td> 0.418</td> <td>  -82.179</td> <td>   34.260</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>C(Embarked)[T.Q]</th> <td>  -18.8295</td> <td>   32.984</td> <td>   -0.571</td> <td> 0.569</td> <td>  -83.937</td> <td>   46.278</td>\n",
+       "  <th>C(Embarked)[T.S]</th> <td>   -3.5748</td> <td>    4.549</td> <td>   -0.786</td> <td> 0.433</td> <td>  -12.555</td> <td>    5.405</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>C(Embarked)[T.S]</th> <td>   -4.8974</td> <td>    5.068</td> <td>   -0.966</td> <td> 0.335</td> <td>  -14.902</td> <td>    5.107</td>\n",
+       "  <th>C(Deck)[T.A]</th>     <td>    4.9509</td> <td>    8.045</td> <td>    0.615</td> <td> 0.539</td> <td>  -10.931</td> <td>   20.833</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>C(Deck)[T.A]</th>     <td>    2.2387</td> <td>    8.979</td> <td>    0.249</td> <td> 0.803</td> <td>  -15.485</td> <td>   19.962</td>\n",
+       "  <th>C(Deck)[T.B]</th>     <td>   18.2136</td> <td>    7.233</td> <td>    2.518</td> <td> 0.013</td> <td>    3.934</td> <td>   32.493</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>C(Deck)[T.B]</th>     <td>   13.0729</td> <td>    8.040</td> <td>    1.626</td> <td> 0.106</td> <td>   -2.798</td> <td>   28.944</td>\n",
+       "  <th>C(Deck)[T.C]</th>     <td>    0.5132</td> <td>    6.418</td> <td>    0.080</td> <td> 0.936</td> <td>  -12.157</td> <td>   13.184</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>C(Deck)[T.C]</th>     <td>    2.2798</td> <td>    7.141</td> <td>    0.319</td> <td> 0.750</td> <td>  -11.817</td> <td>   16.376</td>\n",
+       "  <th>C(Deck)[T.D]</th>     <td>   -4.6450</td> <td>    7.440</td> <td>   -0.624</td> <td> 0.533</td> <td>  -19.333</td> <td>   10.043</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>C(Deck)[T.D]</th>     <td>   -6.4853</td> <td>    8.296</td> <td>   -0.782</td> <td> 0.435</td> <td>  -22.860</td> <td>    9.890</td>\n",
+       "  <th>C(Deck)[T.E]</th>     <td>  -11.8527</td> <td>    8.103</td> <td>   -1.463</td> <td> 0.145</td> <td>  -27.849</td> <td>    4.143</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>C(Deck)[T.E]</th>     <td>   -9.9150</td> <td>    9.067</td> <td>   -1.093</td> <td> 0.276</td> <td>  -27.813</td> <td>    7.983</td>\n",
+       "  <th>C(Cabins)[T.2]</th>   <td>   -0.8461</td> <td>    9.114</td> <td>   -0.093</td> <td> 0.926</td> <td>  -18.839</td> <td>   17.147</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Cabins</th>           <td>   14.4727</td> <td>    5.619</td> <td>    2.575</td> <td> 0.011</td> <td>    3.380</td> <td>   25.565</td>\n",
+       "  <th>C(Cabins)[T.3]</th>   <td>  -16.3908</td> <td>   13.354</td> <td>   -1.227</td> <td> 0.221</td> <td>  -42.754</td> <td>    9.972</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Passengers</th>       <td>   37.3325</td> <td>    3.851</td> <td>    9.695</td> <td> 0.000</td> <td>   29.731</td> <td>   44.934</td>\n",
+       "  <th>C(Cabins)[T.4]</th>   <td>  107.5908</td> <td>   17.838</td> <td>    6.032</td> <td> 0.000</td> <td>   72.375</td> <td>  142.806</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Children</th>         <td>  -43.7836</td> <td>   13.835</td> <td>   -3.165</td> <td> 0.002</td> <td>  -71.092</td> <td>  -16.475</td>\n",
+       "  <th>C(Cabins)[T.5]</th>   <td>  -36.0599</td> <td>   35.618</td> <td>   -1.012</td> <td> 0.313</td> <td> -106.377</td> <td>   34.257</td>\n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Passengers</th>       <td>   41.6937</td> <td>    3.585</td> <td>   11.631</td> <td> 0.000</td> <td>   34.617</td> <td>   48.771</td>\n",
+       "</tr>\n",
+       "<tr>\n",
+       "  <th>Children</th>         <td>  -58.0156</td> <td>   12.642</td> <td>   -4.589</td> <td> 0.000</td> <td>  -82.973</td> <td>  -33.059</td>\n",
        "</tr>\n",
        "</table>\n",
        "<table class=\"simpletable\">\n",
        "<tr>\n",
-       "  <th>Omnibus:</th>       <td>249.208</td> <th>  Durbin-Watson:     </th> <td>   2.125</td> \n",
+       "  <th>Omnibus:</th>       <td>173.832</td> <th>  Durbin-Watson:     </th> <td>   2.009</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Prob(Omnibus):</th> <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>23662.431</td>\n",
+       "  <th>Prob(Omnibus):</th> <td> 0.000</td>  <th>  Jarque-Bera (JB):  </th> <td>6658.055</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Skew:</th>          <td> 5.611</td>  <th>  Prob(JB):          </th> <td>    0.00</td> \n",
+       "  <th>Skew:</th>          <td> 3.273</td>  <th>  Prob(JB):          </th> <td>    0.00</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Kurtosis:</th>      <td>57.721</td>  <th>  Cond. No.          </th> <td>    37.6</td> \n",
+       "  <th>Kurtosis:</th>      <td>31.899</td>  <th>  Cond. No.          </th> <td>    41.2</td>\n",
        "</tr>\n",
        "</table><br/><br/>Notes:<br/>[1] Standard Errors assume that the covariance matrix of the errors is correctly specified."
       ],
@@ -1927,34 +1964,37 @@
        "\"\"\"\n",
        "                            OLS Regression Results                            \n",
        "==============================================================================\n",
-       "Dep. Variable:                   Fare   R-squared:                       0.708\n",
-       "Model:                            OLS   Adj. R-squared:                  0.691\n",
-       "Method:                 Least Squares   F-statistic:                     41.43\n",
-       "Date:                Mon, 26 Sep 2022   Prob (F-statistic):           1.30e-40\n",
-       "Time:                        01:31:39   Log-Likelihood:                -883.75\n",
-       "No. Observations:                 182   AIC:                             1789.\n",
-       "Df Residuals:                     171   BIC:                             1825.\n",
-       "Df Model:                          10                                         \n",
+       "Dep. Variable:                   Fare   R-squared:                       0.772\n",
+       "Model:                            OLS   Adj. R-squared:                  0.754\n",
+       "Method:                 Least Squares   F-statistic:                     43.65\n",
+       "Date:                Mon, 26 Sep 2022   Prob (F-statistic):           5.51e-47\n",
+       "Time:                        16:47:16   Log-Likelihood:                -861.37\n",
+       "No. Observations:                 182   AIC:                             1751.\n",
+       "Df Residuals:                     168   BIC:                             1796.\n",
+       "Df Model:                          13                                         \n",
        "Covariance Type:            nonrobust                                         \n",
        "====================================================================================\n",
        "                       coef    std err          t      P>|t|      [0.025      0.975]\n",
        "------------------------------------------------------------------------------------\n",
-       "Intercept          -19.9204      7.232     -2.755      0.007     -34.195      -5.645\n",
-       "C(Embarked)[T.Q]   -18.8295     32.984     -0.571      0.569     -83.937      46.278\n",
-       "C(Embarked)[T.S]    -4.8974      5.068     -0.966      0.335     -14.902       5.107\n",
-       "C(Deck)[T.A]         2.2387      8.979      0.249      0.803     -15.485      19.962\n",
-       "C(Deck)[T.B]        13.0729      8.040      1.626      0.106      -2.798      28.944\n",
-       "C(Deck)[T.C]         2.2798      7.141      0.319      0.750     -11.817      16.376\n",
-       "C(Deck)[T.D]        -6.4853      8.296     -0.782      0.435     -22.860       9.890\n",
-       "C(Deck)[T.E]        -9.9150      9.067     -1.093      0.276     -27.813       7.983\n",
-       "Cabins              14.4727      5.619      2.575      0.011       3.380      25.565\n",
-       "Passengers          37.3325      3.851      9.695      0.000      29.731      44.934\n",
-       "Children           -43.7836     13.835     -3.165      0.002     -71.092     -16.475\n",
+       "Intercept          -11.6346      6.807     -1.709      0.089     -25.073       1.804\n",
+       "C(Embarked)[T.Q]   -23.9597     29.490     -0.812      0.418     -82.179      34.260\n",
+       "C(Embarked)[T.S]    -3.5748      4.549     -0.786      0.433     -12.555       5.405\n",
+       "C(Deck)[T.A]         4.9509      8.045      0.615      0.539     -10.931      20.833\n",
+       "C(Deck)[T.B]        18.2136      7.233      2.518      0.013       3.934      32.493\n",
+       "C(Deck)[T.C]         0.5132      6.418      0.080      0.936     -12.157      13.184\n",
+       "C(Deck)[T.D]        -4.6450      7.440     -0.624      0.533     -19.333      10.043\n",
+       "C(Deck)[T.E]       -11.8527      8.103     -1.463      0.145     -27.849       4.143\n",
+       "C(Cabins)[T.2]      -0.8461      9.114     -0.093      0.926     -18.839      17.147\n",
+       "C(Cabins)[T.3]     -16.3908     13.354     -1.227      0.221     -42.754       9.972\n",
+       "C(Cabins)[T.4]     107.5908     17.838      6.032      0.000      72.375     142.806\n",
+       "C(Cabins)[T.5]     -36.0599     35.618     -1.012      0.313    -106.377      34.257\n",
+       "Passengers          41.6937      3.585     11.631      0.000      34.617      48.771\n",
+       "Children           -58.0156     12.642     -4.589      0.000     -82.973     -33.059\n",
        "==============================================================================\n",
-       "Omnibus:                      249.208   Durbin-Watson:                   2.125\n",
-       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):            23662.431\n",
-       "Skew:                           5.611   Prob(JB):                         0.00\n",
-       "Kurtosis:                      57.721   Cond. No.                         37.6\n",
+       "Omnibus:                      173.832   Durbin-Watson:                   2.009\n",
+       "Prob(Omnibus):                  0.000   Jarque-Bera (JB):             6658.055\n",
+       "Skew:                           3.273   Prob(JB):                         0.00\n",
+       "Kurtosis:                      31.899   Cond. No.                         41.2\n",
        "==============================================================================\n",
        "\n",
        "Notes:\n",
@@ -1962,20 +2002,20 @@
        "\"\"\""
       ]
      },
-     "execution_count": 1131,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "model = smf.ols('Fare ~ C(Embarked) + C(Deck) + Cabins + Passengers + Children', firstclass).fit()\n",
+    "model = smf.ols('Fare ~ C(Embarked) + C(Deck) + C(Cabins) + Passengers + Children', firstclass).fit()\n",
     "model.summary()"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "2c4a0a71",
+   "id": "5fd3a0f3",
    "metadata": {
     "hidden": true
    },
@@ -1984,14 +2024,14 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dad27a5a",
+   "id": "074c8e82",
    "metadata": {},
    "source": [
     "##\n",
     "\n",
-    "You may notice several issues, including the non-normality of the residuals, with high skewness and kurtosis.\n",
+    "If you used `ols`, you may notice several issues, including the non-normality of the residuals, with high skewness and kurtosis.\n",
     "\n",
-    "If you defined all variables as categorical, you may also be warned about multicollinearity.\n",
+    "If you defined all variables as categorical, you may also be warned about multicollinearity. Let us ignore these warnings for now.\n",
     "\n",
     "## Q\n",
     "\n",
@@ -2000,7 +2040,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ee4d4394",
+   "id": "aad150f8",
    "metadata": {
     "heading_collapsed": true
    },
@@ -2010,15 +2050,83 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1132,
-   "id": "a82a7b4a",
+   "execution_count": 55,
+   "id": "8571c87e",
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "110152         127.239141\n",
+       "110413          97.172862\n",
+       "110465          72.282743\n",
+       "110469          26.997523\n",
+       "110489          21.839335\n",
+       "                  ...    \n",
+       "PC 17759        66.261692\n",
+       "PC 17760       151.232488\n",
+       "PC 17761       113.959732\n",
+       "W.E.P. 5734     56.325306\n",
+       "WE/P 5735       86.391585\n",
+       "Length: 182, dtype: float64"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.fittedvalues"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "a13c82cf",
    "metadata": {
     "hidden": true
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "text/plain": [
+       "110152        -40.739141\n",
+       "110413        -17.522862\n",
+       "110465        -20.282743\n",
+       "110469         -0.997523\n",
+       "110489          4.710665\n",
+       "                 ...    \n",
+       "PC 17759       -2.903392\n",
+       "PC 17760      -15.599188\n",
+       "PC 17761       -7.534732\n",
+       "W.E.P. 5734     4.849694\n",
+       "WE/P 5735     -15.391585\n",
+       "Length: 182, dtype: float64"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.resid"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "c0ee64b9",
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -2029,7 +2137,7 @@
    ],
    "source": [
     "# data to plot\n",
-    "residuals = pd.DataFrame({'Residual': model.resid, 'Predicted value': model.predict()})\n",
+    "residuals = pd.DataFrame({'Residual': model.resid, 'Predicted value': model.fittedvalues})\n",
     "# scatter plot\n",
     "ax = sns.scatterplot(residuals, y='Residual', x='Predicted value')\n",
     "# zero line\n",
@@ -2039,7 +2147,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a280776d",
+   "id": "adb6d2be",
    "metadata": {
     "hidden": true
    },
@@ -2048,7 +2156,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "18b74226",
+   "id": "5c6150f9",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -2061,7 +2169,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "25e159b6",
+   "id": "57c49da8",
    "metadata": {
     "heading_collapsed": true
    },
@@ -2071,15 +2179,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1136,
-   "id": "92bc8372",
+   "execution_count": 59,
+   "id": "c2b97f70",
    "metadata": {
     "hidden": true
    },
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/flaurent/Projects/scientific_python/lib/python3.10/site-packages/statsmodels/stats/outliers_influence.py:696: RuntimeWarning: invalid value encountered in sqrt\n",
+      "  return self.resid / sigma / np.sqrt(1 - hii)\n",
+      "/home/flaurent/Projects/scientific_python/lib/python3.10/site-packages/statsmodels/stats/outliers_influence.py:716: RuntimeWarning: divide by zero encountered in divide\n",
+      "  cooks_d2 *= hii / (1 - hii)\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -2089,14 +2207,15 @@
     }
    ],
    "source": [
+    "from statsmodels.stats.outliers_influence import OLSInfluence\n",
     "fig = OLSInfluence(model).plot_index(threshold=0.05)\n",
     "fig.gca().axhline(0.5, color='r', linestyle=':', linewidth=1);"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1139,
-   "id": "059fdf55",
+   "execution_count": 61,
+   "id": "1a794460",
    "metadata": {
     "hidden": true
    },
@@ -2119,7 +2238,7 @@
        "  <th>Date:</th>             <td>Mon, 26 Sep 2022</td> <th>  Prob (F-statistic):</th> <td>5.14e-61</td>\n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>                 <td>01:36:48</td>     <th>  Log-Likelihood:    </th> <td> -790.26</td>\n",
+       "  <th>Time:</th>                 <td>16:47:40</td>     <th>  Log-Likelihood:    </th> <td> -790.26</td>\n",
        "</tr>\n",
        "<tr>\n",
        "  <th>No. Observations:</th>      <td>   181</td>      <th>  AIC:               </th> <td>   1603.</td>\n",
@@ -2196,7 +2315,7 @@
        "Model:                            OLS   Adj. R-squared:                  0.825\n",
        "Method:                 Least Squares   F-statistic:                     85.62\n",
        "Date:                Mon, 26 Sep 2022   Prob (F-statistic):           5.14e-61\n",
-       "Time:                        01:36:48   Log-Likelihood:                -790.26\n",
+       "Time:                        16:47:40   Log-Likelihood:                -790.26\n",
        "No. Observations:                 181   AIC:                             1603.\n",
        "Df Residuals:                     170   BIC:                             1638.\n",
        "Df Model:                          10                                         \n",
@@ -2227,7 +2346,7 @@
        "\"\"\""
       ]
      },
-     "execution_count": 1139,
+     "execution_count": 61,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2238,35 +2357,10 @@
     "model.summary()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 1140,
-   "id": "0ac923df",
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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ceGyfPn3QvXt3ZGRkODyf0WiETqez+SIiIiLv5THBZ9iwYVizZg22bduGDz74APn5+Rg1ahQqKytRUlICuVyO0NBQm9dERUWhpKTE4TmXLFkCtVotfsXFxXXyuyAiIiJX8phHXTfffLP47+TkZAwbNgzx8fH44osvEBjYtsUDFy1ahPnz54vf63Q6hh8iIiIv5jEtPo2Fhobid7/7HXJzcxEdHQ2TyYSKigqbY86fP2+3T5CVQqGASqWy+SIiIiLv5bHBR6/XIy8vDzExMRgyZAj8/f2xfft2cX92djYKCgowfPhwF5aSiIiI3InHPOp66qmnMGnSJMTHx6OoqAgvvPACfH19MXXqVKjVajzwwAOYP38+wsPDoVKp8Nhjj2H48OEc0UVERESiFgefb775psUn/eMf/9imwjhz9uxZTJ06FWVlZejWrRtGjhyJ/fv3o1u3bgCAf/zjH/Dx8cGUKVNgNBoxfvx4vP/++x1eDiIiIvJcMkEQhJYc6OPTsqdiMpkMdXV17SqUq+h0OqjVami1Wvb3ISIi8hCtuX+3uMXHYrG0u2BEREREruSxnZuJiIiIWqvNnZurqqqwe/duFBQUwGQy2ex7/PHH210wIiIioo7WpuCTmZmJW265BQaDAVVVVQgPD0dpaSmUSiUiIyMZfIiIiMgttelR17x58zBp0iSUl5cjMDAQ+/fvx5kzZzBkyBD8/e9/7+gyEhEREXWINgWfI0eO4Mknn4SPjw98fX1hNBoRFxeHZcuW4a9//WtHl5GI2kFrMCHvgh6ZBeXIu6iH1mBq/kVERF6qTY+6/P39xeHtkZGRKCgoQN++faFWq1FYWNihBSSitiuqqMaCDVnYm1MqbktN0mDplGTEhrZtjTsiIk/WphaflJQU/PzzzwCA0aNHY/HixVi3bh2eeOIJ9O/fv0MLSERtozWYmoQeANiTU4qFG7LY8kNEktSm4PPaa68hJiYGAPDqq68iLCwMjzzyCC5evIiVK1d2aAGJqG1K9aYmocdqT04pSvUMPkQkPW161DV06FDx35GRkdi2bVuHFYiIOoauxux0f2Uz+4mIvBEnMCTyUqoAf6f7Q5rZT0TkjdrU4pOQkACZTOZw/2+//dbmAhFRx9AEy5GapMEeO4+7UpM00ATLXVAqIiLXalPweeKJJ2y+N5vNyMzMxLZt2/D00093RLmIqJ3USjmWTknGwg1ZNuEnNUmD16ckQ61k8CEi6WlT8Jk7d67d7e+99x4OHjzYrgIRUceJDQ3E8qkpKNWbUFljRkiAPzTBcoYeIpIsmSAIQked7LfffsOgQYOg0+k66pRdqjXL2hMREZF7aM39u0M7N3/11VcIDw/vyFMSERERdZg2PepKSUmx6dwsCAJKSkpw8eJFvP/++x1WOCIiIqKO1KbgM3nyZJvvfXx80K1bN4wZMwZ9+vTpiHIRERERdbgO7ePj6djHh4iIyPO05v7d4haf1nRYZmggIiIid9Ti4BMaGup00sKG6urq2lwgIiIios7S4uCzc+dO8d+nT5/GwoULMWPGDAwfPhwAkJGRgbVr12LJkiUdX0oiIiKiDtCmPj5jx47Fgw8+iKlTp9ps//TTT7Fy5Urs2rWro8rXpdjHh4iIyPN0+jw+GRkZNiu0Ww0dOhQ//fRTW05JRERE1OnaFHzi4uLw0UcfNdn+r3/9C3Fxce0uFBERuRetwYS8C3pkFpQj76IeWoPJ1UUiapM2zePzj3/8A1OmTMF3332HYcOGAQB++ukn5OTkYMOGDR1aQCIicq2iimos2JCFvY0Wu106JRmxoYEuLBlR67WpxeeWW27Br7/+ikmTJuHSpUu4dOkSJk2ahF9//RW33HJLR5eRiIhcRGswNQk9ALAnpxQLN2Sx5Yc8TptafID6x12vvfZaR5aFiIjcTKne1CT0WO3JKUWp3gS1Ut7FpXINrcGEUr0JuhozVIH+0ATJJfPevUmLg09WVhb69+8PHx8fZGVlOT02OTm53QUjItfghzs1pKsxO91f2cx+b8HHfd6jxcFn0KBBKCkpQWRkJAYNGgSZTAZ7I+FlMhknMCTyUPxwp8ZUAf5O94c0s98bNPe4b/nUFP5x4EFaHHzy8/PRrVs38d9E5F344U72aILlSE3SYI+dx12pSRpogr3/muDjPu/S4uATHx9v999E5B344U72qJVyLJ2SjIUbsmzCT2qSBq9PSZbENcHHfd6lTZ2b165dC41Gg1tvvRUA8Mwzz2DlypXo168f1q9fz2BE5IH44U6OxIYGYvnUFJTqTaisMSMkwB+aYOn0/eLjPu/SpuHsr732GgID65/3Z2Rk4N1338WyZcug0Wgwb968Di2g1ZIlS/D73/8eISEhiIyMxOTJk5GdnW1zzJgxYyCTyWy+Hn744U4pD5G34Yc7OaNWytErMhiDuoehV2SwZEIPcOVxnz1SedznTdoUfAoLC5GYmAgA2Lx5M/70pz/hoYcewpIlS7B3794OLaDV7t27MXv2bOzfvx9paWkwm8246aabUFVVZXPcrFmzUFxcLH4tW7asU8pD5G344U5kn/VxX+PfDyk97vMmbXrUFRwcjLKyMnTv3h3ff/895s+fDwAICAhAdXV1hxbQatu2bTbfr1mzBpGRkTh06BBSU1PF7UqlEtHR0Z1SBiJvxr4cRI5J/XGfN2lT8Lnxxhvx4IMPIiUlxWa25uPHj6NHjx4dWT6HtFotACA8PNxm+7p16/Cf//wH0dHRmDRpEp5//nkolUq75zAajTAajeL3Op2u8wpM5AH44U7kmFrJ3wVv0Kbg89577+G5555DYWEhNmzYgIiICADAoUOHMHXq1A4toD0WiwVPPPEERowYgf79+4vb77nnHsTHxyM2NhZZWVlYsGABsrOzsXHjRrvnWbJkCV566aVOLy+RJ+GHOxF5M5lgbxZCN/fII4/gu+++Q3p6Oq6++mqHx+3YsQNjx45Fbm4uevXq1WS/vRafuLg4aLVaqFSqTik7ERERdSydTge1Wt2i+3ebOjcDwN69e3Hvvffiuuuuw7lz5wAA//73v5Gent7WU7bInDlzsHXrVuzcudNp6AEgrhyfm5trd79CoYBKpbL5IiIiIu/VpuCzYcMGjB8/HoGBgTh8+LDYaqLVajtt4VJBEDBnzhxs2rQJO3bsQEJCQrOvOXLkCAAgJiamU8pEREREnqVNwedvf/sbVqxYgY8++gj+/lfm9hgxYgQOHz7cYYVraPbs2fjPf/6DTz/9FCEhISgpKUFJSYk4iiwvLw+vvPIKDh06hNOnT+Obb77Bfffdh9TUVC6aSkRERADa2Lk5OzvbZgi5lVqtRkVFRXvLZNcHH3wAoH6SwoZWr16NGTNmQC6X44cffsDbb7+NqqoqxMXFYcqUKXjuuec6pTyuxNWziYiI2qZNwSc6Ohq5ublNhq6np6ejZ8+eHVGuJprrgx0XF4fdu3d3ys9ur44MKufKDThTZkBFtRkB/r7YfuoCsot1eOm2/lw9m4iIqBltCj6zZs3C3LlzsWrVKshkMhQVFSEjIwNPPvkkFi9e3NFl9GhFFdVNVrxOTdJg6ZRkp0HFXliqrKnFgo1Z2JdbJh43IjEC949IwOKvj+HNOwey5YeIiMiJNgWfhQsXwmKxYOzYsTAYDEhNTYVCocDTTz+NBx98sKPL6LG0BlOT0APUr3S9cEMWlk9NsRtU7IWlJXcMwLdZRTahB4D4fUr3MJToaiQffPgYkIiInGlT52aZTIZnn30Wly5dwrFjx7B//35cvHgRarW6RaOtpKJUb2oSeqz25JSiVG9qst1RWIoMUWBvo9BjtS+3DClxoThbXg2toek5paKoohpz1mdi7Fu7cfv7P2Lsm7vx2PpMFFV0zjIqRETkeVoVfIxGIxYtWoShQ4dixIgR+Pbbb9GvXz8cP34cvXv3xj//+c9OW53dE+lqzE73V9rZ7ygsGWstTs9l3W8vTElBc61rUg6ERER0RasedS1evBgffvghxo0bhx9//BF33nkn7r//fuzfvx9vvvkm7rzzTvj6+nZWWT2OKsDf6f4QO/sdhSWFn/OMqg70R8ZvZYgIkuZjnZa0rvGRFxERtarF58svv8Qnn3yCr776Ct9//z3q6upQW1uLX375BX/+858ZehrRBMuRmqSxuy81SQNNcNMbsaOwlFlYgRGJEXb3jUyMQEiAH1al59sNU1LQltY1IiKSnlYFn7Nnz2LIkCEAgP79+0OhUGDevHmQyWSdUjhPp1bKsXRKcpPwk5qkwetTku22QDgKS6vS8/HYDUkY1WjfqEQNnh7fBzPX/Iyh8WF2w5QUtKV1jYiIpKdVj7rq6uogl1+5sfr5+SE4OLjDC+VNYkMDsXxqCkr1JlTWmBES4A9NsOORRtawtHBDFvY0eHQzND4MPcKVeHdqCkp0NThbXt9hN7OwAlM/2o8RvSLw4h+vQanehN9Kqzx2RFNbR2VZA+MeO4+7HLWuEVHLccQkeYtWrc7u4+ODm2++GQqFAgCwZcsW3HDDDQgKCrI5buPGjR1byi7SmtVdO5v1Q8ZRWGq4XxXoD7mvDxZtOtrq+YLcSVvnPGr4+saB0dq6FuMhdUDkjtr7u0nU2Vpz/25V8Ln//vtbdNzq1atbekq34k7BpzW0BhPmrM+027k3NUnjcL4gd9JR78FRYORfq0Rt4w2fL+T9WnP/btWjLk8NNJ6oNTdqZyOaDp4pR4XB7PY3/Y4alaVWNn1v/GuVqO04YpK8TZtmbqb2aS7UtPZG7WhEk1Lui3empuC5zUdtJj90x5u+s/cwc2QCjLV1yCwob3Vwa25+n1du649LBpPbBkIiV+OISfI2DD5drLlQ05ZlLhyNaJo5MgGr9+U3WeaiuSUzXMHee7AGt9X78vHujlxxe2uCW3N/reZe1OOBtQdbfV4iqeCISfI2bVqygtqmJbMLt2WZC0dD4FPiQpuEnubO5Sr23kNzwa3hbMxagwl5F/Q4fOYSTpXo8Ov5Svx2UY86QYBS7nh+qYYzYnOWZ+mxXjeZBeXIu6jn/70dbZmPjMidscWnC7Uk1LSlWdnREPjmaKvdp4na3ntIiQu1aelpqGHfAnutaNZV6z/7qQDvTE3B4+szYTDVNTlP4xmx2WdBOtj3q2Ucfb44m4+MyJ0x+HShloSatjYr25svyGxxvr6Xs5YQV2j8HswW5wMOK2vMDlvRGq5av2ZfPmaOTGgSokYkRiCzsMLuecm7teWRspS1dj4yInfGR11dKFjhPGcGKfyabVYODvBz2DSvVsrRKzIYg7qHoVdkMHxkMofLXIxIjICvj/vNuN3wPYQ386EaEuDvtBXNump9em4ZrutpWw/WFqFV6fl2z0verS2PlKWu8ecLQw95Krb4dCG5rw9GJEbY7XczIjECcl8fp83Kf5vcH89uOoofTl6w2e6oad7PR4b7RyQAgM3PtN703TH4NBQc4IeRiRFIt1NfIxMjEBzgh6KKaqfnsPbhCfD3xfb5o1FZY0aQwg8Hz5TbffzFPgvSwJFKRNLF4NOFKqpNToOIttoEIAixoYF4486BKK8yQVdTC1WgH1QB/nj1vydsQg9g2zQPwGaYfLDCD5//VICU7mGYOSIBxloLFH4+yCyswOc/FeDvdw7ssvfeFlXGWswYkQABTetrxogEVBlrm300aO3Dow70R6/IK8urBCn88F18GPssSBRHKhFJF4NPFwpW+GPqRwcwc2RCkyDy+PpMbJkzEoD9TpejkjSYfl0P7My+2KSV4uCZcpQbzHj+62M2r7mxbySen9gPz20+1mQ4uCfc4CsMJjy+PtNhff3ngWHo1S0Io5I0dh9bjErU4Og5LUbZacVhnwVp49puRNLVqiUrvF1nLVlxrtwAXU0t9DW1qLVYsC+vDKvS820CzKgkDd693GrjaHr4EYkRSOke1qST7pwbEvFLQbnNJIVWN/aNxN9uHwB9Ta3H3eBPFesw4Z97He7fNncUYtQBOFmsw/KduU1aheZcn4TCS1W4NiECFkGAttp9Z66mrse13Yi8R6ctWUGtV1hWhXPaagQp/FBrERAS4I+RiREY1iMc//efQzCY6jAiMQKPjkmEsdaCyppap511Z15+VNaQs2HfaScvYOHNtTaPeTyFj4/MaZ8oXx8ZSvUmzFx70G6r0ANrf8ans/6An09fwtNfZYmv9ZYhy1x/rH3Y6kckTQw+nai43ABjnQXLd9i2RoxMjMCLf+yPjY8Ox7nyGvEmvfGR61BtbjrXTEMNJ9xryLq0Q0pcKIy1FgT4++JwQTlWped7bEfNlnTO1labYTDVOQx+RnMdXvjmuM02bxiyzDloOoa9td2IyLsx+HQis0XAC98cb9JikZ5bhhe/OYZXJw8Ql0sAAF1NLSKCnH8IhwbadrpMTdIgLjwQ796TglXptks7jEqMwLv3pEAV6JkdNSOC5Fjy7UmnnbObe1BbZaqzO3GhJ09UyDloiIjajsGnE1WZ6hwuGZGeWwZDo9YdVUD9PD439o1E7xhVk9ab7GIdekUGi8OyrU3zNbUWvLLlRJNh3/V9fmT4+13uPXrLEbVSjpdu64+FG7Kcds521El1VJIGhwvKHZ7fU1vCuFo2EVHbMfh0Il0zS0I0vPGOTIxA2OU+Gs9P7IdFm47a3OxHJkbgtdsHIEoVgAA/E/x8ZKgy1eLXC3qEKPwwsHsYDhVUNGnd2JtbCl21GVGqgI59c12kuX4YzuY9evm2/rjlHcedoz11yDLnoCEiajsGn07U3COmkAB/bH1sJPRGM65SByJKFQCtwYRnNx+z+3jsuc3HsOSOASgsr8byHTlN+r04WpPKndbkaovm+mE4CkfGWgsGdw91OgGiJ+qoOWjYOZqIpMgzP/k9RLDc1+nMw0p/X4z++y6xs3NJRTWqTHXNPsZoHHqAK51/7a1J5W5rcnUGe+Hot4v6ZidA9EQdMQcNO0cTkVRxra5OpAr0x98mD8DIRutljUyMwN8mD8D/ThYDqG/Neev7UzDXWXCpyvkaQcZax/2GrGtTNTQiMQJBcmnmW221GY+vz0RK9zB8PH0o3p82GB9PH4qU7mF4fH1ms48i3ZX18V7jNd1aOjFlc52jG67/RkTkbaR5R+wiaqUcNaY6PHtrPwgAKqvNCAn0hwwCzl4y4O20+pYZTbAcc8f1xsJNR+3O09NQcyGm4XD3EYkReOyGJIQqPbMvS3upAvydDnX31D4+QPvmoGHnaCKSMgafThYVGogAuS9K9SboARRXVCOzsMJm5ubXpyTj5a31w95Tuoc5X8jU33kjXVx4IN6fNhgKPx9cqDSiR7hSsjcxR4+ElHJfPD+xHyyCgMyCco/t39LWOWjYOZqIpIzBpwtYb1CmOgvuWrm/yf5IlUIMOqvS8/HO5aUr7E3aV1tncRiMRiVpECT3gyZYAVWgH/pfpXbr0Vyd3bnW3ogvpdwXq2b8Hu/tyMWijUfFY6XUv4ULdBKRlDH4dKHwILndzs76miujsAymuiYLc8aHK/Hd8RJsPnwWC2/ui7/e3BcluhrIZDJxdubrekXgyRt743SZATXmOuiNtcgsqMCY33Vzy3WHuqpzbeNHQmFKOZ7bfAx7c6U7+R8X6CQiKfPK4PPee+/hjTfeQElJCQYOHIjly5fj2muvdXWxEKUKwGu3D8BfNx21CT+qRsOqG/dL+W7uKKQmaXDXkKuxaNNR21XbEzX472MjUW2uw9++PdGklShBEwSl3NetbuZdPfNww3NVmWqbhJ6GP79EV9Pmn+0pw8OdzX3Uks7RRESezOuCz+eff4758+djxYoVGDZsGN5++22MHz8e2dnZiIyMdHXx0D0iCG/eNQjlVSboamqhCvBDSICfw2HvoxI1UPj5QKkKwLObjjZZgX1vbin251/Ct1lFDoe4vzZ5gFvdzLq6c23D1qX3pw12euzZ8mpEqwJa/fM9bXg4F+gkIqnyuuHsb731FmbNmoX7778f/fr1w4oVK6BUKrFq1SpXF00UpQpAnxgVrk0IR58YFa4KU+K125sOex+RGIHpI3pg4vJ0nC2vbhJ6rCJDFA737cstQ5XJvear6crOtY1blxR+zV/ypfrWDef21OHhaqUcvSKDMah7GHpFBjP0EJEkeFXwMZlMOHToEMaNGydu8/Hxwbhx45CRkdHkeKPRCJ1OZ/MFAL+e14nH5JyvRFFFNQCgxlyHY+e00F+e+O5ipREniq4cm3dRj7PlBgCAuc6CY+e04k2+TG/EsXNa8dj80ioUXqo/ts4iQFdTixcmXYP/PTEK/7x7EBZP7ItBcaHiTMy5F/QO33eOk30AUKStAVAfOI6d08JcVz/k/Wy5AXkXr7z2RJEOFyuNAAC9sRbHzmlRc3k9saKKauScrxSPPVWiwwVd/XkNJttjS7Q1+LXBsb+er0Sx9kodllwujyPW0W7G2vr6tgahi5VGHC+6Uod5F/ViHVrr2zpLtbW+G7cuZRZWYGSvcLs/97pe4cgsrEDO+UqcLq0Stx87pxXnV9Ia6uuw9nIdFl4yILOwwmkLVvHl93uuotrm//FksQ4XKuv3VTWq72KtbX1nl1Ti/OX6rjbV10v15Xo6r6tBdsmVY3Ma1fexc1pxssYLlTU4WXzlms29oMe5y9e3qdZiU9+letv6/q1Bfdda69tQf+ylKpPN9X26tAoFZfXHWiwCjp3TouJyAKww1B9bZ6lfYbagzID8RvVdpq+/DrXVttds4SXba/Z4kVa8ZisvX9/G2roG9X2lXk4WX7lm7dV342vWep1a69Bw+Q+IC7oanCrp+s+IhvVdfrm+hcur9J4pq8KZsvo6FIT6Y8sbXbPW+i685Li+3eUzwuaa1TW+ZivFa7YjPiMa1rf1mq1zcM1aGlyzrfmM+K3RNVuqt71mTZenIeFnRPs/I1rCq4JPaWkp6urqEBUVZbM9KioKJSUlTY5fsmQJ1Gq1+BUXFwcAePjfh8VjHlufiZV7fgNQ/8s6cXk6jp6t/8/bePgspn50ZZTWU1/+guXb6/vmlFeZMHF5Og6evgQA+O/RYtzx/o/isc9tPopl/8sGUP+hMHF5On49r4dFAOZ+fgQvbz2J93bmiSFg4+GziAsLxKZHrwMAPDK6J76bOwrPTOiNpd+dclov1oU6D56+hInL08UPxOXbc/HUl7+Ix039aD82Hj4LADh6VouJy9PFD/+Ve37DY+szxWNnrPoZ6w4UAAByzusxcXm6eGGuzTiNWZ9cWXX+4X8fwup9pwEABZcMeGTdYQy6Wm23rMEKX3x95BwA4ILOiInL0/FjbinyLujx3s5c3LkiQ2xBWfBVFt7+IQdA/bpoE5en46f8+vredrwEt723r0nr0qr0fDw9oa/dn/2X4T2wKj0f/zlQgJe2HBe3T1yeju+P118/Gb+VYuLydPHG9ub32Xjj8v+jI9Yb3bs7cjH/iyPi9mn/OoAvD9bX94liHSYuTxc/YP61Nx+PrrtyHc5c8zP+nXEGQP2H+cTl6eIN6d8ZZzBzzc/isY+uO4x/7c0HUP9BOnF5Ok5c/iD78uBZTPvXAfHY+V8cEfuTlVXV1/fhggoAwJZfivCnD678wbBo41G8+X39e9Ub66/ZjN/qA9/3x0swcXm6eOxLW47j1W9PAADMFgsmLk/HzuwLAIDdv17ExOXpYkBZuu0kFn99THztbe/tw7bL9f1Tfv01a51s8u0fcrDgqyzx2Ls/3C9eL78U1l+zF3T1H4grduVh7mdX6vu+VT/h858LAQCnSioxcXk6Ci4ZoDWY8I/vf8WM1T8h76IeWoMJsz45iLUZpwHU3xAnLk9Hzvn6+l53oAAzVl2p7678jEi/3D/th5PnMXF5unhjeGXrCbyytb6+6ywCJi5Pxw8nzwMA0nPrr1lrcFv2v2w8t/nKiMY73v8R/z1aP5mqu3xGTFyejlOXb9Sf/1yI+1b9JB4797MjWLErD8CVz4hfCuvr++sj53D3h1fquyWfEVaLvz6GpdtOAqgPVBOXp2P3rxcBADuzL2Di8nSYLfU311e/PdGqz4iGI0j/9EEGtvxSBAA4XFCBicvTUVZVf83yM6LtnxGVrZiQViZY/2TwAkVFRbjqqqvw448/Yvjw4eL2Z555Brt378aBAwdsjjcajTAajeL3Op0OcXFx+PnXQgxNuhpAfTIOUvghNjQQNeb6lpcemiAEK/xwsdKIi5VG9ItVAai/2BR+Prg6TAlznQXZJZXoHqGEKsAfZXojirU16H9V/Q0/v7QKfj4yxIUrUWcRcLJYh7gwJU6V6HC3nSHvj4xJwN1Du+O5TUeRnndJ3P6HhDA8MKon1v542m4foZS4UDx3ax8M6REBXY0ZBWUG9I4Ogb+vD86WG2CstaBXt2AA9X/NdQtRoFuIAnpjLU6XViExMhgB/r4oqqhGlbEWSVEhAOr/mgtXyhGpCoDBVIvfLl45tkRbA12NGb+7fOyv5ysREuCHGPWVOgzw98HLW0406Vz7yOhe6K4JwlWhgTDW1uHH3DKs3JOHjN8u2Ry3dEoyqs11kPv6IC78Sn3HhSuhDrxS34H+vhj71m6bOpk7LhG1dQJ+F1VfD+Y6C/bllWLLkSL8vkc4FkzojSCFP3poggDU/3URGxqI8CA5tAYzCssN6BMdAj9fH7EFYsbqn+HItrmj0CdGhXMV1ag21SExsr6+TxbrEBEsR2RIAKqMtchvUN/F2mroa67Ud3ZJJUKV/ohSBaDaVIe8i3r06haMQLkvzutqUGEwo3d0iHjNBjeq7wRNEIIUfrhQWYMyvQl9Y+qv2dwLegTKfXFVaCBMtRb8er4S8RFKhAT4o1RvxHldDa6Jrb9mf7uoh//l+q6ts+BUSSXiwpRQK/1xqcqEoopq8fo+XVoFH5kM3SOUsFgEnCjW4eqwQIQq5agwmHC2vBp9Y1Tw9ZGhoMyAOkFAQoP6jlEHICJYAW21GYWXrlyzhZcMMNVduWaPF2kRGRKAbiEKVNaYcabMgKSoYCj8fC/Xdy0SI0Ou1HdQ/TVrre8guS8Wf3O8Sd+sh1J7IjEyBNHqALEOe3YLglLuhwu6GlwymNAnWiXWd1d+RqiV/iivMuFcRTWuiVVBJpOJrT3xEUEQBAHHi3S4KjQQYQ2uWWt9F14yoNZiv77d6TNCvGZ1NSiranjNViJQ7id+RuSc14vX7MVKIy5UXrlm8y7qm/2MaFjfvpevWWt9N75m+8Wo4HP5mrUIQos/I8x1FvRscM1GqQKgCb5yzf4uKgRyPx9+RrTjMyJGKUATHgatVguVSuXw8xjwsuBjMpmgVCrx1VdfYfLkyeL26dOno6KiAl9//bXT1+t0OqjV6hZVXGc5WazDzf9suqL41sdG4vXvTtrtyzOuTySendgXzzVa3HREYgQeuz4JsaEB6B4R1KnlbgvrKChHnWu1BhPmrM+0+xgpNUnTotFfWoMJj63PtAlYSrkv3pmagjX78m3ConVUU2uH/9v7Ga0tJ3W9jri+iMg9tOb+7VWjuuRyOYYMGYLt27eLwcdisWD79u2YM2eOawvXQo5GePn5yBx2YP7h1AU8PaE3UrqHiXP/KPx8kFlYgZlrf8bmR0d0RdHbTAAAWdPtHTH6S62UY8kdA3BRb0KNqQ5BCl8AMuRcqMSyKcmoNlvaPaqJw8M9E5fuIJImrwo+ADB//nxMnz4dQ4cOxbXXXou3334bVVVVuP/++11dtBa5OkyJV28fgGcbzfWjq3E+MktXXYuUuFBEqhTQ19QhJMAPKXGhUMp9mx1F5QotGf7dEaO/iiqqsXDDUZu5e6xrmMlkMvS63KTcXhwe7nm4dAeRNHld8Ln77rtx8eJFLF68GCUlJRg0aBC2bdvWpMOzO4uPCMLSKcmorKkVb6KWZp5IKhW+yLk8gsVYa0G1uQ4XdDX4dNYfIMC9nma2dALD9i6toDWYsOCrrCYTFlofB05MjsUt/aM7LJy0de0scg0u3UEkTV4XfABgzpw5HvNoy5Grw5Q23+df1DtdvFTp74tvjxbbtBKNSoxAz27BiFW713pdLX3E0JalFRrOnhwo93U4S/O+3DLMHJHAxxkSxqU7iKTJq4azezMZgMduSMIIO5McPnZDEo4XaTGoexg+nj4U708bjFUzfo+B3cPw0Z7fUGtxsxafaucT+lnn2bD2nUlN0tjsd9R3pqiiGnPWZ2LsW7tx+/s/4reLVXDGWGvh4wwJa+31RUTewStbfLxRmcEEc60FEwfE2nRgvqAzIkalgMFUi8yCcps1vqwruhvrLMi7oHebNaSUcueXnVLuK/67pX1n7D0+a26WZoWfj6QfZ3jK2mKdiX2ziKSHwcdDqAL88ZePf8LMkQmIVCnE7ee01aipteDj9HyHa3U9f2s/m7lsXL2GlK+PDKMSNXYfQ41K1MDXx3aIV0v6zth7fJZZWIFRiRF2R8ONSIzAhUojhsaHteEdeD5PW1usM7FvFpG0MPh4iMgQBYbEh9m06FjdOiDGbt8foD78NH7Q1VmroLeUwtcHc27ohZsHRCNKFQBjreXypGbVSIoMRqCfT6tbqOyN0FmVno9370kBILM7qqtHuFKSN7yWdi4nIvJGDD4eQq2U4/UpyU1uWKMSI8Q1VhzR29nvynlKTBYLqkx1djtjD510DV7cchw/nLoobm9JS4S9EToGUx3mfJqJh1J74tmJfaGvqYVS7osguR9Clf6Svblz/hoikjIGHw8SGxqIv985EHkX9KioNouTFAYpnP83BjvYr23F2iYdySLA7qO5vblleHnLcQzqHmYTfFrSEuFohI7BVIfDZ8px/3U9oI5u2i9Iin1cOH8NEUkZg4+HiVIFoM4i2MwSPKR7qOM+M0ka1NZZ8PH0oeIjpcMF5ViVnm/TibgrWSyCw0dz6blluH9EQpPtLWmJePbWvpheXg2ZTCa+x6HxYQ5HgEm1j4u1dUwp98XMkQlIiQu1uTZUgZ7T4Vuq4ZWI2o7BxwM1HokSqPDFK5P74/nNR2068o5KjMArt/XHy1uPY0eDFpQRiRH4ePpQ+PnaWSeiC1hXiXbEWGuxu91RS4S9EDMqSYNvHx+FMDuPtKTex0UTLMeNfSNx97XdsXpfvk2/sZGJEfjz0DgXlq7lpBxeiajtvGqR0vZyh0VK2yK7RIeLOiMiQuQQIENltRkhgf4Ilvvi5Ub9ZaxGJWrwt9v7I94Fi5fmXdA3WTEduNICMf6aKBReqrZpnTKY6rB9/ugmS0y0ZaFJRz/fyt7P8Tbnyg14ZkOW3ZY3T1igkwuMElFDkl2kVKpClXIs23YKfWPV4mMLvbEWkSqF3dADAHtzS2Fy0LLS2ez1x7GumN64BWJEYgTemZqCz34qsDuTbqnehENnyjHnhsQmj2xWpefbfTzGPi5Ajdni8HGjJ3RwZgdtImorBh8vEKUKwAuTrsFfNx21CQ2rpg91+rrmRoN1Fnurmc8cmYDV++zPRSQD8NrtA+zeyPRGs9PAZC/EcI0mzw9/nl5+InIdBh8v0T0iCG/eNQjlVSboamqhCvCDj8x5Hx5X3uAb91NS+PvanaMIqO/wXOkgpKkD/bHsf9kOJ2989pa+KKqotunzwTWaPD/8eXr5ich1uFaXF4lSBaBPjArXJoSjT4wKUSpFk3WIrNzhBq9WytErMhiDuodBX+O89clgrLO7vabW8SObfbllMJjqsHBDFrSGK+uDcY2mK+HPHne4Nprj6eUnItdhi48Xs/dICXDPG7y6mSHUjvbrqp0Hpot6o90+H1Jfo8mTrg17PL38ROQ6DD5ezlNu8FEqBUYlaex2WB2VpEFUg/XJGlIFOL+E5b71jZr2+nxIfY0mT7k2HPH08hORazD4SIAn3OAdLsmRpMEyJ3/BhwXJMTIxwmbpC6sRiRHILKwAwD4fjnjCteGMp5efiLoegw+5jdjQQLzbzF/w9mbqfe32AXh2k+3kjSMSI3D/iAQ8vj6TfT6IiEjE4ENuxdlf8I5m6n19SjL+ftcglBtMOFdeDQDILKzA4+szHS5ZwaUOiIikiTM3N+CpMzdLQUtn6rUGGmd9PrjUARGRd+HMzeR1WjpTr70Wo4atO8EKPxw8U45DZ8qbnEMK63QREUkd5/Ehj9DWmXrPlRtwvEiH7POVKDeY8fUvRUg7UYJ3pqY0WZ3eGqBIOrQGE/Iu6JFZUI68i3qb+Z6IyDuxxYc8Qltm6j17yYCFG7NsRnyNStTgyfG98eHuXMwcmdBktmgudSAdfORJJE0MPuQRWrrMhPWxVp0g4JUtx5sMc9+bWwoBAp6Z0AeX7LTucNi7NGgNpiahB+AjT6LO5C6DShh8yCM0N1MvAJwurcLzm+uHtX88fajN8PaG0nPL8EhNLdRK25DDYe/SwdXdibqWO7WwMviQx3A0U6/BVIdvj5Ug7UQJBnYPw4wRCVDKnV/a2ur6vzisuNSBtHB1d6Ku424trAw+5JEEAJDVL1L6/NfHcO+weNz7h3isSs/Huzty8fH0oU5fr/DzgdFch42PDEeAvy+CFH5NOju7E3dpIvYWXN2dqOu4Wwsrgw95DHtNpaOSNJh+XQ+EBcnx9/+dEvv0ZBZWYERihN2V261LWYzoFYF9eWViB2d36djaMOSoA/0h9/XBok1H3aKJ2Fu0tM8YEbWfu7Wwcjg7eQRHTaV7c0qxel8+5H4+Nn16VqXn4/4RCRiRGGFzvHUpixNFWuzLK0NKXKi4z9rs6sohzUUV1ZizPhNj39qN29//ERszz2HBRsdNxBx+3TbWPmOpSRqb7XzkSdTx3K2FlS0+5BGcNZXuyy2DvqbWZpvBVIfH12di5sgEzLzc58dgqkVmYQU+PXAG9wyLx+PrM/H3OwfavM6VHVvthbuUuNAmQ+6t2Am3fbi6O1HXcLcWVgYf8gjNNZXa659jMNWJoWHLYyNQbjCJLTyPr8+EwVQHhV/TRk9XdWy1F+6MtRanr2En3Pbh6u5Ena+5Ubld/TvI4ENuxVEn3uaaSgP8fe326VHKffH8rX1hNNcHCJlMJu6z9vVpzFUdW+2FO3vBrCF2wiUiT+BOLawMPuQ2nM3z0FxTqVLui8duSAIAMfwo5b74ePpQvL8zF3s3HROPH5EYgY+nD0WN2YLZnx5uci5XdWy1F+6cddJmJ1wi8iTu0sLKzs3kFpqb5wGA086oMaGBiA9XYmJybH3YmTYYnz30h/rQ0yg07Mstw/u78lCqN8JgqmtyLlf9YlrDXUPWTtojG3XSdnVZiYg8lUwQBMHVhWjO6dOn8corr2DHjh0oKSlBbGws7r33Xjz77LOQy+XiMQkJCU1em5GRgT/84Q8t+jmtWdaeOlbeBT3GvrXb4f7t80ejV2QwzutqUF5lgq6mFqpAP4Qp5YhSBYjHWR+VVdaYEeDviwn/3OvwnGnzUuEjk7m82bWhoopqm+fgSrkvXvrjNRgaH4Zqcx0MpjqoA/0RGaJweVmJiNxFa+7fHvGo69SpU7BYLPjwww+RmJiIY8eOYdasWaiqqsLf//53m2N/+OEHXHPNNeL3ERERjU9Hbqgl8zy0ZMrzhk2pmQXlTs9ZZazFoO5h7Sx5x2r4HLzKaIYqUI7nNx/D019licdY37Na6cKCEhF5KI8IPhMmTMCECRPE73v27Ins7Gx88MEHTYJPREQEoqOju7qI1E7NdV4OUvi1espzd5s7oqWs4U1rMGHO+kzszXWPad6JiLyBx/bx0Wq1CA8Pb7L9j3/8IyIjIzFy5Eh88803Ts9hNBqh0+lsvsg17PVvsUpN0kDu69PslOetPae7dwxuyTTvRETUOh4ZfHJzc7F8+XL83//9n7gtODgYb775Jr788kv897//xciRIzF58mSn4WfJkiVQq9XiV1xcXFcUn+xobibdimrnN3l789l4+uy87jbNOxGRN3Bp5+aFCxfi9ddfd3rMyZMn0adPH/H7c+fOYfTo0RgzZgz+9a9/OX3tfffdh/z8fOzda7+Dq9FohNFoFL/X6XSIi4tj52YXatg5uWGH45Z2fm7NOd1de94zEZGUeEzn5ieffBIzZsxwekzPnj3FfxcVFeH666/Hddddh5UrVzZ7/mHDhiEtLc3hfoVCAYVC0eLyujNvWb3b0TwP7Zny3F3mjmgtd5vmnYjIG7g0+HTr1g3dunVr0bHnzp3D9ddfjyFDhmD16tXw8Wn+Kd2RI0cQExPT3mK6vZaMdvJ07jbleVfo7PfsLWGZiKg1PGIen3PnzmHMmDGIj4/H2rVr4et7ZV0m6wiutWvXQi6XIyUlBQCwceNGPP/88/jXv/6F+++/v0U/xxPn8RFH/jhoFfC2kT+e+tiqPRy95/YEFymEZSKSDo951NVSaWlpyM3NRW5uLq6++mqbfQ1z2yuvvIIzZ87Az88Pffr0weeff44//elPXV3cLtWSkT/eFAw89bFVe9h7z+0JLs3Nku1tYZmIqCGPGNU1Y8YMCIJg98tq+vTpOHHiBKqqqqDVanHgwAGvDz0AR/5IUXPBRWtwPgKOw+SJSMo8IviQY546SR+1XXuDC8MyEUkZg4+H8/RJ+qj12htcGJaJSMo8oo8POSbF0U5S197gogmW48a+kegdo0JKXCiMtRYE+PvicEE5sot1DMtE5NUYfLxAw4UtpTTaSaraO7+PWinH8xP7YdGmo3h3R664fWRiBF67fQCvGyLyanzU5SXUSjl6RQZjUPcw9IoM5s3Li7V3KQ6twYRnNx/Dvtwym+3puWV4bvOxZjtHExF5Mrb4EHmg1rbyNZzzJ1Dui4FxoTh0phwGU53Ncd44BQIRUUMMPkQeqqVzGtmb82dEYgTemZqCx9dnNgk/HNVFRN6Mj7qIvJijOX/25ZZh9b58zByZ0OQ1HNVFRN6MwYfIizmb82dfbhlS4kJttnEKBCLydnzURR6FC2u2TnNz/hhrLeK/OQUCEUkBgw95DC6s2XrNzfnTUxOEzY9exykQiEgy+KiLPEJ716eSquZm9o5RB3AKBCKSFAYf8ghcWLNt2jvnDxGRt+GjLvIIXFiz7TizNxHRFQw+5BG4sGb7tHTOHyIib8dHXeQRuAo9ERF1BAYf8gjsq0JERB2Bj7rIY7CvChERtReDD3kU9lUhIqL24KMuIiIikgwGHyIiIpIMBh8iIiKSDAYfIiIikgwGHyIiIpIMBh8iIiKSDAYfIiIikgzO40NE1IjWYEKp3gRdjRmqQH9ogjh/FJG3YPAhImqgqKIaCzZkYW9OqbgtNUmDpVOSERsa6MKSEVFH4KMuIqLLtAZTk9ADAHtySrFwQxa0BpOLSkZEHYXBh4joslK9qUnosdqTU4pSPYMPkadj8CEiukxXY3a6v7KZ/UTk/hh8iIguUwX4O90f0sx+InJ/DD5ERJdpguVITdLY3ZeapIEmmCO7iDydxwSfHj16QCaT2XwtXbrU5pisrCyMGjUKAQEBiIuLw7Jly1xUWiLyRGqlHEunJDcJP6lJGrw+JZlD2om8gEcNZ3/55Zcxa9Ys8fuQkBDx3zqdDjfddBPGjRuHFStW4OjRo5g5cyZCQ0Px0EMPuaK4ROSBYkMDsXxqCkr1JlTWmBES4A9NMOfxIfIWHhV8QkJCEB0dbXffunXrYDKZsGrVKsjlclxzzTU4cuQI3nrrLQYfImoVtZJBh8hbecyjLgBYunQpIiIikJKSgjfeeAO1tbXivoyMDKSmpkIuv/JhNX78eGRnZ6O8vNzu+YxGI3Q6nc0XEREReS+PafF5/PHHMXjwYISHh+PHH3/EokWLUFxcjLfeegsAUFJSgoSEBJvXREVFifvCwsKanHPJkiV46aWXOr/wRERE5BZc2uKzcOHCJh2WG3+dOnUKADB//nyMGTMGycnJePjhh/Hmm29i+fLlMBqNbf75ixYtglarFb8KCws76q0RERGRG3Jpi8+TTz6JGTNmOD2mZ8+edrcPGzYMtbW1OH36NHr37o3o6GicP3/e5hjr9476BSkUCigUitYXnIiIiDySS4NPt27d0K1btza99siRI/Dx8UFkZCQAYPjw4Xj22WdhNpvh718/yVhaWhp69+5t9zEXERERSY9HdG7OyMjA22+/jV9++QW//fYb1q1bh3nz5uHee+8VQ80999wDuVyOBx54AMePH8fnn3+Of/7zn5g/f76LS09ERETuwiM6NysUCnz22Wd48cUXYTQakZCQgHnz5tmEGrVaje+//x6zZ8/GkCFDoNFosHjxYg5lJyIiIpFMEATB1YVwFzqdDmq1GlqtFiqVytXFISIiohZozf3bIx51EREREXUEBh8iIiKSDAYfIiIikgwGHyIiIpIMBh8iIiKSDAYfIiIikgwGHyIiIpIMBh8iIiKSDAYfIiIikgwGHyIiIpIMBh8iIiKSDI9YpJSIqCtoDSaU6k3Q1ZihCvSHJkgOtVLu6mIRUQdi8CEiAlBUUY0FG7KwN6dU3JaapMHSKcmIDQ10YcmIqCPxURcRSZ7WYGoSegBgT04pFm7IgtZgclHJiKijMfgQkeSV6k1NQo/VnpxSlOoZfIi8BYMPEUmersbsdH9lM/uJyHMw+BCR5KkC/J3uD2lmPxF5DgYfIpI8TbAcqUkau/tSkzTQBHNkF5G3YPAhIslTK+VYOiW5SfhJTdLg9SnJHNJO5EU4nJ2ICEBsaCCWT01Bqd6EyhozQgL8oQnmPD5E3obBh4joMrWSQYfI2/FRFxEREUkGgw8RERFJBoMPERERSQaDDxEREUkGgw8RERFJBoMPERERSQaDDxEREUkGgw8RERFJBoMPERERSQaDDxEREUkGl6xoQBAEAIBOp3NxSYiIiKilrPdt633cGQafBiorKwEAcXFxLi4JERERtVZlZSXUarXTY2RCS+KRRFgsFhQVFSEkJAQymczVxXF7Op0OcXFxKCwshEqlcnVxvAbrtXOwXjsH67VzsF5bRxAEVFZWIjY2Fj4+znvxsMWnAR8fH1x99dWuLobHUalU/MXsBKzXzsF67Rys187Bem255lp6rNi5mYiIiCSDwYeIiIgkg8GH2kyhUOCFF16AQqFwdVG8Cuu1c7BeOwfrtXOwXjsPOzcTERGRZLDFh4iIiCSDwYeIiIgkg8GHiIiIJIPBh4iIiCSDwYecevHFFyGTyWy++vTpI+6vqanB7NmzERERgeDgYEyZMgXnz593YYnd0549ezBp0iTExsZCJpNh8+bNNvsFQcDixYsRExODwMBAjBs3Djk5OTbHXLp0CdOmTYNKpUJoaCgeeOAB6PX6LnwX7qe5ep0xY0aT63fChAk2x7Bem1qyZAl+//vfIyQkBJGRkZg8eTKys7NtjmnJ735BQQFuvfVWKJVKREZG4umnn0ZtbW1XvhW30pJ6HTNmTJNr9uGHH7Y5hvXaPgw+1KxrrrkGxcXF4ld6erq4b968ediyZQu+/PJL7N69G0VFRbjjjjtcWFr3VFVVhYEDB+K9996zu3/ZsmV45513sGLFChw4cABBQUEYP348ampqxGOmTZuG48ePIy0tDVu3bsWePXvw0EMPddVbcEvN1SsATJgwweb6Xb9+vc1+1mtTu3fvxuzZs7F//36kpaXBbDbjpptuQlVVlXhMc7/7dXV1uPXWW2EymfDjjz9i7dq1WLNmDRYvXuyKt+QWWlKvADBr1iyba3bZsmXiPtZrBxCInHjhhReEgQMH2t1XUVEh+Pv7C19++aW47eTJkwIAISMjo4tK6HkACJs2bRK/t1gsQnR0tPDGG2+I2yoqKgSFQiGsX79eEARBOHHihABA+Pnnn8VjvvvuO0Emkwnnzp3rsrK7s8b1KgiCMH36dOG2225z+BrWa8tcuHBBACDs3r1bEISW/e5/++23go+Pj1BSUiIe88EHHwgqlUowGo1d+wbcVON6FQRBGD16tDB37lyHr2G9th9bfKhZOTk5iI2NRc+ePTFt2jQUFBQAAA4dOgSz2Yxx48aJx/bp0wfdu3dHRkaGq4rrcfLz81FSUmJTj2q1GsOGDRPrMSMjA6GhoRg6dKh4zLhx4+Dj44MDBw50eZk9ya5duxAZGYnevXvjkUceQVlZmbiP9doyWq0WABAeHg6gZb/7GRkZGDBgAKKiosRjxo8fD51Oh+PHj3dh6d1X43q1WrduHTQaDfr3749FixbBYDCI+1iv7cdFSsmpYcOGYc2aNejduzeKi4vx0ksvYdSoUTh27BhKSkogl8sRGhpq85qoqCiUlJS4psAeyFpXDT/IrN9b95WUlCAyMtJmv5+fH8LDw1nXTkyYMAF33HEHEhISkJeXh7/+9a+4+eabkZGRAV9fX9ZrC1gsFjzxxBMYMWIE+vfvDwAt+t0vKSmxe01b90mdvXoFgHvuuQfx8fGIjY1FVlYWFixYgOzsbGzcuBEA67UjMPiQUzfffLP47+TkZAwbNgzx8fH44osvEBgY6MKSETXvz3/+s/jvAQMGIDk5Gb169cKuXbswduxYF5bMc8yePRvHjh2z6dtH7eeoXhv2LxswYABiYmIwduxY5OXloVevXl1dTK/ER13UKqGhofjd736H3NxcREdHw2QyoaKiwuaY8+fPIzo62jUF9EDWumo8IqZhPUZHR+PChQs2+2tra3Hp0iXWdSv07NkTGo0Gubm5AFivzZkzZw62bt2KnTt34uqrrxa3t+R3Pzo62u41bd0nZY7q1Z5hw4YBgM01y3ptHwYfahW9Xo+8vDzExMRgyJAh8Pf3x/bt28X92dnZKCgowPDhw11YSs+SkJCA6Ohom3rU6XQ4cOCAWI/Dhw9HRUUFDh06JB6zY8cOWCwW8YORmnf27FmUlZUhJiYGAOvVEUEQMGfOHGzatAk7duxAQkKCzf6W/O4PHz4cR48etQmWaWlpUKlU6NevX9e8ETfTXL3ac+TIEQCwuWZZr+3k6t7V5N6efPJJYdeuXUJ+fr6wb98+Ydy4cYJGoxEuXLggCIIgPPzww0L37t2FHTt2CAcPHhSGDx8uDB8+3MWldj+VlZVCZmamkJmZKQAQ3nrrLSEzM1M4c+aMIAiCsHTpUiE0NFT4+uuvhaysLOG2224TEhIShOrqavEcEyZMEFJSUoQDBw4I6enpQlJSkjB16lRXvSW34KxeKysrhaeeekrIyMgQ8vPzhR9++EEYPHiwkJSUJNTU1IjnYL029cgjjwhqtVrYtWuXUFxcLH4ZDAbxmOZ+92tra4X+/fsLN910k3DkyBFh27ZtQrdu3YRFixa54i25hebqNTc3V3j55ZeFgwcPCvn5+cLXX38t9OzZU0hNTRXPwXptPwYfcuruu+8WYmJiBLlcLlx11VXC3XffLeTm5or7q6urhUcffVQICwsTlEqlcPvttwvFxcUuLLF72rlzpwCgydf06dMFQagf0v78888LUVFRgkKhEMaOHStkZ2fbnKOsrEyYOnWqEBwcLKhUKuH+++8XKisrXfBu3IezejUYDMJNN90kdOvWTfD39xfi4+OFWbNm2QwDFgTWqz326hSAsHr1avGYlvzunz59Wrj55puFwMBAQaPRCE8++aRgNpu7+N24j+bqtaCgQEhNTRXCw8MFhUIhJCYmCk8//bSg1WptzsN6bR+ZIAhC17UvEREREbkO+/gQERGRZDD4EBERkWQw+BAREZFkMPgQERGRZDD4EBERkWQw+BAREZFkMPgQERGRZDD4EBERkWQw+BCRW5gxYwYmT54sfj9mzBg88cQTXV6OXbt2QSaTNVmAsyOdPn0aMplMXIeJiLoOgw8ROTRjxgzIZDLIZDLI5XIkJibi5ZdfRm1tbaf/7I0bN+KVV15p0bFdEVaIyDv4uboAROTeJkyYgNWrV8NoNOLbb7/F7Nmz4e/vj0WLFjU51mQyQS6Xd8jPDQ8P75DzEBE1xBYfInJKoVAgOjoa8fHxeOSRRzBu3Dh88803AK48nnr11VcRGxuL3r17AwAKCwtx1113ITQ0FOHh4bjttttw+vRp8Zx1dXWYP38+QkNDERERgWeeeQaNlw1s/KjLaDRiwYIFiIuLg0KhQGJiIj7++GOcPn0a119/PQAgLCwMMpkMM2bMAABYLBYsWbIECQkJCAwMxMCBA/HVV1/Z/Jxvv/0Wv/vd7xAYGIjrr7/eppz23HPPPbj77rtttpnNZmg0GnzyyScAgG3btmHkyJHi+5s4cSLy8vIcnnPNmjUIDQ212bZ582bIZDKbbV9//TUGDx6MgIAA9OzZEy+99FKXtL4ReRMGHyJqlcDAQJhMJvH77du3Izs7G2lpadi6dSvMZjPGjx+PkJAQ7N27F/v27UNwcDAmTJggvu7NN9/EmjVrsGrVKqSnp+PSpUvYtGmT05973333Yf369XjnnXdw8uRJfPjhhwgODkZcXBw2bNgAAMjOzkZxcTH++c9/AgCWLFmCTz75BCtWrMDx48cxb9483Hvvvdi9ezeA+oB2xx13YNKkSThy5AgefPBBLFy40Gk5pk2bhi1btkCv14vb/ve//8FgMOD2228HAFRVVWH+/Pk4ePAgtm/fDh8fH9x+++2wWCytrO0r9u7di/vuuw9z587FiRMn8OGHH2LNmjV49dVX23xOIkly8erwROTGpk+fLtx2222CIAiCxWIR0tLSBIVCITz11FPi/qioKMFoNIqv+fe//y307t1bsFgs4jaj0SgEBgYK//vf/wRBEISYmBhh2bJl4n6z2SxcffXV4s8SBEEYPXq0MHfuXEEQBCE7O1sAIKSlpdkt586dOwUAQnl5ubitpqZGUCqVwo8//mhz7AMPPCBMnTpVEARBWLRokdCvXz+b/QsWLGhyrobMZrOg0WiETz75RNw2depU4e6777Z7vCAIwsWLFwUAwtGjRwVBEIT8/HwBgJCZmSkIgiCsXr1aUKvVNq/ZtGmT0PAjeuzYscJrr71mc8y///1vISYmxuHPJaKm2MeHiJzaunUrgoODYTabYbFYcM899+DFF18U9w8YMMCmX88vv/yC3NxchISE2JynpqYGeXl50Gq1KC4uxrBhw8R9fn5+GDp0aJPHXVZHjhyBr68vRo8e3eJy5+bmwmAw4MYbb7TZbjKZkJKSAgA4efKkTTkAYPjw4U7P6+fnh7vuugvr1q3DX/7yF1RVVeHrr7/GZ599Jh6Tk5ODxYsX48CBAygtLRVbegoKCtC/f/8Wv4eGfvnlF+zbt8+mhaeurg41NTUwGAxQKpVtOi+R1DD4EJFT119/PT744API5XLExsbCz8/2YyMoKMjme71ejyFDhmDdunVNztWtW7c2lSEwMLDVr7E+ivrvf/+Lq666ymafQqFoUzmspk2bhtGjR+PChQtIS0tDYGAgJkyYIO6fNGkS4uPj8dFHHyE2NhYWiwX9+/e3eUTYkI+PT5PQZzabm7yfl156CXfccUeT1wcEBLTr/RBJCYMPETkVFBSExMTEFh8/ePBgfP7554iMjIRKpbJ7TExMDA4cOIDU1FQAQG1tLQ4dOoTBgwfbPX7AgAGwWCzYvXs3xo0b12S/tcWprq5O3NavXz8oFAoUFBQ4bCnq27ev2FHbav/+/c2+x+uuuw5xcXH4/PPP8d133+HOO++Ev78/AKCsrAzZ2dn46KOPMGrUKABAenq60/N169YNlZWVqKqqEoNk4zl+Bg8ejOzs7Fb9XxBRU+zcTEQdatq0adBoNLjtttuwd+9e5OfnY9euXXj88cdx9uxZAMDcuXOxdOlSbN68GadOncKjjz7qdA6eHj16YPr06Zg5cyY2b94snvOLL74AAMTHx0Mmk2Hr1q24ePEi9Ho9QkJC8NRTT2HevHlYu3Yt8vLycPjwYSxfvhxr164FADz88MPIycnB008/jezsbHz66adYs2ZNi97nPffcgxUrViAtLQ3Tpk0Tt4eFhSEiIgIrV65Ebm4uduzYgfnz5zs917Bhw6BUKvHXv/4VeXl5dsuxePFifPLJJ3jppZdw/PhxnDx5Ep999hmee+65FpWXiC5zdScjInJfDTs3t2Z/cXGxcN999wkajUZQKBRCz549hVmzZglarVYQhPoOwnPnzhVUKpUQGhoqzJ8/X7jvvvscdm4WBEGorq4W5s2bJ8TExAhyuVxITEwUVq1aJe5/+eWXhejoaEEmkwnTp08XBKG+Q/bbb78t9O7dW/D39xe6desmjB8/Xti9e7f4ui1btgiJiYmCQqEQRo0aJaxatcpp52arEydOCACE+Ph4m47cgiAIaWlpQt++fQWFQiEkJycLu3btEgAImzZtEgShaedmQajvzJyYmCgEBgYKEydOFFauXCk0/ojetm2bcN111wmBgYGCSqUSrr32WmHlypVOy0lEtmSC4KA3IREREZGX4aMuIiIikgwGHyIiIpIMBh8iIiKSDAYfIiIikgwGHyIiIpIMBh8iIiKSDAYfIiIikgwGHyIiIpIMBh8iIiKSDAYfIiIikgwGHyIiIpKM/wfqRsHBoq1vNAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "residuals = pd.DataFrame({'Residual': model.resid, 'Predicted value': model.predict()})\n",
-    "ax = sns.scatterplot(residuals, y='Residual', x='Predicted value')\n",
-    "ax.axhline(0, linestyle=':', linewidth=1);"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "aa11ead0",
+   "id": "45574c5f",
    "metadata": {
     "hidden": true
    },
@@ -2275,17 +2369,17 @@
   },
   {
    "cell_type": "markdown",
-   "id": "556b852a",
+   "id": "94cb7b0a",
    "metadata": {},
    "source": [
     "## Q\n",
     "\n",
-    "Plot the density of `Fare` for first-class passengers and overlay a fitted distribution function from the exponential family."
+    "Plot the density of `Fare` for first-class passengers and overlay a fitted distribution function from the exponential family. `scipy.stats.invgauss` and `scipy.stats.gamma` may be useful here."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "5c7e48ea",
+   "id": "9b31306d",
    "metadata": {
     "heading_collapsed": true
    },
@@ -2295,8 +2389,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1123,
-   "id": "2edf81b9",
+   "execution_count": 64,
+   "id": "d2ec65b5",
    "metadata": {
     "hidden": true
    },
@@ -2329,7 +2423,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "fec96b60",
+   "id": "a16c3246",
    "metadata": {
     "hidden": true
    },
@@ -2338,7 +2432,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "af2b537e",
+   "id": "6e8d2e6b",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -2350,7 +2444,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "ecc8cb21",
+   "id": "0f7a8edc",
    "metadata": {
     "heading_collapsed": true
    },
@@ -2360,8 +2454,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1080,
-   "id": "ed8726e1",
+   "execution_count": 65,
+   "id": "e58c6f4c",
    "metadata": {
     "hidden": true
    },
@@ -2390,7 +2484,7 @@
        "  <th>Date:</th>            <td>Mon, 26 Sep 2022</td> <th>  Deviance:          </th> <td> 0.29921</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>                <td>01:10:16</td>     <th>  Pearson chi2:      </th>  <td> 0.285</td>  \n",
+       "  <th>Time:</th>                <td>16:49:53</td>     <th>  Pearson chi2:      </th>  <td> 0.285</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>No. Iterations:</th>         <td>34</td>        <th>  Pseudo R-squ. (CS):</th>  <td>0.9871</td>  \n",
@@ -2449,7 +2543,7 @@
        "Link Function:                    log   Scale:                       0.0016691\n",
        "Method:                          IRLS   Log-Likelihood:                -725.75\n",
        "Date:                Mon, 26 Sep 2022   Deviance:                      0.29921\n",
-       "Time:                        01:10:16   Pearson chi2:                    0.285\n",
+       "Time:                        16:49:53   Pearson chi2:                    0.285\n",
        "No. Iterations:                    34   Pseudo R-squ. (CS):             0.9871\n",
        "Covariance Type:            nonrobust                                         \n",
        "====================================================================================\n",
@@ -2470,7 +2564,7 @@
        "\"\"\""
       ]
      },
-     "execution_count": 1080,
+     "execution_count": 65,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2482,8 +2576,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1081,
-   "id": "7ecad003",
+   "execution_count": 66,
+   "id": "c9767999",
    "metadata": {
     "hidden": true
    },
@@ -2725,7 +2819,7 @@
        "E-D   0.958609      False  "
       ]
      },
-     "execution_count": 1081,
+     "execution_count": 66,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2734,19 +2828,9 @@
     "model.t_test_pairwise('C(Deck)').result_frame"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c239b5f3",
-   "metadata": {
-    "hidden": true
-   },
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "markdown",
-   "id": "a27f7b48",
+   "id": "a7c01894",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -2756,7 +2840,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "562b2ee0",
+   "id": "e72dd608",
    "metadata": {
     "heading_collapsed": true
    },
@@ -2766,15 +2850,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1082,
-   "id": "0ffbb960",
+   "execution_count": 72,
+   "id": "5fdcbbd8",
    "metadata": {
     "hidden": true
    },
    "outputs": [],
    "source": [
     "deck = firstclass['Deck']\n",
-    "for d in 'ABC':\n",
+    "for d in ['A', 'B', 'C']:\n",
     "    firstclass.loc[deck==d, 'Deck'] = 'ABC'\n",
     "for d in 'DE':\n",
     "    firstclass.loc[deck==d, 'Deck'] = 'DE'"
@@ -2782,8 +2866,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1083,
-   "id": "543ada9d",
+   "execution_count": 73,
+   "id": "7e1e4b40",
    "metadata": {
     "hidden": true
    },
@@ -2812,7 +2896,7 @@
        "  <th>Date:</th>            <td>Mon, 26 Sep 2022</td> <th>  Deviance:          </th> <td> 0.30293</td> \n",
        "</tr>\n",
        "<tr>\n",
-       "  <th>Time:</th>                <td>01:10:17</td>     <th>  Pearson chi2:      </th>  <td> 0.291</td>  \n",
+       "  <th>Time:</th>                <td>16:56:30</td>     <th>  Pearson chi2:      </th>  <td> 0.291</td>  \n",
        "</tr>\n",
        "<tr>\n",
        "  <th>No. Iterations:</th>         <td>33</td>        <th>  Pseudo R-squ. (CS):</th>  <td>0.9868</td>  \n",
@@ -2862,7 +2946,7 @@
        "Link Function:                    log   Scale:                       0.0016739\n",
        "Method:                          IRLS   Log-Likelihood:                -726.86\n",
        "Date:                Mon, 26 Sep 2022   Deviance:                      0.30293\n",
-       "Time:                        01:10:17   Pearson chi2:                    0.291\n",
+       "Time:                        16:56:30   Pearson chi2:                    0.291\n",
        "No. Iterations:                    33   Pseudo R-squ. (CS):             0.9868\n",
        "Covariance Type:            nonrobust                                         \n",
        "====================================================================================\n",
@@ -2880,7 +2964,7 @@
        "\"\"\""
       ]
      },
-     "execution_count": 1083,
+     "execution_count": 73,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2892,8 +2976,8 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1084,
-   "id": "148277f8",
+   "execution_count": 74,
+   "id": "ebc787b2",
    "metadata": {
     "hidden": true
    },
@@ -2979,7 +3063,7 @@
        "DE-ABC        -0.031936   0.028389       True  "
       ]
      },
-     "execution_count": 1084,
+     "execution_count": 74,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2991,7 +3075,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "98447386",
+   "id": "625feb31",
    "metadata": {
     "hidden": true
    },
@@ -3000,7 +3084,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9ce08870",
+   "id": "36556c9e",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -3012,7 +3096,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24b92142",
+   "id": "b7706819",
    "metadata": {
     "heading_collapsed": true
    },
@@ -3022,12 +3106,33 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "71e87548",
+   "execution_count": 24,
+   "id": "63983757",
    "metadata": {
     "hidden": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'Fare ~ C(Embarked) + C(Deck) + Cabins + Passengers + Children': 1469.7224530524886,\n",
+       " 'Fare ~ C(Embarked) * C(Deck) + Cabins + Passengers + Children': 1472.8570267766695,\n",
+       " 'Fare ~ C(Embarked) * Cabins + C(Deck) + Passengers + Children': 1450.589879261779,\n",
+       " 'Fare ~ C(Embarked) * Passengers + C(Deck) + Cabins + Children': 1466.6673025135624,\n",
+       " 'Fare ~ C(Embarked) * Children + C(Deck) + Cabins + Passengers': 1471.730470133521,\n",
+       " 'Fare ~ C(Deck) * Cabins + C(Embarked) + Passengers + Children': 1471.7331290112245,\n",
+       " 'Fare ~ C(Deck) * Passengers + C(Embarked) + Cabins + Children': 1472.4105103002053,\n",
+       " 'Fare ~ C(Deck) * Children + C(Embarked) + Cabins + Passengers': 1471.7304701335215,\n",
+       " 'Fare ~ Cabins * Passengers + C(Embarked) + C(Deck) + Children': 1442.7498384491118,\n",
+       " 'Fare ~ Cabins * Children + C(Embarked) + C(Deck) + Passengers': 1471.6186668619553,\n",
+       " 'Fare ~ Passengers * Children + C(Embarked) + C(Deck) + Cabins': 1470.8386820677097}"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "model_spec = 'Fare ~ C(Embarked) + C(Deck) + Cabins + Passengers + Children'\n",
     "model_aic = {model_spec: model.aic}\n",
@@ -3051,12 +3156,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "67fe2f97",
+   "execution_count": 25,
+   "id": "173f5ca5",
    "metadata": {
     "hidden": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'Fare ~ C(Embarked) * C(Deck) + Cabins * Passengers + Children': 1446.202974050631,\n",
+       " 'Fare ~ C(Embarked) * Cabins * Passengers + C(Deck) + Children': 1399.9999464641298,\n",
+       " 'Fare ~ C(Embarked) * Children + C(Deck) + Cabins * Passengers': 1440.048662430043,\n",
+       " 'Fare ~ C(Deck) * Cabins * Passengers + C(Embarked) + Children': 1432.1006575382407,\n",
+       " 'Fare ~ C(Deck) * Children + C(Embarked) + Cabins * Passengers': 1440.0486624300434,\n",
+       " 'Fare ~ Cabins * Passengers * Children + C(Embarked) + C(Deck)': 1437.8075309435865}"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "terms = ['C(Embarked)', 'C(Deck)', 'Cabins * Passengers', 'Children']\n",
     "explore_1level({}, terms)"
@@ -3064,12 +3185,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "34b28cdc",
+   "execution_count": 26,
+   "id": "487aa1b3",
    "metadata": {
     "hidden": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'Fare ~ C(Embarked) * Cabins * Passengers * C(Deck) + Children': 1416.4827989888995,\n",
+       " 'Fare ~ C(Embarked) * Cabins * Passengers * Children + C(Deck)': 1403.1712552041527,\n",
+       " 'Fare ~ C(Deck) * Children + C(Embarked) * Cabins * Passengers': 1402.1020940398735}"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "terms = ['C(Embarked) * Cabins * Passengers', 'C(Deck)', 'Children']\n",
     "explore_1level({}, terms)"
@@ -3077,7 +3211,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "af0edee7",
+   "id": "89bfc75b",
    "metadata": {},
    "source": [
     "## Q\n",
@@ -3090,7 +3224,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e6f1a428",
+   "id": "e596ffca",
    "metadata": {
     "heading_collapsed": true
    },
@@ -3100,12 +3234,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "62b235cf",
+   "execution_count": 81,
+   "id": "6102bdce",
    "metadata": {
     "hidden": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'Fare ~ C(Embarked) + C(Deck) + Cabins + Passengers + Children': 1469.7224530524886,\n",
+       " 'Fare ~ C(Embarked) * C(Deck) + Cabins + Passengers + Children': 1472.8570267766695,\n",
+       " 'Fare ~ C(Embarked) * Cabins + C(Deck) + Passengers + Children': 1450.589879261779,\n",
+       " 'Fare ~ C(Embarked) * Passengers + C(Deck) + Cabins + Children': 1466.6673025135624,\n",
+       " 'Fare ~ C(Embarked) * Children + C(Deck) + Cabins + Passengers': 1471.730470133521,\n",
+       " 'Fare ~ C(Deck) * Cabins + C(Embarked) + Passengers + Children': 1471.7331290112245,\n",
+       " 'Fare ~ C(Deck) * Passengers + C(Embarked) + Cabins + Children': 1472.4105103002053,\n",
+       " 'Fare ~ C(Deck) * Children + C(Embarked) + Cabins + Passengers': 1471.7304701335215,\n",
+       " 'Fare ~ Cabins * Passengers + C(Embarked) + C(Deck) + Children': 1442.7498384491118,\n",
+       " 'Fare ~ Cabins * Children + C(Embarked) + C(Deck) + Passengers': 1471.6186668619553,\n",
+       " 'Fare ~ Passengers * Children + C(Embarked) + C(Deck) + Cabins': 1470.8386820677097,\n",
+       " 'Fare ~ C(Embarked) * C(Deck) + Cabins * Passengers + Children': 1446.202974050631,\n",
+       " 'Fare ~ C(Embarked) * Cabins * Passengers + C(Deck) + Children': 1399.9999464641298,\n",
+       " 'Fare ~ C(Embarked) * Children + C(Deck) + Cabins * Passengers': 1440.048662430043,\n",
+       " 'Fare ~ C(Deck) * Cabins * Passengers + C(Embarked) + Children': 1432.1006575382407,\n",
+       " 'Fare ~ C(Deck) * Children + C(Embarked) + Cabins * Passengers': 1440.0486624300434,\n",
+       " 'Fare ~ Cabins * Passengers * Children + C(Embarked) + C(Deck)': 1437.8075309435865,\n",
+       " 'Fare ~ C(Embarked) * Cabins * Passengers * C(Deck) + Children': 1416.4827989888995,\n",
+       " 'Fare ~ C(Embarked) * Cabins * Passengers * Children + C(Deck)': 1403.1712552041527,\n",
+       " 'Fare ~ C(Deck) * Children + C(Embarked) * Cabins * Passengers': 1402.1020940398735}"
+      ]
+     },
+     "execution_count": 81,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "model_spec = 'Fare ~ C(Embarked) + C(Deck) + Cabins + Passengers + Children'\n",
     "model_aic = {model_spec: model.aic}\n",
@@ -3120,29 +3284,210 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "2d714cc2",
+   "execution_count": 82,
+   "id": "29b1f1d6",
    "metadata": {
     "hidden": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>models</th>\n",
+       "      <th>AIC</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Fare ~ C(Embarked) + C(Deck) + Cabins + Passen...</td>\n",
+       "      <td>1469.722453</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Fare ~ C(Embarked) * C(Deck) + Cabins + Passen...</td>\n",
+       "      <td>1472.857027</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Fare ~ C(Embarked) * Cabins + C(Deck) + Passen...</td>\n",
+       "      <td>1450.589879</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Fare ~ C(Embarked) * Passengers + C(Deck) + Ca...</td>\n",
+       "      <td>1466.667303</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Fare ~ C(Embarked) * Children + C(Deck) + Cabi...</td>\n",
+       "      <td>1471.730470</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Fare ~ C(Deck) * Cabins + C(Embarked) + Passen...</td>\n",
+       "      <td>1471.733129</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>Fare ~ C(Deck) * Passengers + C(Embarked) + Ca...</td>\n",
+       "      <td>1472.410510</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>Fare ~ C(Deck) * Children + C(Embarked) + Cabi...</td>\n",
+       "      <td>1471.730470</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Fare ~ Cabins * Passengers + C(Embarked) + C(D...</td>\n",
+       "      <td>1442.749838</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Fare ~ Cabins * Children + C(Embarked) + C(Dec...</td>\n",
+       "      <td>1471.618667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Fare ~ Passengers * Children + C(Embarked) + C...</td>\n",
+       "      <td>1470.838682</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>Fare ~ C(Embarked) * C(Deck) + Cabins * Passen...</td>\n",
+       "      <td>1446.202974</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>Fare ~ C(Embarked) * Cabins * Passengers + C(D...</td>\n",
+       "      <td>1399.999946</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>Fare ~ C(Embarked) * Children + C(Deck) + Cabi...</td>\n",
+       "      <td>1440.048662</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>Fare ~ C(Deck) * Cabins * Passengers + C(Embar...</td>\n",
+       "      <td>1432.100658</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>Fare ~ C(Deck) * Children + C(Embarked) + Cabi...</td>\n",
+       "      <td>1440.048662</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>Fare ~ Cabins * Passengers * Children + C(Emba...</td>\n",
+       "      <td>1437.807531</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>Fare ~ C(Embarked) * Cabins * Passengers * C(D...</td>\n",
+       "      <td>1416.482799</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>18</th>\n",
+       "      <td>Fare ~ C(Embarked) * Cabins * Passengers * Chi...</td>\n",
+       "      <td>1403.171255</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>19</th>\n",
+       "      <td>Fare ~ C(Deck) * Children + C(Embarked) * Cabi...</td>\n",
+       "      <td>1402.102094</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                               models          AIC\n",
+       "0   Fare ~ C(Embarked) + C(Deck) + Cabins + Passen...  1469.722453\n",
+       "1   Fare ~ C(Embarked) * C(Deck) + Cabins + Passen...  1472.857027\n",
+       "2   Fare ~ C(Embarked) * Cabins + C(Deck) + Passen...  1450.589879\n",
+       "3   Fare ~ C(Embarked) * Passengers + C(Deck) + Ca...  1466.667303\n",
+       "4   Fare ~ C(Embarked) * Children + C(Deck) + Cabi...  1471.730470\n",
+       "5   Fare ~ C(Deck) * Cabins + C(Embarked) + Passen...  1471.733129\n",
+       "6   Fare ~ C(Deck) * Passengers + C(Embarked) + Ca...  1472.410510\n",
+       "7   Fare ~ C(Deck) * Children + C(Embarked) + Cabi...  1471.730470\n",
+       "8   Fare ~ Cabins * Passengers + C(Embarked) + C(D...  1442.749838\n",
+       "9   Fare ~ Cabins * Children + C(Embarked) + C(Dec...  1471.618667\n",
+       "10  Fare ~ Passengers * Children + C(Embarked) + C...  1470.838682\n",
+       "11  Fare ~ C(Embarked) * C(Deck) + Cabins * Passen...  1446.202974\n",
+       "12  Fare ~ C(Embarked) * Cabins * Passengers + C(D...  1399.999946\n",
+       "13  Fare ~ C(Embarked) * Children + C(Deck) + Cabi...  1440.048662\n",
+       "14  Fare ~ C(Deck) * Cabins * Passengers + C(Embar...  1432.100658\n",
+       "15  Fare ~ C(Deck) * Children + C(Embarked) + Cabi...  1440.048662\n",
+       "16  Fare ~ Cabins * Passengers * Children + C(Emba...  1437.807531\n",
+       "17  Fare ~ C(Embarked) * Cabins * Passengers * C(D...  1416.482799\n",
+       "18  Fare ~ C(Embarked) * Cabins * Passengers * Chi...  1403.171255\n",
+       "19  Fare ~ C(Deck) * Children + C(Embarked) * Cabi...  1402.102094"
+      ]
+     },
+     "execution_count": 82,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "model_aic = pd.DataFrame(zip(model_aic.keys(), model_aic.values()), columns=['models', 'AIC'])"
+    "model_aic = pd.DataFrame(model_aic.items(), columns=['models', 'AIC'])\n",
+    "model_aic"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "id": "d7529481",
+   "execution_count": 30,
+   "id": "70bda649",
    "metadata": {
     "hidden": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
-    "ax = sns.stripplot(y='models', x='AIC', data=model_aic, size=10, orient=\"h\", jitter=False, palette=\"flare_r\", hue='models', linewidth=1, edgecolor=\"w\")\n",
+    "ax = sns.stripplot(y='models', x='AIC', data=model_aic, size=10, orient=\"h\", jitter=False, palette=\"flare_r\", hue='models', linewidth=1, edgecolor=\"w\", legend=False)\n",
     "ax.yaxis.grid(True)\n",
     "ax.yaxis.set_ticks_position('right');"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2f483181",
+   "metadata": {
+    "hidden": true
+   },
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {