bank_regression+testing.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import the relevant libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set()\n",
    "\n",
    "from scipy import stats\n",
    "stats.chisqprob = lambda chisq, df: stats.chi2.sf(chisq, df)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the ‘Bank_data.csv’ dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
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       "      <th>7</th>\n",
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       "      <td>4.858</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>8</td>\n",
       "      <td>4.962</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>704.0</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
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       "      <td>4.865</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>185.0</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>no</td>\n",
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       "      <th>11</th>\n",
       "      <td>11</td>\n",
       "      <td>0.773</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>yes</td>\n",
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       "      <th>12</th>\n",
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       "      <td>0.714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>169.0</td>\n",
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       "      <th>13</th>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>249.0</td>\n",
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       "      <th>14</th>\n",
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       "      <td>4.966</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>no</td>\n",
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       "      <th>15</th>\n",
       "      <td>15</td>\n",
       "      <td>0.904</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>324.0</td>\n",
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       "    <tr>\n",
       "      <th>16</th>\n",
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       "      <td>0.849</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>yes</td>\n",
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       "      <th>17</th>\n",
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       "      <td>1.811</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>18</td>\n",
       "      <td>1.264</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>337.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>19</td>\n",
       "      <td>4.076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>640.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>20</td>\n",
       "      <td>1.262</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>663.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>21</td>\n",
       "      <td>0.695</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>403.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>22</td>\n",
       "      <td>4.960</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>23</td>\n",
       "      <td>4.963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>255.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>24</td>\n",
       "      <td>1.354</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>25</td>\n",
       "      <td>1.244</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>26</td>\n",
       "      <td>0.748</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>266.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>27</td>\n",
       "      <td>0.878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>0.644</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>398.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>29</td>\n",
       "      <td>4.968</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>488</td>\n",
       "      <td>0.885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>608.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>489</td>\n",
       "      <td>4.153</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>490</td>\n",
       "      <td>0.735</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>491</td>\n",
       "      <td>4.965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>716.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>492</td>\n",
       "      <td>4.859</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>619.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>493</td>\n",
       "      <td>4.864</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>494</td>\n",
       "      <td>4.963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>no</td>\n",
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       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>495</td>\n",
       "      <td>1.334</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>496</td>\n",
       "      <td>4.153</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>497</td>\n",
       "      <td>0.646</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>498</td>\n",
       "      <td>1.266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>499</td>\n",
       "      <td>1.405</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>500</td>\n",
       "      <td>0.900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>470.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>501</td>\n",
       "      <td>4.076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>502</td>\n",
       "      <td>1.050</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>503</td>\n",
       "      <td>1.029</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>504</td>\n",
       "      <td>0.748</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>505</td>\n",
       "      <td>4.961</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>498.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>506</td>\n",
       "      <td>1.268</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>yes</td>\n",
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       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>507</td>\n",
       "      <td>4.959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>508</td>\n",
       "      <td>4.021</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>796.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>509</td>\n",
       "      <td>0.877</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>279.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>510</td>\n",
       "      <td>1.327</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>511</td>\n",
       "      <td>4.965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>479.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>512</td>\n",
       "      <td>1.266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>513</td>\n",
       "      <td>1.334</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>514</td>\n",
       "      <td>0.861</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>515</td>\n",
       "      <td>0.879</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>516</td>\n",
       "      <td>0.877</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>473.0</td>\n",
       "      <td>yes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>517</td>\n",
       "      <td>4.965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>no</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>518 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     Unnamed: 0  interest_rate  credit  march  may  previous  duration    y\n",
       "0             0          1.334     0.0    1.0  0.0       0.0     117.0   no\n",
       "1             1          0.767     0.0    0.0  2.0       1.0     274.0  yes\n",
       "2             2          4.858     0.0    1.0  0.0       0.0     167.0   no\n",
       "3             3          4.120     0.0    0.0  0.0       0.0     686.0  yes\n",
       "4             4          4.856     0.0    1.0  0.0       0.0     157.0   no\n",
       "5             5          0.899     0.0    0.0  1.0       0.0     126.0   no\n",
       "6             6          4.962     0.0    0.0  0.0       0.0      84.0   no\n",
       "7             7          4.858     0.0    1.0  0.0       0.0      17.0   no\n",
       "8             8          4.962     0.0    0.0  0.0       0.0     704.0  yes\n",
       "9             9          4.865     0.0    0.0  0.0       0.0     185.0   no\n",
       "10           10          1.365     0.0    0.0  1.0       1.0     374.0   no\n",
       "11           11          0.773     0.0    0.0  0.0       0.0      91.0  yes\n",
       "12           12          0.714     0.0    0.0  2.0       1.0     169.0  yes\n",
       "13           13          4.864     0.0    0.0  0.0       0.0     249.0   no\n",
       "14           14          4.966     0.0    0.0  0.0       0.0     215.0   no\n",
       "15           15          0.904     0.0    0.0  0.0       0.0     324.0  yes\n",
       "16           16          0.849     0.0    0.0  2.0       1.0     159.0  yes\n",
       "17           17          1.811     1.0    0.0  0.0       0.0     120.0  yes\n",
       "18           18          1.264     0.0    1.0  0.0       0.0     337.0  yes\n",
       "19           19          4.076     0.0    0.0  0.0       0.0     640.0   no\n",
       "20           20          1.262     0.0    0.0  0.0       0.0     663.0  yes\n",
       "21           21          0.695     0.0    1.0  2.0       1.0     403.0  yes\n",
       "22           22          4.960     0.0    0.0  0.0       0.0     300.0   no\n",
       "23           23          4.963     0.0    0.0  0.0       0.0     255.0  yes\n",
       "24           24          1.354     0.0    1.0  1.0       1.0     293.0  yes\n",
       "25           25          1.244     0.0    1.0  0.0       0.0      68.0   no\n",
       "26           26          0.748     0.0    0.0  1.0       0.0     266.0  yes\n",
       "27           27          0.878     0.0    0.0  0.0       0.0     272.0  yes\n",
       "28           28          0.644     0.0    0.0  0.0       0.0     398.0  yes\n",
       "29           29          4.968     0.0    0.0  0.0       0.0     126.0   no\n",
       "..          ...            ...     ...    ...  ...       ...       ...  ...\n",
       "488         488          0.885     0.0    0.0  2.0       1.0     608.0  yes\n",
       "489         489          4.153     0.0    0.0  0.0       0.0     250.0   no\n",
       "490         490          0.735     0.0    0.0  0.0       0.0     107.0  yes\n",
       "491         491          4.965     0.0    0.0  0.0       0.0     716.0  yes\n",
       "492         492          4.859     0.0    1.0  0.0       0.0     619.0  yes\n",
       "493         493          4.864     0.0    0.0  0.0       0.0     406.0   no\n",
       "494         494          4.963     0.0    0.0  0.0       0.0      73.0   no\n",
       "495         495          1.334     0.0    1.0  0.0       0.0     127.0   no\n",
       "496         496          4.153     0.0    0.0  0.0       0.0     187.0   no\n",
       "497         497          0.646     1.0    0.0  1.0       1.0     180.0  yes\n",
       "498         498          1.266     0.0    1.0  0.0       0.0     326.0  yes\n",
       "499         499          1.405     0.0    0.0  1.0       0.0     109.0  yes\n",
       "500         500          0.900     0.0    0.0  2.0       1.0     470.0  yes\n",
       "501         501          4.076     0.0    0.0  0.0       0.0      73.0   no\n",
       "502         502          1.050     0.0    0.0  0.0       0.0     141.0   no\n",
       "503         503          1.029     0.0    0.0  1.0       0.0     115.0   no\n",
       "504         504          0.748     0.0    0.0  1.0       1.0     171.0   no\n",
       "505         505          4.961     0.0    0.0  0.0       0.0     498.0   no\n",
       "506         506          1.268     0.0    0.0  0.0       0.0     365.0  yes\n",
       "507         507          4.959     0.0    0.0  0.0       0.0      10.0   no\n",
       "508         508          4.021     0.0    0.0  1.0       0.0     796.0  yes\n",
       "509         509          0.877     0.0    0.0  2.0       1.0     279.0  yes\n",
       "510         510          1.327     0.0    1.0  0.0       0.0     476.0  yes\n",
       "511         511          4.965     0.0    0.0  0.0       0.0     479.0  yes\n",
       "512         512          1.266     0.0    1.0  1.0       0.0     225.0   no\n",
       "513         513          1.334     0.0    1.0  0.0       0.0     204.0   no\n",
       "514         514          0.861     0.0    0.0  2.0       1.0     806.0  yes\n",
       "515         515          0.879     0.0    0.0  0.0       0.0     290.0   no\n",
       "516         516          0.877     0.0    0.0  5.0       1.0     473.0  yes\n",
       "517         517          4.965     0.0    0.0  0.0       0.0     142.0   no\n",
       "\n",
       "[518 rows x 8 columns]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "raw_data = pd.read_csv('Bank_data.csv')\n",
    "raw_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that <i> interest rate</i> indicates the 3-month interest rate between banks and <i> duration </i> indicates the time since the last contact was made with a given consumer. The <i> previous </i> variable shows whether the last marketing campaign was successful with this customer. The <i>march</i> and <i> may </i> are Boolean variables that account for when the call was made to the specific customer and <i> credit </i> shows if the customer has enough credit to avoid defaulting."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to know whether the bank marketing strategy was successful, so we need to transform the outcome variable into Boolean values in order to run regressions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>interest_rate</th>\n",
       "      <th>credit</th>\n",
       "      <th>march</th>\n",
       "      <th>may</th>\n",
       "      <th>previous</th>\n",
       "      <th>duration</th>\n",
       "      <th>y</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.334</td>\n",
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       "      <td>1.0</td>\n",
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       "      <th>1</th>\n",
       "      <td>0.767</td>\n",
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       "      <td>4.858</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>686.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.856</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.899</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0</td>\n",
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       "      <th>6</th>\n",
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       "      <td>84.0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4.858</td>\n",
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       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>4.962</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>704.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>4.865</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>185.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.365</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>374.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.773</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4.864</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4.966</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.904</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1.811</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.264</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>337.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4.076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>640.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1.262</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>663.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.695</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>403.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>4.960</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>300.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>4.963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>255.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1.354</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.244</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.748</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>266.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>272.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.644</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>398.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>4.968</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>488</th>\n",
       "      <td>0.885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>608.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>489</th>\n",
       "      <td>4.153</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>250.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>490</th>\n",
       "      <td>0.735</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>491</th>\n",
       "      <td>4.965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>716.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>492</th>\n",
       "      <td>4.859</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>619.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>493</th>\n",
       "      <td>4.864</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>494</th>\n",
       "      <td>4.963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>495</th>\n",
       "      <td>1.334</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>4.153</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>187.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>0.646</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>1.266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>326.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>1.405</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>0.900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>470.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>501</th>\n",
       "      <td>4.076</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>502</th>\n",
       "      <td>1.050</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>503</th>\n",
       "      <td>1.029</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>504</th>\n",
       "      <td>0.748</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>505</th>\n",
       "      <td>4.961</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>498.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>506</th>\n",
       "      <td>1.268</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>365.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>4.959</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>4.021</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>796.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>0.877</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>279.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>1.327</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>476.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>4.965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>479.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>512</th>\n",
       "      <td>1.266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>513</th>\n",
       "      <td>1.334</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>514</th>\n",
       "      <td>0.861</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>806.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>515</th>\n",
       "      <td>0.879</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>516</th>\n",
       "      <td>0.877</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>473.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>4.965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>518 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     interest_rate  credit  march  may  previous  duration  y\n",
       "0            1.334     0.0    1.0  0.0       0.0     117.0  0\n",
       "1            0.767     0.0    0.0  2.0       1.0     274.0  1\n",
       "2            4.858     0.0    1.0  0.0       0.0     167.0  0\n",
       "3            4.120     0.0    0.0  0.0       0.0     686.0  1\n",
       "4            4.856     0.0    1.0  0.0       0.0     157.0  0\n",
       "5            0.899     0.0    0.0  1.0       0.0     126.0  0\n",
       "6            4.962     0.0    0.0  0.0       0.0      84.0  0\n",
       "7            4.858     0.0    1.0  0.0       0.0      17.0  0\n",
       "8            4.962     0.0    0.0  0.0       0.0     704.0  1\n",
       "9            4.865     0.0    0.0  0.0       0.0     185.0  0\n",
       "10           1.365     0.0    0.0  1.0       1.0     374.0  0\n",
       "11           0.773     0.0    0.0  0.0       0.0      91.0  1\n",
       "12           0.714     0.0    0.0  2.0       1.0     169.0  1\n",
       "13           4.864     0.0    0.0  0.0       0.0     249.0  0\n",
       "14           4.966     0.0    0.0  0.0       0.0     215.0  0\n",
       "15           0.904     0.0    0.0  0.0       0.0     324.0  1\n",
       "16           0.849     0.0    0.0  2.0       1.0     159.0  1\n",
       "17           1.811     1.0    0.0  0.0       0.0     120.0  1\n",
       "18           1.264     0.0    1.0  0.0       0.0     337.0  1\n",
       "19           4.076     0.0    0.0  0.0       0.0     640.0  0\n",
       "20           1.262     0.0    0.0  0.0       0.0     663.0  1\n",
       "21           0.695     0.0    1.0  2.0       1.0     403.0  1\n",
       "22           4.960     0.0    0.0  0.0       0.0     300.0  0\n",
       "23           4.963     0.0    0.0  0.0       0.0     255.0  1\n",
       "24           1.354     0.0    1.0  1.0       1.0     293.0  1\n",
       "25           1.244     0.0    1.0  0.0       0.0      68.0  0\n",
       "26           0.748     0.0    0.0  1.0       0.0     266.0  1\n",
       "27           0.878     0.0    0.0  0.0       0.0     272.0  1\n",
       "28           0.644     0.0    0.0  0.0       0.0     398.0  1\n",
       "29           4.968     0.0    0.0  0.0       0.0     126.0  0\n",
       "..             ...     ...    ...  ...       ...       ... ..\n",
       "488          0.885     0.0    0.0  2.0       1.0     608.0  1\n",
       "489          4.153     0.0    0.0  0.0       0.0     250.0  0\n",
       "490          0.735     0.0    0.0  0.0       0.0     107.0  1\n",
       "491          4.965     0.0    0.0  0.0       0.0     716.0  1\n",
       "492          4.859     0.0    1.0  0.0       0.0     619.0  1\n",
       "493          4.864     0.0    0.0  0.0       0.0     406.0  0\n",
       "494          4.963     0.0    0.0  0.0       0.0      73.0  0\n",
       "495          1.334     0.0    1.0  0.0       0.0     127.0  0\n",
       "496          4.153     0.0    0.0  0.0       0.0     187.0  0\n",
       "497          0.646     1.0    0.0  1.0       1.0     180.0  1\n",
       "498          1.266     0.0    1.0  0.0       0.0     326.0  1\n",
       "499          1.405     0.0    0.0  1.0       0.0     109.0  1\n",
       "500          0.900     0.0    0.0  2.0       1.0     470.0  1\n",
       "501          4.076     0.0    0.0  0.0       0.0      73.0  0\n",
       "502          1.050     0.0    0.0  0.0       0.0     141.0  0\n",
       "503          1.029     0.0    0.0  1.0       0.0     115.0  0\n",
       "504          0.748     0.0    0.0  1.0       1.0     171.0  0\n",
       "505          4.961     0.0    0.0  0.0       0.0     498.0  0\n",
       "506          1.268     0.0    0.0  0.0       0.0     365.0  1\n",
       "507          4.959     0.0    0.0  0.0       0.0      10.0  0\n",
       "508          4.021     0.0    0.0  1.0       0.0     796.0  1\n",
       "509          0.877     0.0    0.0  2.0       1.0     279.0  1\n",
       "510          1.327     0.0    1.0  0.0       0.0     476.0  1\n",
       "511          4.965     0.0    0.0  0.0       0.0     479.0  1\n",
       "512          1.266     0.0    1.0  1.0       0.0     225.0  0\n",
       "513          1.334     0.0    1.0  0.0       0.0     204.0  0\n",
       "514          0.861     0.0    0.0  2.0       1.0     806.0  1\n",
       "515          0.879     0.0    0.0  0.0       0.0     290.0  0\n",
       "516          0.877     0.0    0.0  5.0       1.0     473.0  1\n",
       "517          4.965     0.0    0.0  0.0       0.0     142.0  0\n",
       "\n",
       "[518 rows x 7 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# We make sure to create a copy of the data before we start altering it. Note that we don't change the original data we loaded.\n",
    "data = raw_data.copy()\n",
    "# Removes the index column thata comes with the data\n",
    "data = data.drop(['Unnamed: 0'], axis = 1)\n",
    "# We use the map function to change any 'yes' values to 1 and 'no'values to 0. \n",
    "data['y'] = data['y'].map({'yes':1, 'no':0})\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>interest_rate</th>\n",
       "      <th>credit</th>\n",
       "      <th>march</th>\n",
       "      <th>may</th>\n",
       "      <th>previous</th>\n",
       "      <th>duration</th>\n",
       "      <th>y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>518.000000</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>518.000000</td>\n",
       "      <td>518.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.835776</td>\n",
       "      <td>0.034749</td>\n",
       "      <td>0.266409</td>\n",
       "      <td>0.388031</td>\n",
       "      <td>0.127413</td>\n",
       "      <td>382.177606</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.876903</td>\n",
       "      <td>0.183321</td>\n",
       "      <td>0.442508</td>\n",
       "      <td>0.814527</td>\n",
       "      <td>0.333758</td>\n",
       "      <td>344.295990</td>\n",
       "      <td>0.500483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.635000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.042750</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>155.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1.466000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>266.500000</td>\n",
       "      <td>0.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4.956500</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>482.750000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.970000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2653.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       interest_rate      credit       march         may    previous  \\\n",
       "count     518.000000  518.000000  518.000000  518.000000  518.000000   \n",
       "mean        2.835776    0.034749    0.266409    0.388031    0.127413   \n",
       "std         1.876903    0.183321    0.442508    0.814527    0.333758   \n",
       "min         0.635000    0.000000    0.000000    0.000000    0.000000   \n",
       "25%         1.042750    0.000000    0.000000    0.000000    0.000000   \n",
       "50%         1.466000    0.000000    0.000000    0.000000    0.000000   \n",
       "75%         4.956500    0.000000    1.000000    0.000000    0.000000   \n",
       "max         4.970000    1.000000    1.000000    5.000000    1.000000   \n",
       "\n",
       "          duration           y  \n",
       "count   518.000000  518.000000  \n",
       "mean    382.177606    0.500000  \n",
       "std     344.295990    0.500483  \n",
       "min       9.000000    0.000000  \n",
       "25%     155.000000    0.000000  \n",
       "50%     266.500000    0.500000  \n",
       "75%     482.750000    1.000000  \n",
       "max    2653.000000    1.000000  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Declare the dependent and independent variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use 'duration' as the independet variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = data['y']\n",
    "x1 = data['duration']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simple Logistic Regression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the regression and graph the scatter plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.546118\n",
      "         Iterations 7\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<caption>Logit Regression Results</caption>\n",
       "<tr>\n",
       "  <th>Dep. Variable:</th>         <td>y</td>        <th>  No. Observations:  </th>  <td>   518</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Model:</th>               <td>Logit</td>      <th>  Df Residuals:      </th>  <td>   516</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Method:</th>               <td>MLE</td>       <th>  Df Model:          </th>  <td>     1</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Date:</th>          <td>Wed, 30 Jan 2019</td> <th>  Pseudo R-squ.:     </th>  <td>0.2121</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>Time:</th>              <td>17:12:17</td>     <th>  Log-Likelihood:    </th> <td> -282.89</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>converged:</th>           <td>True</td>       <th>  LL-Null:           </th> <td> -359.05</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th> </th>                      <td> </td>        <th>  LLR p-value:       </th> <td>5.387e-35</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>const</th>    <td>   -1.7001</td> <td>    0.192</td> <td>   -8.863</td> <td> 0.000</td> <td>   -2.076</td> <td>   -1.324</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>duration</th> <td>    0.0051</td> <td>    0.001</td> <td>    9.159</td> <td> 0.000</td> <td>    0.004</td> <td>    0.006</td>\n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary.Summary'>\n",
       "\"\"\"\n",
       "                           Logit Regression Results                           \n",
       "==============================================================================\n",
       "Dep. Variable:                      y   No. Observations:                  518\n",
       "Model:                          Logit   Df Residuals:                      516\n",
       "Method:                           MLE   Df Model:                            1\n",
       "Date:                Wed, 30 Jan 2019   Pseudo R-squ.:                  0.2121\n",
       "Time:                        17:12:17   Log-Likelihood:                -282.89\n",
       "converged:                       True   LL-Null:                       -359.05\n",
       "                                        LLR p-value:                 5.387e-35\n",
       "==============================================================================\n",
       "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
       "------------------------------------------------------------------------------\n",
       "const         -1.7001      0.192     -8.863      0.000      -2.076      -1.324\n",
       "duration       0.0051      0.001      9.159      0.000       0.004       0.006\n",
       "==============================================================================\n",
       "\"\"\""
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = sm.add_constant(x1)\n",
    "reg_log = sm.Logit(y,x)\n",
    "results_log = reg_log.fit()\n",
    "# Get the regression summary\n",
    "results_log.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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g2326FBImkwmzZ8/Gd999B1EUERoaiujoaFRUVGDXrl3YvXs3xo4di9dff71e46nVahgMBvtrm80GufxGSa1bt0bPnj2h1WoBAP369cPp06edhkRZWZUr7dhptRrodJVurduc+EOf/tAj4B99+kOPgG/06SykXLpP4p133sHBgweRnJyM3bt349ChQ9i+fTtycnKQnZ2N5ORkZGZm4qOPPqrXeAkJCcjJyQEA5OXlISYmxj6vR48eKCwsRGlpKSwWC44dO4auXbu6Ui4RETWQIN7pi5hukZSUhNDQUGzdurXO51xbLBaMHz8eNpsN27dvv+N4N69uKiwshCiKSEtLQ05ODqKjo5GUlIR//vOfWL9+PQBg2LBhePrpp52O524a+0KSNwV/6NMfegT8o09/6BHwjT6d7Um4dLippKQEQ4cOrTMgAEAul2PAgAFO76O4VUBAAF599VWHaV26dLH/PHLkSIwcOdKVEomIyINcOtzUrVs3hyuQ6nL27Fl06tSpITUREZGPcCkknnvuORw9ehSpqamorKy9e/T+++/j8OHDWLp0qccKJCIi73HpcNNnn32GTp06YfPmzfjiiy8QGxuLNm3aoKamBidPnoROp4NKpap1dZMgCPj88889WjgRETU+l0Ji27Zt9p8NBgP+85//1FpGr9fj9OnTDtP4VRpERM2TSyEh9e2vRETUMrl0ToKIiPyL0z2J7OxsdO7c2X6Xc3Z2dr0HTkpKalhlRETkdU5DYt68eUhJSUFKSor99Z3OL4iiCEEQap2XICKi5sdpSKSkpKB///4Or4mIyH/cMSRuNXDgQMTFxUGpVDZqUURE5BtcOnE9f/58PPPMM41VCxER+RiXQqKyspLfxEpE5EdcComkpCTs3r0bpaWljVUPERH5EJduprvvvvtw+PBhJCUloW/fvoiKikJQUFCt5QRBwAsvvOCxIomIyDtcColXXnnF/vO+ffskl2NIEBG1DC6FxMaNGxurDiIi8kEuhcSt90xYrVbIZDL76+LiYkRFRXmuMiIi8jqXv7vpwIEDGDNmjMNzrEVRxPDhwzFq1CicOHHCowUSEZH3uBQSR44cwdNPP42LFy8iODjYPt1kMmH06NG4cuUKpk6diuPHj3u8UCIianouhcTatWuhUqnw5ZdfYtKkSfbpSqUSqamp+Pzzz6FUKrF69WqPF0pERE3PpZA4ffo0Ro0ahejo6DrnR0dHY8SIEXU+jIiIiJofl0LCarXCaDQ6XUYQBIii2KCiiIjIN7gUEt27d8fevXsl77i+fv069u7di9jYWI8UR0RE3uVSSDz55JMoKSnBjBkz8K9//QvFxcUoLy/H5cuXsWPHDjz11FO4evUqnnrqqUYql4iImpJL90kkJydj4cKFSE9Px7PPPltrviAImD9/PoYNG+axAomIyHtcCgkAmD17NoYOHYqvv/4aZ86cQUVFBUJCQhATE4NHH30UnTt3bow6iYjIC1wOCQDo1KkT5s6d6+laiIjIx7gVEufOnUOXLl3sr//xj3/gyJEjiIqKwrRp06DVaj1WIBEReY9LIWEwGDBv3jwcOnQIBw8eROvWrfHWW2/hvffes1/2+sUXX2DLli1o27ZtoxRMRERNx6Wrm95991189913SExMBABUV1dj48aNCA8Px0cffYSVK1eitLQUa9eubZRiiYioabm0J7Fr1y7cd999ePfddwEAWVlZqK6uxrRp09CvXz/069cP//73v5GTk9MoxRIRUdNyaU/iypUr6NOnj/11Tk4OBEHAgw8+aJ8WFRWFsrKyeo1ns9nw8ssvY/LkyZg+fTouXLhQ5zKzZs3CJ5984kqpRETkAS6FRGhoKMrLy+2vc3JyEBwc7BAc58+fr/eJ66ysLJhMJmRkZODZZ5/FypUray2zatUqh20SEVHTcelwU1xcHHbs2IFHH30Uubm5+PHHHzFixAjI5TeG2bFjB7KzszFy5Mh6jZebm4vBgwcDAOLj45Gfn+8wf8eOHbX2VJwJCwuBXC6784J10Go1bq3X3PhDn/7QI+AfffpDj4Bv9+lSSMyfPx+//e1vMWPGDIiiCKVSidmzZwMAUlNT8dFHHyEsLAy///3v6zWeXq+HWq22v5bJZLBYLJDL5SgsLMT27duxevXqep8ILyurcqUdO61WA52u0q11mxN/6NMfegT8o09/6BHwjT6dhZRLIdGjRw98+umnyMjIgCiKGDt2rP3L/Hr06IEnnngCs2bNqvdjTNVqNQwGg/21zWaz75VkZmbip59+wpNPPoni4mIEBgYiKiqq3nsVRETUcC7fTNepUyc8//zztaaPHTsWY8eOdWmshIQE7N27FyNGjEBeXh5iYmLs8xYvXmz/OT09HREREQwIIqIm5tYd13q9HllZWSgoKEBVVRVCQ0PRo0cPPPzww1AoFPUeZ8iQIdi/fz8ef/xxiKKItLQ0bNiwAdHR0UhKSnKnNCIi8iBBdPEJQRkZGXjjjTdQXV3t8HAhQRAQHh6OtLQ0+812Tc3d43q+cEywKfhDn/7QI+AfffpDj4Bv9OmxcxI7d+7EsmXLEBERgTlz5qBXr15QqVS4evUqjh49ik8++QTz5s3Dpk2bHC6LJSKi5smlkPjggw8QFhaGLVu2oF27dg7zkpKSMG7cOEyePBmrVq3C3//+d48WSkRETc+lm+kKCwsxdOjQWgFxU5cuXfCb3/wGx48f90hxRETkXS6FRFhYGGw2m9NlgoODoVKpGlQUERH5BpdCYtKkSfjqq69w+vTpOudfvHgR27dvx/jx4z1SHBEReZfTcxIbN250eB0SEgKVSoWJEydizJgx6NOnDyIiIlBRUYETJ07gyy+/RFhYGOLi4hq1aCIiahpOL4Ht3r07BEGwX+p668/2AQQBAGpdDiu1t9GYeAmsc/7Qpz/0CPhHn/7QI+Abfbp9Cezrr7/u8WKIiKj5cBoS48aNa6o6iIjIB7l04pqIiPyLSzfT9e/fv17LCYKAQ4cOuVUQERH5DpdC4tZnP9yqpqYG169fh81mQ0xMDDp06OCR4oiIyLtcCok9e/ZIzqusrMS6devw2Wef4a233mpwYURE5H0eOyeh0WiwePFidO3aFW+++aanhiUiIi/y+InrPn364MiRI54eloiIvMDjIXH69Gn7DXZERNS8uXROIjs7u87poiiiqqoK33zzDQ4cOIAhQ4Z4pDgiIvIul0Ji3rx5TvcSRFFEZGQk/vCHPzS4MCIi8j6PhYRCoUDnzp2RmJiIwMBAjxRHRETe5VJIzJ8/v9Y0o9GIH3/8EREREXyOBBFRC1OvE9d79uzBkiVLUFBQ4DD9L3/5Cx544AEMGzYM/fv3x4IFC1BWVtYohRIRUdO7457Eyy+/jE8//RQA8NBDD6F79+4AgL/+9a94//33IQgCfv3rXwMAdu3ahbNnz+Lzzz+HQqFoxLKJiKgpON2T2LNnD7Zs2YJ7770XH3zwAR566CEAwE8//YQPP/wQgiDgtddew/r167F+/Xqkp6fj7NmztR5WREREzZPTkNi6dStat26NjRs3YuDAgVAqlQCAHTt2wGKxIDo6Go899ph9+aSkJCQkJGDHjh2NWzURETUJpyFx/PhxPPTQQ7W+2O/AgQMQBAGPPPJIrXV69+6NCxcueLZKIiLyCqchUV5ejjZt2jhMs9lsyM3NBQAMGDCg1jpyuRxms9mDJRIRkbc4DQmNRlPraqXjx49Dr9dDLpfjvvvuq7XO+fPnERYW5tkqiYjIK5yGRM+ePXHgwAHYbDb7tO3btwO4sRcRHBzssLxOp8O+ffvQs2fPRiiViIiamtOQmDRpEi5duoRFixbh+++/x+bNm5GRkQFBEDB16lSHZUtLS7FgwQLU1NRg9OjRjVo0ERE1Daf3SSQlJWHq1KnYvHkzdu7cCeDG9zNNmTIFiYmJ9uXmzJmDgwcPwmg0YtiwYUhOTm7cqomIqEnc8Wa6l156CUOHDsXevXthsVgwcOBA+/0SN/3vf/+DSqXC008/jblz59Z74zabDcuXL8eZM2egUCiQmpqKjh072uf/7W9/wz//+U8AQGJiIlJSUuo9NhERNVy9vrupf//+6N+/v+T8zz//XPL5185kZWXBZDIhIyMDeXl5WLlyJdatWwcAKCoqwrZt2/Dpp59CEARMmTIFycnJ9ju+iYio8bn0BX9S3AkIAMjNzcXgwYMBAPHx8cjPz7fPa9u2LT744APIZDIAgMVisd/MR0RETcMjIeEuvV7vEDAymQwWiwVyuRyBgYEIDw+HKIr405/+hLi4ONxzzz1OxwsLC4FcLnOrFq1W49Z6zY0/9OkPPQL+0ac/9Aj4dp9eDQm1Wg2DwWB/bbPZIJf/UpLRaMTSpUuhUqmwbNmyO45XVlblVh1arQY6XaVb6zYn/tCnP/QI+Eef/tAj4Bt9Ogspjz/j2hUJCQnIyckBAOTl5SEmJsY+TxRF/P73v0dsbCxeffVV+2EnIiJqOl7dkxgyZAj279+Pxx9/HKIoIi0tDRs2bEB0dDRsNhsOHz4Mk8mEf//73wCARYsWoU+fPt4smYjIr3g1JAICAvDqq686TOvSpYv95xMnTjR1SUREdAuvHm4iIiLfxpAgIiJJDAkiIpLEkCAiIkkMCSIiksSQICIiSQwJIiKSxJAgIiJJDAkiIpLEkCAiIkkMCSIiksSQICIiSQwJIiKSxJAgIiJJDAkiIpLEkCAiIkkMCSIiksSQICIiSQwJIiKSxJAgIiJJDAkiIpLEkCAiIkkMCSIiksSQICIiSQwJIiKSxJAgIiJJDAkiIpLEkCAiIkkMCSIikiT3dgG+oFxvxL7jl/FTqQEdIluhqsaEK6VVqDaZceWqAdUmM6pNIpSBAeh0dyucLy6H3mhBK40C+soaWBEAs9kGiw0IU8uhDlJCEyKHocaKsFZKVBpMUAbKcVfrILQJD0ZpeTXO/1gJm01EoDwA2rAQdI4KhUopx9lL12G1iujUrhU6RKqRW1iCop8q0E6rQcdIDUquV8NotkCECEEQEBIUiH6xkVCHKFCuNyJYKceFHytx/scKdI9ujaoaC9QqBbShwbCUGFBdZUK5wQSIIoKVchTrDNCEBKKdVg1loAxGsxXleiNkAQKullUjMiwY1UYLzBabvVZloMzh92c0W6G7Xg2IYp3zG+JmPaFqpcO4RrMVurIqQBCgbR1ca15d6xCR6wRRFEVvbdxms2H58uU4c+YMFAoFUlNT0bFjR/v8LVu24B//+Afkcjnmzp2Lhx9+2Ol4Ol2lS9s3WSx49W9HcLmkyq36W5IAAWgXoUKV0YLSCqPkcsrAAAzsdTeeSOoGAPhH9n+x/8SPqDFZAQBBigD8uueN+bIA93dUrTYbMvacxdFCHUorjAhvpUSfGC0ee6gztuw9hwMnrqDGZPt5mzIM7NkWEx/ugn8duoT9x4od1pn8SNcG1eKLtFqNy3/vzY0/9Aj4Rp9arUZynlf3JLKysmAymZCRkYG8vDysXLkS69atAwDodDps2rQJn332GYxGI6ZMmYKBAwdCoVB4bPsrNv6HAfEzmwhc0hnuuJzRbMOe3GIECAIAIDu32GF+jemX+VOSY9yuJ2PPWWQduWR/fa3CiKwjl3Dm4nUUXdXftk0rsnOLUVhU7jDv5joAGlQLkT/z6j+vcnNzMXjwYABAfHw88vPz7fOOHz+OPn36QKFQQKPRIDo6GgUFBR7bdmWVCZdu+7Ch+sstuIrcMzrJ+f85o4PRbHVrbKPZiqOFdY9drJN+z6TmHS0scbsWIn/n1T0JvV4PtVptfy2TyWCxWCCXy6HX66HR/LILpFKpoNc7/1APCwuBXF6/Y9CX/6uD146ztQBlehMEZ/MrjZApAqGNULk89pUSA0or6z7kZXPypknNK6uscbsWX+bsEEFL4Q89Ar7dp1dDQq1Ww2D45RCHzWaDXC6vc57BYHAIjbqUldX/0JFGEQABYFC4KUytAAQBZRIf5mEaJawms1vHWq1mK8I1Slyr49xIgCAdBlLzwjRBbtfiq3zhOHZj84ceAd/o01lIefVwU0JCAnJycgAAeXl5iIn55bhxr169kJubC6PRiMrKSpw7d85hfkNpQhRoH6m+84JUp77dI9FS8OjZAAALu0lEQVQ3Vis5PyFW6/aVRcpAGfrE1D12lFb6PZOa1ycmglc5EbnJq3sSQ4YMwf79+/H4449DFEWkpaVhw4YNiI6ORlJSEqZPn44pU6ZAFEUsXLgQSqXSo9v/44wEXt30s5tXN1UbLXX+C/6mm1c3TX6kKwBAFMXbrm6S4dc929rnu+vm+kcLS1BWWYMwTRD6xETccnWT4zYdr2667LBOQ2sh8mdevQTW09zdZVMEK7Dn0PkWf59EsCoI1YaaFn2fhFarwaXL11v8fRK+cIiisflDj4Bv9OnscBNDAr7xJjUFf+jTH3oE/KNPf+gR8I0+ffacBBER+TaGBBERSWJIEBGRJIYEERFJYkgQEZEkhgQREUliSBARkaQWdZ8EERF5FvckiIhIEkOCiIgkMSSIiEgSQ4KIiCQxJIiISBJDgoiIJDEkiIhIklefTOdtNpsNy5cvx5kzZ6BQKJCamoqOHTt6u6wGGTt2rP1Z4O3bt8fkyZOxYsUKyGQyDBo0CCkpKc2272PHjuHPf/4zNm3ahAsXLuCFF16AIAjo1q0bli1bhoCAAKxZswbffPMN5HI5li5dil69ekku66tu7fPkyZOYM2cOOnXqBAB44oknMGLEiGbdp9lsxtKlS1FcXAyTyYS5c+eia9euLer9rKvHtm3bNs/3UvRjO3fuFJ9//nlRFEXx6NGj4pw5c7xcUcPU1NSIY8aMcZg2evRo8cKFC6LNZhNnzZol5ufnN8u+33vvPfHRRx8VJ06cKIqiKM6ePVv87rvvRFEUxZdeeknctWuXmJ+fL06fPl202WxicXGxOH78eMllfdXtfW7ZskVcv369wzLNvc+tW7eKqampoiiKYmlpqZiYmNji3s+6emyu76VvxW8Ty83NxeDBgwEA8fHxyM/P93JFDVNQUIDq6mr87ne/w4wZM/D999/DZDIhOjoagiBg0KBBOHjwYLPsOzo6Gunp6fbXJ0+eRP/+/QEADz74IA4cOIDc3FwMGjQIgiCgXbt2sFqtKC0trXNZX3V7n/n5+fjmm28wdepULF26FHq9vtn3OWzYMDzzzDP21zKZrMW9n3X12FzfS78OCb1eD7VabX8tk8lgsVi8WFHDBAUFYebMmVi/fj1eeeUVLFmyBMHBwfb5KpUKlZWVzbLvoUOHQi7/5eioKN54xjcg3dfN6XUt66tu77NXr15YvHgxNm/ejA4dOmDt2rXNvk+VSgW1Wg29Xo//+7//w4IFC1rc+1lXj831vfTrkFCr1TAYDPbXNpvN4X/Q5uaee+7B6NGjIQgC7rnnHmg0Gly/ft0+32AwoFWrVi2i71uPz0r1ZTAYoNFo6ly2uRgyZAh69Ohh//nUqVMtos8rV65gxowZGDNmDEaNGtUi38/be2yu76Vfh0RCQgJycnIAAHl5eYiJifFyRQ2zdetWrFy5EgDw008/obq6GiEhIbh48SJEUcS+ffvQr1+/FtF3XFwcDh06BADIycmx97Vv3z7YbDZcvnwZNpsN4eHhdS7bXMycORPHjx8HABw8eBC/+tWvmn2fJSUl+N3vfofnnnsOjz32GICW937W1WNzfS/9+ltgb17lU1hYCFEUkZaWhi5duni7LLeZTCYsWbIEly9fhiAI+MMf/oCAgACkpaXBarVi0KBBWLhwYbPt+9KlS1i0aBG2bNmCH374AS+99BLMZjM6d+6M1NRUyGQypKenIycnBzabDUuWLEG/fv0kl/VVt/Z58uRJvPbaawgMDERERARee+01qNXqZt1namoqvv76a3Tu3Nk+7Y9//CNSU1NbzPtZV48LFizAm2++2ezeS78OCSIics6vDzcREZFzDAkiIpLEkCAiIkkMCSIiksSQICIiSc3rDiqiekpPT8eaNWscpgmCgKCgIERGRuL+++/HU0895ROX/lZWVuLLL7/EtGnT7NOmT5+Ow4cP4/vvv/fZm8XIPzAkqEVLSkrCvffeC+DGfTF6vR4FBQXYsmULtm3bhrfffhsPPfSQV2scOnQotFqtQ0iMGzcO/fv3h1Kp9GJlRAwJauGSk5Mxfvz4WtO//fZbzJs3DwsXLkRmZqZXvyr92rVr0Gq1DtPqqpnIG3hOgvxSYmIinnnmGVRVVeGdd97xdjlEPoshQX5r2rRpUCqV2LVrFywWCw4dOoTY2FisWLGi1rIvvPACYmNjcfr0aQA3vjojNjYWb7/9NlJTUxEfH4/7778fX3/9NQCgtLQUb7zxBoYPH47evXujd+/eGDlyJN599137N+7e3B5w42veY2Nj7V8TPn36dMTGxqKiosJeg81mw8cff4yxY8eiV69e6Nu3L377299i//79DrXerC09PR3Z2dl47LHH0KtXLwwYMAAvvvgiSktLPf/LpBaLIUF+Kzg4GHFxcaiqqrJ/+Ltqy5Yt+Prrr/HEE08gPj4e8fHxqKysxKRJk7Bx40Z07doVM2bMwKOPPgqdToe33noLf/nLXwAAUVFRSElJAQBEREQgJSXF/gyB29lsNixcuBCvvPIK9Ho9JkyYgOTkZJw4cQIzZ87E5s2ba62zd+9epKSkQKvVYvr06WjTpg0+/fRTLFq0yK1eyT/xnAT5tTZt2gAAdDodVCqVy+tfu3YNmZmZ6N69u33ae++9h6KiIqSmpmLixIn26SkpKfjNb36Dr776Cs8//zzat2+P+fPnY82aNYiIiMD8+fMlt7Nt2zbs2LEDgwYNQnp6OkJCQgAARUVFeOKJJ5CWloYHH3wQHTp0sK9z8uRJrFq1CsOHDwdw4wvmxo0bh4MHD+LixYuIjo52uV/yP9yTIL+mUCgA3HgAlTs6duzoEBAAMGjQILzyyisYO3asw/S7774bHTp0cOtwzxdffAEAWL58uT0gAKBDhw6YO3cuLBYLMjMzHdbp0KGDPSAAIDAwEAMGDAAAnD9/3uUayD9xT4L82s0Hvtz6weuK9u3b15oWFxeHuLg4GAwGHDt2DBcuXMD58+dx4sQJXLhwAVar1eXtFBQUoE2bNg57Cjf17dvXvsytOnXqVGtZjUYD4MbXyhPVB0OC/FpxcTGAG//qvvUpfvVV130MRqMRf/3rX5GRkYHq6moANw5r3XfffQgLC4NOp3N5O3q9HhEREXXOi4yMBADU1NQ4TL+5l3Srm4/EJKovhgT5rfLycpw9exatWrVC165dkZubC+DG87Nvd/PDvj5WrlyJjz/+GEOHDsXUqVMRGxuL1q1bAwCGDx/uVkioVCpcvXpVsg8A9m0QeRLPSZDfysjIgMViwfDhwyGTyRAYGAgAqKqqqrVsUVFRvcfdvn077rrrLrz99tu4//777R/eNTU1uHz5MoC6g8iZ7t27o6KiAoWFhbXmHTlyBADQtWtXl8Ykqg+GBPmlgwcPYu3atQgJCcHs2bMB3DgJLZPJ8N133znsOXzzzTc4efJkvcdWKpUwGo0O9zhYrVasWLHCfkjIbDbb5wUGBjq8rsvNO7BXrFjhEGJFRUVYu3YtAgMDMXLkyHrXSFRfPNxELVpWVpb9vIMoiqisrMSpU6dw5MgRBAUF4a233kJUVBQAIDw8HMnJydi5cycmTpyIxMREFBUVYc+ePejbt6/9cNSdjBo1Ch9++KH9XgaLxYJ9+/bhhx9+QHh4OEpLS3H9+nX7uYTIyEj873//w7Jly5CYmIhHHnmk1phjxozBnj17sHPnTowePRoPPvggqqqqkJ2djcrKSrz00ku8pJUaBUOCWrTs7GxkZ2fbXwcHByMqKgrTpk3Dk08+WeuDNS0tDZGRkdixYwc2bdqEbt26YfXq1bh48WK9Q2LhwoVQqVTYtm0bPv74Y4SHh6NLly548cUXce7cOaSlpeHbb7+130Px8ssvIzU1FZ999hksFkudISEIAlatWoXNmzdj69at2Lp1K4KDgxEfH4+ZM2figQceaMBviUiaILp6cJSIiPwGz0kQEZEkhgQREUliSBARkSSGBBERSWJIEBGRJIYEERFJYkgQEZEkhgQREUliSBARkaT/B2mQHxNjkerPAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1b794010cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a scatter plot of x1 (Duration, no constant) and y (Subscribed)\n",
    "plt.scatter(x1,y,color = 'C0')\n",
    "# Don't forget to label your axes!\n",
    "plt.xlabel('Duration', fontsize = 20)\n",
    "plt.ylabel('Subscription', fontsize = 20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Expand the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can be omitting many causal factors in our simple logistic model, so we instead switch to a multivariate logistic regression model. Add the ‘interest_rate’, ‘march’, ‘credit’ and ‘previous’ estimators to our model and run the regression again. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Declare the independent variable(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To avoid writing them out every time, we save the names of the estimators of our model in a list. \n",
    "estimators=['interest_rate','credit','march','previous','duration']\n",
    "\n",
    "X1_all = data[estimators]\n",
    "y = data['y']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimization terminated successfully.\n",
      "         Current function value: 0.336664\n",
      "         Iterations 7\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"simpletable\">\n",
       "<tr>\n",
       "        <td>Model:</td>              <td>Logit</td>      <td>Pseudo R-squared:</td>    <td>0.514</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "  <td>Dependent Variable:</td>         <td>y</td>              <td>AIC:</td>         <td>360.7836</td> \n",
       "</tr>\n",
       "<tr>\n",
       "         <td>Date:</td>        <td>2019-01-30 17:13</td>       <td>BIC:</td>         <td>386.2834</td> \n",
       "</tr>\n",
       "<tr>\n",
       "   <td>No. Observations:</td>         <td>518</td>        <td>Log-Likelihood:</td>    <td>-174.39</td> \n",
       "</tr>\n",
       "<tr>\n",
       "       <td>Df Model:</td>              <td>5</td>            <td>LL-Null:</td>        <td>-359.05</td> \n",
       "</tr>\n",
       "<tr>\n",
       "     <td>Df Residuals:</td>           <td>512</td>         <td>LLR p-value:</td>    <td>1.2114e-77</td>\n",
       "</tr>\n",
       "<tr>\n",
       "      <td>Converged:</td>           <td>1.0000</td>           <td>Scale:</td>         <td>1.0000</td>  \n",
       "</tr>\n",
       "<tr>\n",
       "    <td>No. Iterations:</td>        <td>7.0000</td>              <td></td>               <td></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>const</th>         <td>-0.0211</td>  <td>0.3113</td>  <td>-0.0677</td> <td>0.9460</td> <td>-0.6313</td> <td>0.5891</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>interest_rate</th> <td>-0.8001</td>  <td>0.0895</td>  <td>-8.9434</td> <td>0.0000</td> <td>-0.9755</td> <td>-0.6248</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>credit</th>        <td>2.3585</td>   <td>1.0875</td>  <td>2.1688</td>  <td>0.0301</td> <td>0.2271</td>  <td>4.4900</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>march</th>         <td>-1.8322</td>  <td>0.3297</td>  <td>-5.5563</td> <td>0.0000</td> <td>-2.4785</td> <td>-1.1859</td>\n",
       "</tr>\n",
       "<tr>\n",
       "  <th>previous</th>      <td>1.5363</td>   <td>0.5010</td>  <td>3.0666</td>  <td>0.0022</td> <td>0.5544</td>  <td>2.5182</td> \n",
       "</tr>\n",
       "<tr>\n",
       "  <th>duration</th>      <td>0.0070</td>   <td>0.0007</td>  <td>9.3810</td>  <td>0.0000</td> <td>0.0055</td>  <td>0.0084</td> \n",
       "</tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<class 'statsmodels.iolib.summary2.Summary'>\n",
       "\"\"\"\n",
       "                         Results: Logit\n",
       "=================================================================\n",
       "Model:              Logit            Pseudo R-squared: 0.514     \n",
       "Dependent Variable: y                AIC:              360.7836  \n",
       "Date:               2019-01-30 17:13 BIC:              386.2834  \n",
       "No. Observations:   518              Log-Likelihood:   -174.39   \n",
       "Df Model:           5                LL-Null:          -359.05   \n",
       "Df Residuals:       512              LLR p-value:      1.2114e-77\n",
       "Converged:          1.0000           Scale:            1.0000    \n",
       "No. Iterations:     7.0000                                       \n",
       "-----------------------------------------------------------------\n",
       "                   Coef.  Std.Err.    z    P>|z|   [0.025  0.975]\n",
       "-----------------------------------------------------------------\n",
       "const             -0.0211   0.3113 -0.0677 0.9460 -0.6313  0.5891\n",
       "interest_rate     -0.8001   0.0895 -8.9434 0.0000 -0.9755 -0.6248\n",
       "credit             2.3585   1.0875  2.1688 0.0301  0.2271  4.4900\n",
       "march             -1.8322   0.3297 -5.5563 0.0000 -2.4785 -1.1859\n",
       "previous           1.5363   0.5010  3.0666 0.0022  0.5544  2.5182\n",
       "duration           0.0070   0.0007  9.3810 0.0000  0.0055  0.0084\n",
       "=================================================================\n",
       "\n",
       "\"\"\""
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "X_all = sm.add_constant(X1_all)\n",
    "reg_logit = sm.Logit(y,X_all)\n",
    "results_logit = reg_logit.fit()\n",
    "results_logit.summary2()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Confusion Matrix"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Find the confusion matrix of the model and estimate its accuracy. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "def confusion_matrix(data,actual_values,model):\n",
    "        \n",
    "        # Confusion matrix \n",
    "        \n",
    "        # Parameters\n",
    "        # ----------\n",
    "        # data: data frame or array\n",
    "            # data is a data frame formatted in the same way as your input data (without the actual values)\n",
    "            # e.g. const, var1, var2, etc. Order is very important!\n",
    "        # actual_values: data frame or array\n",
    "            # These are the actual values from the test_data\n",
    "            # In the case of a logistic regression, it should be a single column with 0s and 1s\n",
    "            \n",
    "        # model: a LogitResults object\n",
    "            # this is the variable where you have the fitted model \n",
    "            # e.g. results_log in this course\n",
    "        # ----------\n",
    "        \n",
    "        #Predict the values using the Logit model\n",
    "        pred_values = model.predict(data)\n",
    "        # Specify the bins \n",
    "        bins=np.array([0,0.5,1])\n",
    "        # Create a histogram, where if values are between 0 and 0.5 tell will be considered 0\n",
    "        # if they are between 0.5 and 1, they will be considered 1\n",
    "        cm = np.histogram2d(actual_values, pred_values, bins=bins)[0]\n",
    "        # Calculate the accuracy\n",
    "        accuracy = (cm[0,0]+cm[1,1])/cm.sum()\n",
    "        # Return the confusion matrix and \n",
    "        return cm, accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[218.,  41.],\n",
       "        [ 30., 229.]]), 0.862934362934363)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "confusion_matrix(X_all,y,results_logit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Test the model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the test data from the 'Bank_data_testing.csv' file provided. (Remember to convert the outcome variable ‘y’ into Boolean). "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load new data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We have to load data our model has never seen before.\n",
    "raw_data2 = pd.read_csv('Bank-data-testing.csv')\n",
    "data_test = raw_data2.copy()\n",
    "# Removes the index column thata comes with the data\n",
    "data_test = data_test.drop(['Unnamed: 0'], axis = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>interest_rate</th>\n",
       "      <th>credit</th>\n",
       "      <th>march</th>\n",
       "      <th>may</th>\n",
       "      <th>previous</th>\n",
       "      <th>duration</th>\n",
       "      <th>y</th>\n",
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       "      <th>0</th>\n",
       "      <td>1.313</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>0</td>\n",
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       "      <th>3</th>\n",
       "      <td>4.120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1468.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.697</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>0</td>\n",
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       "      <th>6</th>\n",
       "      <td>0.639</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>215.0</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>4.120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1.281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>809.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>4.966</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>389.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>4.965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>4.968</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>766.0</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.714</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1.410</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>4.964</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>181.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>4.120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>288.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1.260</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>431.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.354</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>617.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4.857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>4.857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.883</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1.405</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>180.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.702</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>4.021</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1074.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1.264</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>4.962</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1441.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>4.120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>4.857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1.260</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>0.709</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>367.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>1.299</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>0.788</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>261.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>4.856</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>0.702</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>347.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>0.900</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>288.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>4.963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>0.851</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>0.720</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>1.327</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>263.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>1.281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>4.961</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>1.327</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1046.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>1.291</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>725.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>1.498</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>4.120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>1.410</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>291.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>4.968</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>1.266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>533.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>4.961</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>952.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>1.281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>1.260</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>372.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>4.858</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>607.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>1.778</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>377.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>1.268</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>166.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>4.963</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>458.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>1.264</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>397.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>1.281</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>0.739</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>1.046</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>222 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     interest_rate  credit  march  may  previous  duration  y\n",
       "0            1.313     0.0    1.0  0.0       0.0     487.0  0\n",
       "1            4.961     0.0    0.0  0.0       0.0     132.0  0\n",
       "2            4.856     0.0    1.0  0.0       0.0      92.0  0\n",
       "3            4.120     0.0    0.0  0.0       0.0    1468.0  1\n",
       "4            4.963     0.0    0.0  0.0       0.0      36.0  0\n",
       "5            0.697     0.0    1.0  4.0       0.0     131.0  0\n",
       "6            0.639     1.0    0.0  0.0       0.0     215.0  1\n",
       "7            4.120     0.0    0.0  0.0       0.0     499.0  0\n",
       "8            1.281     0.0    1.0  1.0       0.0     809.0  1\n",
       "9            4.966     0.0    0.0  0.0       0.0     389.0  0\n",
       "10           4.965     0.0    0.0  0.0       0.0     168.0  0\n",
       "11           4.968     0.0    0.0  0.0       0.0     766.0  1\n",
       "12           0.714     0.0    0.0  1.0       0.0     192.0  1\n",
       "13           1.410     0.0    0.0  1.0       0.0      48.0  0\n",
       "14           4.964     0.0    0.0  0.0       0.0     181.0  0\n",
       "15           4.120     0.0    0.0  0.0       0.0     288.0  0\n",
       "16           1.260     0.0    0.0  2.0       0.0     431.0  1\n",
       "17           0.900     0.0    0.0  1.0       1.0     153.0  1\n",
       "18           1.354     0.0    1.0  0.0       0.0     617.0  1\n",
       "19           4.857     0.0    1.0  0.0       0.0     293.0  0\n",
       "20           4.857     0.0    1.0  0.0       0.0     157.0  0\n",
       "21           0.883     0.0    0.0  4.0       0.0     167.0  1\n",
       "22           1.405     0.0    0.0  0.0       0.0     180.0  0\n",
       "23           0.702     0.0    0.0  0.0       0.0       7.0  0\n",
       "24           4.021     0.0    0.0  0.0       0.0    1074.0  1\n",
       "25           1.264     0.0    1.0  0.0       0.0     377.0  1\n",
       "26           4.962     0.0    0.0  0.0       0.0    1441.0  1\n",
       "27           4.120     0.0    0.0  0.0       0.0      30.0  0\n",
       "28           4.857     0.0    1.0  0.0       0.0     154.0  0\n",
       "29           1.260     0.0    0.0  0.0       0.0     121.0  1\n",
       "..             ...     ...    ...  ...       ...       ... ..\n",
       "192          0.709     0.0    0.0  1.0       0.0     367.0  1\n",
       "193          1.299     0.0    1.0  0.0       0.0     123.0  0\n",
       "194          0.788     0.0    0.0  1.0       1.0     261.0  1\n",
       "195          4.856     0.0    1.0  0.0       0.0     130.0  0\n",
       "196          0.702     0.0    0.0  1.0       1.0     347.0  1\n",
       "197          0.900     0.0    0.0  3.0       1.0     288.0  1\n",
       "198          4.963     0.0    0.0  0.0       0.0     119.0  0\n",
       "199          0.851     0.0    0.0  1.0       1.0      63.0  1\n",
       "200          0.720     0.0    0.0  0.0       0.0     485.0  1\n",
       "201          1.327     0.0    1.0  0.0       0.0     263.0  0\n",
       "202          1.281     0.0    1.0  0.0       0.0      77.0  0\n",
       "203          4.961     0.0    0.0  0.0       0.0     135.0  0\n",
       "204          1.327     0.0    1.0  0.0       0.0    1046.0  1\n",
       "205          1.291     0.0    1.0  0.0       0.0     725.0  1\n",
       "206          1.498     0.0    0.0  0.0       0.0     351.0  1\n",
       "207          4.120     0.0    0.0  0.0       0.0      91.0  0\n",
       "208          1.410     0.0    0.0  1.0       0.0     291.0  0\n",
       "209          4.968     0.0    0.0  0.0       0.0      81.0  0\n",
       "210          1.266     0.0    1.0  0.0       0.0     533.0  1\n",
       "211          4.961     0.0    0.0  0.0       0.0     952.0  1\n",
       "212          1.281     0.0    1.0  0.0       0.0       6.0  0\n",
       "213          1.260     0.0    0.0  0.0       0.0     372.0  1\n",
       "214          4.858     0.0    1.0  0.0       0.0     607.0  1\n",
       "215          1.778     1.0    0.0  0.0       0.0     377.0  1\n",
       "216          1.268     0.0    0.0  0.0       0.0     166.0  1\n",
       "217          4.963     0.0    0.0  0.0       0.0     458.0  1\n",
       "218          1.264     0.0    1.0  1.0       0.0     397.0  1\n",
       "219          1.281     0.0    1.0  0.0       0.0      34.0  0\n",
       "220          0.739     0.0    0.0  2.0       0.0     233.0  0\n",
       "221          1.046     0.0    0.0  0.0       0.0     238.0  1\n",
       "\n",
       "[222 rows x 7 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Coverting the outcome variable into 1s and 0s again. \n",
    "data_test['y'] = data_test['y'].map({'yes':1, 'no':0})\n",
    "data_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Declare the dependent and the independent variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test = data_test['y']\n",
    "# We already declared a list called 'estimators' that holds all relevant estimators for our model. \n",
    "X1_test = data_test[estimators]\n",
    "X_test = sm.add_constant(X1_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Determine the test confusion matrix and the test accuracy and compare them with the train confusion matrix and the train accuracy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[93., 18.],\n",
       "        [13., 98.]]), 0.8603603603603603)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Determine the Confusion Matrix and the accuracy of the model with the new data. Note that the model itself stays the same (results_logit).\n",
    "# test accuracy\n",
    "confusion_matrix(X_test, y_test, results_logit)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[218.,  41.],\n",
       "        [ 30., 229.]]), 0.862934362934363)"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compare these values to the Confusion Matrix and the accuracy of the model with the old data.\n",
    "# train accuracy\n",
    "confusion_matrix(X_all,y, results_logit)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the test acccuracy we see a number which is a tiny but lower: 86.04%, compared to 86.29% for train accuracy. \n",
    "\n",
    "In general, we always expect the test accuracy to be lower than the train one. If the test accuracy is higher, this is just due to luck.\n",
    "\n",
    "Note that when you run the regression, you may get different numbers than us!"
   ]
  }
 ],
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