diff --git a/exercicios/para-casa/atividadeS13_comentada.ipynb b/exercicios/para-casa/atividadeS13_comentada.ipynb
new file mode 100644
index 0000000..d5c41df
--- /dev/null
+++ b/exercicios/para-casa/atividadeS13_comentada.ipynb
@@ -0,0 +1,1259 @@
+{
+  "cells": [
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "metadata": {
+        "id": "wO2h1xQEZaEQ"
+      },
+      "outputs": [],
+      "source": [
+        "import pandas as pd\n",
+        "import numpy as np\n",
+        "import matplotlib.pyplot as plt\n",
+        "import scipy.stats as stats\n",
+        "from scipy.stats import norm\n",
+        "from statsmodels.stats.proportion import proportions_ztest"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 52,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 444
+        },
+        "id": "ZHL0Rpf2aJnI",
+        "outputId": "4acb0691-9187-460f-81bf-ed3cda2627d1"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 2392,\n  \"fields\": [\n    {\n      \"column\": \"StudentID\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 690,\n        \"min\": 1001,\n        \"max\": 3392,\n        \"num_unique_values\": 2392,\n        \"samples\": [\n          2005,\n          1197,\n          3343\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 15,\n        \"max\": 18,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          18,\n          16,\n          17\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ethnicity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 3,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          2,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ParentalEducation\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 4,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"StudyTimeWeekly\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5.652774235860264,\n        \"min\": 0.001056538645936,\n        \"max\": 19.97809399526153,\n        \"num_unique_values\": 2392,\n        \"samples\": [\n          0.1357634804717955,\n          1.9899245236127627\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Absences\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8,\n        \"min\": 0,\n        \"max\": 29,\n        \"num_unique_values\": 30,\n        \"samples\": [\n          18,\n          25\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Tutoring\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ParentalSupport\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 4,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Extracurricular\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Sports\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Music\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Volunteering\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"GPA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.9151558203249592,\n        \"min\": 0.0,\n        \"max\": 4.0,\n        \"num_unique_values\": 2371,\n        \"samples\": [\n          3.3104012689001965,\n          3.4577117259752934\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"GradeClass\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1.2339075602260876,\n        \"min\": 0.0,\n        \"max\": 4.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1.0,\n          0.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+              "type": "dataframe",
+              "variable_name": "df"
+            },
+            "text/html": [
+              "\n",
+              "  <div id=\"df-f6c89549-1526-4f65-a953-1d56fde6bdfe\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>StudentID</th>\n",
+              "      <th>Age</th>\n",
+              "      <th>Gender</th>\n",
+              "      <th>Ethnicity</th>\n",
+              "      <th>ParentalEducation</th>\n",
+              "      <th>StudyTimeWeekly</th>\n",
+              "      <th>Absences</th>\n",
+              "      <th>Tutoring</th>\n",
+              "      <th>ParentalSupport</th>\n",
+              "      <th>Extracurricular</th>\n",
+              "      <th>Sports</th>\n",
+              "      <th>Music</th>\n",
+              "      <th>Volunteering</th>\n",
+              "      <th>GPA</th>\n",
+              "      <th>GradeClass</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>1001</td>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>19.833723</td>\n",
+              "      <td>7</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2.929196</td>\n",
+              "      <td>2.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>1002</td>\n",
+              "      <td>18</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>15.408756</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3.042915</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>1003</td>\n",
+              "      <td>15</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>4.210570</td>\n",
+              "      <td>26</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0.112602</td>\n",
+              "      <td>4.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>1004</td>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3</td>\n",
+              "      <td>10.028829</td>\n",
+              "      <td>14</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2.054218</td>\n",
+              "      <td>3.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>1005</td>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>4.672495</td>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1.288061</td>\n",
+              "      <td>4.0</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",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2387</th>\n",
+              "      <td>3388</td>\n",
+              "      <td>18</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3</td>\n",
+              "      <td>10.680555</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3.455509</td>\n",
+              "      <td>0.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2388</th>\n",
+              "      <td>3389</td>\n",
+              "      <td>17</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>7.583217</td>\n",
+              "      <td>4</td>\n",
+              "      <td>1</td>\n",
+              "      <td>4</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3.279150</td>\n",
+              "      <td>4.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2389</th>\n",
+              "      <td>3390</td>\n",
+              "      <td>16</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>6.805500</td>\n",
+              "      <td>20</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1.142333</td>\n",
+              "      <td>2.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2390</th>\n",
+              "      <td>3391</td>\n",
+              "      <td>16</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>12.416653</td>\n",
+              "      <td>17</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1.803297</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2391</th>\n",
+              "      <td>3392</td>\n",
+              "      <td>16</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>17.819907</td>\n",
+              "      <td>13</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>2.140014</td>\n",
+              "      <td>1.0</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>2392 rows × 15 columns</p>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f6c89549-1526-4f65-a953-1d56fde6bdfe')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-f6c89549-1526-4f65-a953-1d56fde6bdfe button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-f6c89549-1526-4f65-a953-1d56fde6bdfe');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-e8b1ada4-8c24-48cd-9a26-a36e775bb582\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-e8b1ada4-8c24-48cd-9a26-a36e775bb582')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-e8b1ada4-8c24-48cd-9a26-a36e775bb582 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_6c03c764-9658-44ce-9f0e-6b2b720bf170\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_6c03c764-9658-44ce-9f0e-6b2b720bf170 button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "      StudentID  Age  Gender  Ethnicity  ParentalEducation  StudyTimeWeekly  \\\n",
+              "0          1001   17       1          0                  2        19.833723   \n",
+              "1          1002   18       0          0                  1        15.408756   \n",
+              "2          1003   15       0          2                  3         4.210570   \n",
+              "3          1004   17       1          0                  3        10.028829   \n",
+              "4          1005   17       1          0                  2         4.672495   \n",
+              "...         ...  ...     ...        ...                ...              ...   \n",
+              "2387       3388   18       1          0                  3        10.680555   \n",
+              "2388       3389   17       0          0                  1         7.583217   \n",
+              "2389       3390   16       1          0                  2         6.805500   \n",
+              "2390       3391   16       1          1                  0        12.416653   \n",
+              "2391       3392   16       1          0                  2        17.819907   \n",
+              "\n",
+              "      Absences  Tutoring  ParentalSupport  Extracurricular  Sports  Music  \\\n",
+              "0            7         1                2                0       0      1   \n",
+              "1            0         0                1                0       0      0   \n",
+              "2           26         0                2                0       0      0   \n",
+              "3           14         0                3                1       0      0   \n",
+              "4           17         1                3                0       0      0   \n",
+              "...        ...       ...              ...              ...     ...    ...   \n",
+              "2387         2         0                4                1       0      0   \n",
+              "2388         4         1                4                0       1      0   \n",
+              "2389        20         0                2                0       0      0   \n",
+              "2390        17         0                2                0       1      1   \n",
+              "2391        13         0                2                0       0      0   \n",
+              "\n",
+              "      Volunteering       GPA  GradeClass  \n",
+              "0                0  2.929196         2.0  \n",
+              "1                0  3.042915         1.0  \n",
+              "2                0  0.112602         4.0  \n",
+              "3                0  2.054218         3.0  \n",
+              "4                0  1.288061         4.0  \n",
+              "...            ...       ...         ...  \n",
+              "2387             0  3.455509         0.0  \n",
+              "2388             0  3.279150         4.0  \n",
+              "2389             1  1.142333         2.0  \n",
+              "2390             0  1.803297         1.0  \n",
+              "2391             1  2.140014         1.0  \n",
+              "\n",
+              "[2392 rows x 15 columns]"
+            ]
+          },
+          "execution_count": 52,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df = pd.read_csv('Student_performance_data _.csv')\n",
+        "df"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 9,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "EjkkUnSwbLfL",
+        "outputId": "8214065b-346e-4db0-a5f3-19c00b9d5e38"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "Index(['StudentID', 'Age', 'Gender', 'Ethnicity', 'ParentalEducation',\n",
+              "       'StudyTimeWeekly', 'Absences', 'Tutoring', 'ParentalSupport',\n",
+              "       'Extracurricular', 'Sports', 'Music', 'Volunteering', 'GPA',\n",
+              "       'GradeClass'],\n",
+              "      dtype='object')"
+            ]
+          },
+          "execution_count": 9,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df.columns"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 20,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 424
+        },
+        "id": "ihLqa5jQcCZV",
+        "outputId": "15367767-0d2a-492a-853c-83e0fc85c2ca"
+      },
+      "outputs": [
+        {
+          "data": {
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 2392,\n  \"fields\": [\n    {\n      \"column\": \"Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 15,\n        \"max\": 18,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          18,\n          16,\n          17\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Gender\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0,\n        \"min\": 0,\n        \"max\": 1,\n        \"num_unique_values\": 2,\n        \"samples\": [\n          0,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ethnicity\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 3,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          2,\n          3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ParentalEducation\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 0,\n        \"max\": 4,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1,\n          0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"GPA\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.9151558203249592,\n        \"min\": 0.0,\n        \"max\": 4.0,\n        \"num_unique_values\": 2371,\n        \"samples\": [\n          3.3104012689001965,\n          3.4577117259752934\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}",
+              "type": "dataframe",
+              "variable_name": "df"
+            },
+            "text/html": [
+              "\n",
+              "  <div id=\"df-8b879888-d1d6-41cf-9d0f-f64a095a6493\" class=\"colab-df-container\">\n",
+              "    <div>\n",
+              "<style scoped>\n",
+              "    .dataframe tbody tr th:only-of-type {\n",
+              "        vertical-align: middle;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe tbody tr th {\n",
+              "        vertical-align: top;\n",
+              "    }\n",
+              "\n",
+              "    .dataframe thead th {\n",
+              "        text-align: right;\n",
+              "    }\n",
+              "</style>\n",
+              "<table border=\"1\" class=\"dataframe\">\n",
+              "  <thead>\n",
+              "    <tr style=\"text-align: right;\">\n",
+              "      <th></th>\n",
+              "      <th>Age</th>\n",
+              "      <th>Gender</th>\n",
+              "      <th>Ethnicity</th>\n",
+              "      <th>ParentalEducation</th>\n",
+              "      <th>GPA</th>\n",
+              "    </tr>\n",
+              "  </thead>\n",
+              "  <tbody>\n",
+              "    <tr>\n",
+              "      <th>0</th>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2.929196</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>1</th>\n",
+              "      <td>18</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3.042915</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2</th>\n",
+              "      <td>15</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>3</td>\n",
+              "      <td>0.112602</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>3</th>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3</td>\n",
+              "      <td>2.054218</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>4</th>\n",
+              "      <td>17</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1.288061</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>...</th>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "      <td>...</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2387</th>\n",
+              "      <td>18</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>3</td>\n",
+              "      <td>3.455509</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2388</th>\n",
+              "      <td>17</td>\n",
+              "      <td>0</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1</td>\n",
+              "      <td>3.279150</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2389</th>\n",
+              "      <td>16</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>1.142333</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2390</th>\n",
+              "      <td>16</td>\n",
+              "      <td>1</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>1.803297</td>\n",
+              "    </tr>\n",
+              "    <tr>\n",
+              "      <th>2391</th>\n",
+              "      <td>16</td>\n",
+              "      <td>1</td>\n",
+              "      <td>0</td>\n",
+              "      <td>2</td>\n",
+              "      <td>2.140014</td>\n",
+              "    </tr>\n",
+              "  </tbody>\n",
+              "</table>\n",
+              "<p>2392 rows × 5 columns</p>\n",
+              "</div>\n",
+              "    <div class=\"colab-df-buttons\">\n",
+              "\n",
+              "  <div class=\"colab-df-container\">\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8b879888-d1d6-41cf-9d0f-f64a095a6493')\"\n",
+              "            title=\"Convert this dataframe to an interactive table.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
+              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "\n",
+              "  <style>\n",
+              "    .colab-df-container {\n",
+              "      display:flex;\n",
+              "      gap: 12px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert {\n",
+              "      background-color: #E8F0FE;\n",
+              "      border: none;\n",
+              "      border-radius: 50%;\n",
+              "      cursor: pointer;\n",
+              "      display: none;\n",
+              "      fill: #1967D2;\n",
+              "      height: 32px;\n",
+              "      padding: 0 0 0 0;\n",
+              "      width: 32px;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-convert:hover {\n",
+              "      background-color: #E2EBFA;\n",
+              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "      fill: #174EA6;\n",
+              "    }\n",
+              "\n",
+              "    .colab-df-buttons div {\n",
+              "      margin-bottom: 4px;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert {\n",
+              "      background-color: #3B4455;\n",
+              "      fill: #D2E3FC;\n",
+              "    }\n",
+              "\n",
+              "    [theme=dark] .colab-df-convert:hover {\n",
+              "      background-color: #434B5C;\n",
+              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "      fill: #FFFFFF;\n",
+              "    }\n",
+              "  </style>\n",
+              "\n",
+              "    <script>\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#df-8b879888-d1d6-41cf-9d0f-f64a095a6493 button.colab-df-convert');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      async function convertToInteractive(key) {\n",
+              "        const element = document.querySelector('#df-8b879888-d1d6-41cf-9d0f-f64a095a6493');\n",
+              "        const dataTable =\n",
+              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
+              "                                                    [key], {});\n",
+              "        if (!dataTable) return;\n",
+              "\n",
+              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
+              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
+              "          + ' to learn more about interactive tables.';\n",
+              "        element.innerHTML = '';\n",
+              "        dataTable['output_type'] = 'display_data';\n",
+              "        await google.colab.output.renderOutput(dataTable, element);\n",
+              "        const docLink = document.createElement('div');\n",
+              "        docLink.innerHTML = docLinkHtml;\n",
+              "        element.appendChild(docLink);\n",
+              "      }\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "\n",
+              "<div id=\"df-eb025789-b18f-45a2-8000-bf1a6ab61f17\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-eb025789-b18f-45a2-8000-bf1a6ab61f17')\"\n",
+              "            title=\"Suggest charts\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "     width=\"24px\">\n",
+              "    <g>\n",
+              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
+              "    </g>\n",
+              "</svg>\n",
+              "  </button>\n",
+              "\n",
+              "<style>\n",
+              "  .colab-df-quickchart {\n",
+              "      --bg-color: #E8F0FE;\n",
+              "      --fill-color: #1967D2;\n",
+              "      --hover-bg-color: #E2EBFA;\n",
+              "      --hover-fill-color: #174EA6;\n",
+              "      --disabled-fill-color: #AAA;\n",
+              "      --disabled-bg-color: #DDD;\n",
+              "  }\n",
+              "\n",
+              "  [theme=dark] .colab-df-quickchart {\n",
+              "      --bg-color: #3B4455;\n",
+              "      --fill-color: #D2E3FC;\n",
+              "      --hover-bg-color: #434B5C;\n",
+              "      --hover-fill-color: #FFFFFF;\n",
+              "      --disabled-bg-color: #3B4455;\n",
+              "      --disabled-fill-color: #666;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart {\n",
+              "    background-color: var(--bg-color);\n",
+              "    border: none;\n",
+              "    border-radius: 50%;\n",
+              "    cursor: pointer;\n",
+              "    display: none;\n",
+              "    fill: var(--fill-color);\n",
+              "    height: 32px;\n",
+              "    padding: 0;\n",
+              "    width: 32px;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart:hover {\n",
+              "    background-color: var(--hover-bg-color);\n",
+              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "    fill: var(--button-hover-fill-color);\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-quickchart-complete:disabled,\n",
+              "  .colab-df-quickchart-complete:disabled:hover {\n",
+              "    background-color: var(--disabled-bg-color);\n",
+              "    fill: var(--disabled-fill-color);\n",
+              "    box-shadow: none;\n",
+              "  }\n",
+              "\n",
+              "  .colab-df-spinner {\n",
+              "    border: 2px solid var(--fill-color);\n",
+              "    border-color: transparent;\n",
+              "    border-bottom-color: var(--fill-color);\n",
+              "    animation:\n",
+              "      spin 1s steps(1) infinite;\n",
+              "  }\n",
+              "\n",
+              "  @keyframes spin {\n",
+              "    0% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "      border-left-color: var(--fill-color);\n",
+              "    }\n",
+              "    20% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    30% {\n",
+              "      border-color: transparent;\n",
+              "      border-left-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    40% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-top-color: var(--fill-color);\n",
+              "    }\n",
+              "    60% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "    }\n",
+              "    80% {\n",
+              "      border-color: transparent;\n",
+              "      border-right-color: var(--fill-color);\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "    90% {\n",
+              "      border-color: transparent;\n",
+              "      border-bottom-color: var(--fill-color);\n",
+              "    }\n",
+              "  }\n",
+              "</style>\n",
+              "\n",
+              "  <script>\n",
+              "    async function quickchart(key) {\n",
+              "      const quickchartButtonEl =\n",
+              "        document.querySelector('#' + key + ' button');\n",
+              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
+              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
+              "      try {\n",
+              "        const charts = await google.colab.kernel.invokeFunction(\n",
+              "            'suggestCharts', [key], {});\n",
+              "      } catch (error) {\n",
+              "        console.error('Error during call to suggestCharts:', error);\n",
+              "      }\n",
+              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
+              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
+              "    }\n",
+              "    (() => {\n",
+              "      let quickchartButtonEl =\n",
+              "        document.querySelector('#df-eb025789-b18f-45a2-8000-bf1a6ab61f17 button');\n",
+              "      quickchartButtonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "    })();\n",
+              "  </script>\n",
+              "</div>\n",
+              "\n",
+              "  <div id=\"id_1cd99aaa-a167-422c-aa40-8eaebe330730\">\n",
+              "    <style>\n",
+              "      .colab-df-generate {\n",
+              "        background-color: #E8F0FE;\n",
+              "        border: none;\n",
+              "        border-radius: 50%;\n",
+              "        cursor: pointer;\n",
+              "        display: none;\n",
+              "        fill: #1967D2;\n",
+              "        height: 32px;\n",
+              "        padding: 0 0 0 0;\n",
+              "        width: 32px;\n",
+              "      }\n",
+              "\n",
+              "      .colab-df-generate:hover {\n",
+              "        background-color: #E2EBFA;\n",
+              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
+              "        fill: #174EA6;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate {\n",
+              "        background-color: #3B4455;\n",
+              "        fill: #D2E3FC;\n",
+              "      }\n",
+              "\n",
+              "      [theme=dark] .colab-df-generate:hover {\n",
+              "        background-color: #434B5C;\n",
+              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
+              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
+              "        fill: #FFFFFF;\n",
+              "      }\n",
+              "    </style>\n",
+              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('df')\"\n",
+              "            title=\"Generate code using this dataframe.\"\n",
+              "            style=\"display:none;\">\n",
+              "\n",
+              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
+              "       width=\"24px\">\n",
+              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
+              "  </svg>\n",
+              "    </button>\n",
+              "    <script>\n",
+              "      (() => {\n",
+              "      const buttonEl =\n",
+              "        document.querySelector('#id_1cd99aaa-a167-422c-aa40-8eaebe330730 button.colab-df-generate');\n",
+              "      buttonEl.style.display =\n",
+              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
+              "\n",
+              "      buttonEl.onclick = () => {\n",
+              "        google.colab.notebook.generateWithVariable('df');\n",
+              "      }\n",
+              "      })();\n",
+              "    </script>\n",
+              "  </div>\n",
+              "\n",
+              "    </div>\n",
+              "  </div>\n"
+            ],
+            "text/plain": [
+              "      Age  Gender  Ethnicity  ParentalEducation       GPA\n",
+              "0      17       1          0                  2  2.929196\n",
+              "1      18       0          0                  1  3.042915\n",
+              "2      15       0          2                  3  0.112602\n",
+              "3      17       1          0                  3  2.054218\n",
+              "4      17       1          0                  2  1.288061\n",
+              "...   ...     ...        ...                ...       ...\n",
+              "2387   18       1          0                  3  3.455509\n",
+              "2388   17       0          0                  1  3.279150\n",
+              "2389   16       1          0                  2  1.142333\n",
+              "2390   16       1          1                  0  1.803297\n",
+              "2391   16       1          0                  2  2.140014\n",
+              "\n",
+              "[2392 rows x 5 columns]"
+            ]
+          },
+          "execution_count": 20,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df = df[['Age', 'Gender', 'Ethnicity', 'ParentalEducation','GPA']]\n",
+        "df"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 22,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "Le5xnfN_c3Am",
+        "outputId": "58abf916-740c-49a0-d1bc-a50a4786dc6a"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "0       2.929196\n",
+              "1       3.042915\n",
+              "2       0.112602\n",
+              "3       2.054218\n",
+              "4       1.288061\n",
+              "          ...   \n",
+              "2387    3.455509\n",
+              "2388    3.279150\n",
+              "2389    1.142333\n",
+              "2390    1.803297\n",
+              "2391    2.140014\n",
+              "Name: GPA, Length: 2392, dtype: float64"
+            ]
+          },
+          "execution_count": 22,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df_gpa = df.loc[:, 'GPA']\n",
+        "df_gpa"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 18,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "tpQLEMMmd-gi",
+        "outputId": "97175b20-3391-46d7-bae8-9fc4b03b129e"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "0       2.93\n",
+              "1       3.04\n",
+              "2       0.11\n",
+              "3       2.05\n",
+              "4       1.29\n",
+              "        ... \n",
+              "2387    3.46\n",
+              "2388    3.28\n",
+              "2389    1.14\n",
+              "2390    1.80\n",
+              "2391    2.14\n",
+              "Name: GPA, Length: 2392, dtype: float64"
+            ]
+          },
+          "execution_count": 18,
+          "metadata": {},
+          "output_type": "execute_result"
+        }
+      ],
+      "source": [
+        "df_gpa = df_gpa.round(2)\n",
+        "df_gpa"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "BCPdSouEcZnd"
+      },
+      "source": [
+        "# **Teste T-Student:**\n",
+        "Hipótese nula (H0): a média das notas (GPA) é igual a 2.0.\n",
+        "\n",
+        "Hipótese alternativa (H1): a média das notas (GPA) é diferente de 2.0 (two-sided - maior ou menor)\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 53,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "IHOMfQQXi2XW",
+        "outputId": "ca59e807-bbc5-44b5-c348-134067accf57"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Média populacional: 2\n",
+            "Média amostral: 1.9061863027265407\n",
+            "Estatística t: -5.013624381766575\n",
+            "Valor p: 5.733044870766935e-07\n"
+          ]
+        }
+      ],
+      "source": [
+        "h0 = 2\n",
+        "h1 = 'two-sided'\n",
+        "media_gpa = df_gpa.mean()\n",
+        "print('Média populacional:', h0)\n",
+        "print('Média amostral:', media_gpa)\n",
+        "t_statistic, p_value = stats.ttest_1samp(df_gpa, popmean= h0)\n",
+        "\n",
+        "print('Estatística t:', t_statistic)\n",
+        "print('Valor p:', p_value)\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 48,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "a_47OKgympb0",
+        "outputId": "e54aa321-0633-4a62-f93b-b91d5d896809"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Rejeitamos a hipótese nula. A média do GPA dos alunos é significativamente diferente de 2.\n"
+          ]
+        }
+      ],
+      "source": [
+        "if p_value <= 0.05:\n",
+        "    print(f\"Rejeitamos a hipótese nula. A média do GPA dos alunos é significativamente diferente de {h0}.\")\n",
+        "else:\n",
+        "    print(f\"Não rejeitamos a hipótese nula. Não há evidências suficientes para concluir que a média do GPA dos alunos é diferente de {h0}.\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 47,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "EIKUbCznlfL-",
+        "outputId": "617306f0-969e-4cc5-a953-0416d94a1d00"
+      },
+      "outputs": [
+        {
+          "data": {
+            "image/png": "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",
+            "text/plain": [
+              "<Figure size 640x480 with 1 Axes>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "plt.hist(df_gpa, bins=10, edgecolor='black')\n",
+        "plt.xlabel('GPA')\n",
+        "plt.ylabel('Frequência')\n",
+        "plt.title('Distribuição de Frequências')\n",
+        "\n",
+        "plt.axvline(h0, color='red', linestyle='--', label='Média Populacional (2.0)')\n",
+        "plt.axvline(df_gpa.mean(), color='blue', linestyle='-', label='Média Amostral')\n",
+        "\n",
+        "plt.legend()\n",
+        "plt.show()"
+      ]
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}
diff --git a/exercicios/para-casa/relatorioS13.md b/exercicios/para-casa/relatorioS13.md
new file mode 100644
index 0000000..e3440e2
--- /dev/null
+++ b/exercicios/para-casa/relatorioS13.md
@@ -0,0 +1,42 @@
+**Título:** Analisando a média de notas (Grade Point Average - GPA) de estudantes utilizando o Teste T-Student
+
+**1. Introdução**
+Apresentamos neste relatório uma análise sobre a média de notas de estudantes de 15 até 18 anos, utilizando dados coletados em uma pesquisa. Tal análise busca responder à seguinte pergunta: **A média de notas dos estudantes é igual a 2.0?**. O valor 2.0 é considerado como conceito 'D', abaixo do regular, conforme apresentado na escala de notas de 0 a 4, a seguir:
+
+0: 'A' (GPA >= 3.5)
+1: 'B' (3.0 <= GPA < 3.5)
+2: 'C' (2.5 <= GPA < 3.0)
+3: 'D' (2.0 <= GPA < 2.5)
+4: 'F' (GPA < 2.0)
+
+Compreender em qual faixa de notas se encontram a maioria dos estudantes é fundamental para saber se as estratégias educacionais atuais são funcionais.
+
+**2. Materiais e métodos**
+Para responder à pergunta norteadora da pesquisa, utilizamos:
+*   Conjunto de dados: disponível na plataforma Kaggle, utilizamos o *dataset* denominado *Students Perfomance Dataset*. Os dados apresentam diversas informações sobre os 2392 estudantes do Ensino Médio estadounidense (*High School*), tais como gênero, idade, etnia, entre outros. 
+*   Teste de Hipóteses: para analisar as informações obtidas na coluna GPA da tabela, utilizamos o Teste T-Student, que indica a diferença entre a média real dos dados e a média estipulada pela pergunta inicial.
+*   Análise: utilizamos a biblioteca **scipy.stats** do Python para desenvolver o Teste T-Student. Os passos da análise incluem: 
+
+        a. Importar as bibliotecas necessárias.
+        b. Carregar o conjunto de dados.
+        c. Criar uma tabela destacando apenas as médias GPA.
+        d. Realizar o Teste T-Student.       
+        e. Interpretar os resultados do teste, incluindo o valor p e a estatística T.
+  
+**3. Resultados**
+Dentre o cálculo de algumas medidas descritivas, obtivemos o valor da média das amostras:
+*   Média amostral: 1.9061863027265407
+
+Já o Teste T-Student retornou os seguintes resultados:
+
+*   Estatística T: -5.013624381766575
+*   Valor p: 5.733044870766935e-07
+
+
+**4. Resultados**
+O valor p obtido (5.733044870766935e-07) é menor que o nível de significância usual de 0.05. Isso indica que há evidências suficientes para rejeitar a hipótese nula de que a média de GPA seja igual a 2.0. 
+É importante ressaltar que não consideramos apenas o Teste T-Student para analisar o resultado. Calculamos a média dos dados por meio da função **.mean()**, que confirmou que o valor da média não é 2.0, mas sim aproximadamente 1.91. 
+
+**5. Conclusão**
+A análise desenvolvida com o Teste T-Student sugere que a média proposta na hipótese (2.0) difere da média real das amostras (1.91), ou seja, a maioria das médias dos estudantes é considerada como conceito F. Dessa maneira, compreendemos que as estratégias educacionais precisam ser aprimoradas, a fim de auxiliar os estudantes a se desenvolverem de forma mais satisfatória e, consequentemente, aumentar a média GPA. 
+