6.questionnaire_bayes_factor.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "# Copyright 2022 by the author(s) of CHI2023 submission \"Short-Form\n",
    "# Videos Degrade Our Capacity to Retain Intentions: Effect of Context\n",
    "# Switching On Prospective Memory\". All rights reserved.\n",
    "#\n",
    "# Use of this source code is governed by a GPLv3 license that\n",
    "# can be found in the LICENSE file.\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "library(BayesFactor)\n",
    "library(report)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 60 × 10</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>folder_id</th><th scope=col>interrupt</th><th scope=col>SUQ</th><th scope=col>BSMARS</th><th scope=col>META_CC</th><th scope=col>META_POS</th><th scope=col>META_CSC</th><th scope=col>META_NEG</th><th scope=col>META_NC</th><th scope=col>ENGAGE</th></tr>\n",
       "\t<tr><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>101</td><td>rest   </td><td>4.5</td><td>15</td><td>14</td><td>21</td><td>16</td><td>15</td><td> 8</td><td>5</td></tr>\n",
       "\t<tr><td>102</td><td>rest   </td><td>4.9</td><td> 6</td><td>10</td><td>15</td><td>20</td><td>11</td><td> 9</td><td>3</td></tr>\n",
       "\t<tr><td>103</td><td>rest   </td><td>1.9</td><td> 9</td><td>11</td><td>12</td><td>16</td><td>11</td><td>11</td><td>4</td></tr>\n",
       "\t<tr><td>104</td><td>rest   </td><td>3.6</td><td> 8</td><td> 9</td><td>12</td><td>12</td><td>11</td><td>12</td><td>5</td></tr>\n",
       "\t<tr><td>105</td><td>rest   </td><td>4.4</td><td> 8</td><td>11</td><td>11</td><td>11</td><td> 7</td><td> 6</td><td>1</td></tr>\n",
       "\t<tr><td>106</td><td>rest   </td><td>4.3</td><td>13</td><td> 9</td><td>11</td><td>13</td><td> 7</td><td> 8</td><td>3</td></tr>\n",
       "\t<tr><td>107</td><td>rest   </td><td>2.1</td><td> 5</td><td>11</td><td> 8</td><td>14</td><td> 8</td><td> 9</td><td>3</td></tr>\n",
       "\t<tr><td>108</td><td>rest   </td><td>6.1</td><td>17</td><td> 9</td><td> 9</td><td>20</td><td>20</td><td>17</td><td>5</td></tr>\n",
       "\t<tr><td>109</td><td>rest   </td><td>3.6</td><td> 5</td><td>15</td><td>17</td><td>16</td><td>17</td><td>10</td><td>1</td></tr>\n",
       "\t<tr><td>110</td><td>rest   </td><td>4.7</td><td>11</td><td>18</td><td>15</td><td>20</td><td>15</td><td>12</td><td>4</td></tr>\n",
       "\t<tr><td>111</td><td>rest   </td><td>3.8</td><td> 6</td><td> 7</td><td> 5</td><td>14</td><td>11</td><td>12</td><td>1</td></tr>\n",
       "\t<tr><td>112</td><td>rest   </td><td>4.2</td><td>14</td><td>12</td><td>14</td><td>12</td><td>18</td><td>17</td><td>4</td></tr>\n",
       "\t<tr><td>113</td><td>rest   </td><td>3.9</td><td>18</td><td>17</td><td>16</td><td>14</td><td>17</td><td>10</td><td>4</td></tr>\n",
       "\t<tr><td>114</td><td>rest   </td><td>1.6</td><td> 8</td><td>11</td><td> 8</td><td>21</td><td>18</td><td>15</td><td>3</td></tr>\n",
       "\t<tr><td>115</td><td>rest   </td><td>3.4</td><td> 7</td><td>10</td><td> 6</td><td>24</td><td>11</td><td>14</td><td>1</td></tr>\n",
       "\t<tr><td>201</td><td>tiktok </td><td>5.5</td><td>15</td><td>20</td><td>15</td><td>16</td><td>20</td><td>13</td><td>2</td></tr>\n",
       "\t<tr><td>202</td><td>tiktok </td><td>6.8</td><td>16</td><td>17</td><td>21</td><td>11</td><td>23</td><td>19</td><td>3</td></tr>\n",
       "\t<tr><td>203</td><td>tiktok </td><td>5.4</td><td>17</td><td>13</td><td> 7</td><td>13</td><td>11</td><td> 7</td><td>3</td></tr>\n",
       "\t<tr><td>204</td><td>tiktok </td><td>4.8</td><td>12</td><td>12</td><td>11</td><td>17</td><td>16</td><td> 8</td><td>2</td></tr>\n",
       "\t<tr><td>205</td><td>tiktok </td><td>3.8</td><td>11</td><td>16</td><td>18</td><td>24</td><td>17</td><td>11</td><td>5</td></tr>\n",
       "\t<tr><td>206</td><td>tiktok </td><td>4.0</td><td>10</td><td> 7</td><td>13</td><td>13</td><td>12</td><td> 9</td><td>4</td></tr>\n",
       "\t<tr><td>207</td><td>tiktok </td><td>4.9</td><td>12</td><td> 8</td><td>14</td><td>17</td><td>13</td><td>10</td><td>4</td></tr>\n",
       "\t<tr><td>208</td><td>tiktok </td><td>4.5</td><td> 7</td><td>16</td><td>14</td><td>19</td><td>16</td><td> 8</td><td>4</td></tr>\n",
       "\t<tr><td>209</td><td>tiktok </td><td>4.8</td><td>16</td><td>10</td><td> 8</td><td> 8</td><td>10</td><td>12</td><td>3</td></tr>\n",
       "\t<tr><td>210</td><td>tiktok </td><td>4.1</td><td> 5</td><td> 8</td><td> 6</td><td>15</td><td> 9</td><td>12</td><td>4</td></tr>\n",
       "\t<tr><td>211</td><td>tiktok </td><td>6.2</td><td>17</td><td>11</td><td>17</td><td>21</td><td>22</td><td>13</td><td>5</td></tr>\n",
       "\t<tr><td>212</td><td>tiktok </td><td>3.9</td><td>11</td><td>14</td><td>15</td><td>17</td><td>16</td><td>12</td><td>4</td></tr>\n",
       "\t<tr><td>213</td><td>tiktok </td><td>5.0</td><td>13</td><td>11</td><td>10</td><td>14</td><td>19</td><td>12</td><td>4</td></tr>\n",
       "\t<tr><td>214</td><td>tiktok </td><td>4.0</td><td>10</td><td> 8</td><td> 6</td><td>12</td><td>13</td><td> 6</td><td>2</td></tr>\n",
       "\t<tr><td>215</td><td>tiktok </td><td>3.6</td><td> 9</td><td> 9</td><td>11</td><td>18</td><td> 7</td><td> 6</td><td>2</td></tr>\n",
       "\t<tr><td>301</td><td>youtube</td><td>4.0</td><td> 7</td><td> 9</td><td>22</td><td>19</td><td> 7</td><td>12</td><td>5</td></tr>\n",
       "\t<tr><td>302</td><td>youtube</td><td>4.8</td><td>12</td><td>12</td><td>10</td><td>15</td><td>10</td><td>12</td><td>4</td></tr>\n",
       "\t<tr><td>303</td><td>youtube</td><td>3.7</td><td>14</td><td>11</td><td>12</td><td>16</td><td>16</td><td>12</td><td>3</td></tr>\n",
       "\t<tr><td>304</td><td>youtube</td><td>2.2</td><td> 9</td><td> 7</td><td>15</td><td>24</td><td>12</td><td>13</td><td>4</td></tr>\n",
       "\t<tr><td>305</td><td>youtube</td><td>5.2</td><td>16</td><td>16</td><td>15</td><td>12</td><td>15</td><td>13</td><td>5</td></tr>\n",
       "\t<tr><td>306</td><td>youtube</td><td>6.2</td><td>17</td><td>16</td><td>11</td><td>15</td><td>22</td><td>18</td><td>5</td></tr>\n",
       "\t<tr><td>307</td><td>youtube</td><td>3.8</td><td> 8</td><td> 9</td><td>14</td><td>14</td><td> 6</td><td> 7</td><td>5</td></tr>\n",
       "\t<tr><td>308</td><td>youtube</td><td>4.0</td><td>11</td><td> 8</td><td> 8</td><td>11</td><td>11</td><td>10</td><td>5</td></tr>\n",
       "\t<tr><td>309</td><td>youtube</td><td>4.9</td><td> 9</td><td>17</td><td>12</td><td>17</td><td> 9</td><td>10</td><td>5</td></tr>\n",
       "\t<tr><td>310</td><td>youtube</td><td>2.9</td><td>12</td><td>22</td><td>19</td><td>23</td><td>24</td><td>16</td><td>5</td></tr>\n",
       "\t<tr><td>311</td><td>youtube</td><td>5.6</td><td> 8</td><td>18</td><td>16</td><td>17</td><td>19</td><td>16</td><td>3</td></tr>\n",
       "\t<tr><td>312</td><td>youtube</td><td>5.2</td><td>16</td><td>17</td><td>16</td><td>13</td><td>17</td><td>13</td><td>4</td></tr>\n",
       "\t<tr><td>313</td><td>youtube</td><td>6.1</td><td>12</td><td>13</td><td>11</td><td>19</td><td>15</td><td>15</td><td>3</td></tr>\n",
       "\t<tr><td>314</td><td>youtube</td><td>4.2</td><td>11</td><td> 6</td><td> 6</td><td>16</td><td> 6</td><td>14</td><td>2</td></tr>\n",
       "\t<tr><td>315</td><td>youtube</td><td>4.2</td><td>17</td><td>12</td><td> 9</td><td>23</td><td>14</td><td>11</td><td>5</td></tr>\n",
       "\t<tr><td>401</td><td>twitter</td><td>4.9</td><td>10</td><td>15</td><td>13</td><td>19</td><td> 9</td><td> 6</td><td>4</td></tr>\n",
       "\t<tr><td>402</td><td>twitter</td><td>5.6</td><td> 7</td><td> 7</td><td>13</td><td>17</td><td> 7</td><td> 8</td><td>4</td></tr>\n",
       "\t<tr><td>403</td><td>twitter</td><td>4.5</td><td>12</td><td> 9</td><td>18</td><td>19</td><td>13</td><td>11</td><td>4</td></tr>\n",
       "\t<tr><td>404</td><td>twitter</td><td>6.0</td><td>10</td><td>10</td><td>21</td><td>24</td><td>18</td><td>19</td><td>5</td></tr>\n",
       "\t<tr><td>405</td><td>twitter</td><td>4.7</td><td>12</td><td> 9</td><td> 6</td><td>13</td><td>14</td><td> 6</td><td>2</td></tr>\n",
       "\t<tr><td>406</td><td>twitter</td><td>4.6</td><td> 8</td><td> 8</td><td> 6</td><td>18</td><td> 9</td><td>13</td><td>3</td></tr>\n",
       "\t<tr><td>407</td><td>twitter</td><td>3.2</td><td>10</td><td> 6</td><td>12</td><td>24</td><td>19</td><td>16</td><td>1</td></tr>\n",
       "\t<tr><td>408</td><td>twitter</td><td>3.5</td><td> 9</td><td>12</td><td> 8</td><td>14</td><td>14</td><td>11</td><td>4</td></tr>\n",
       "\t<tr><td>409</td><td>twitter</td><td>3.9</td><td> 8</td><td>13</td><td>16</td><td>21</td><td>14</td><td>10</td><td>4</td></tr>\n",
       "\t<tr><td>410</td><td>twitter</td><td>4.3</td><td>12</td><td>12</td><td> 7</td><td>22</td><td>15</td><td> 7</td><td>3</td></tr>\n",
       "\t<tr><td>411</td><td>twitter</td><td>4.1</td><td>14</td><td>14</td><td>11</td><td>20</td><td>11</td><td>12</td><td>2</td></tr>\n",
       "\t<tr><td>412</td><td>twitter</td><td>4.8</td><td> 7</td><td>12</td><td>10</td><td>14</td><td>15</td><td> 9</td><td>2</td></tr>\n",
       "\t<tr><td>413</td><td>twitter</td><td>6.2</td><td>16</td><td>12</td><td>20</td><td>17</td><td>19</td><td>15</td><td>4</td></tr>\n",
       "\t<tr><td>414</td><td>twitter</td><td>4.0</td><td>15</td><td>15</td><td>11</td><td>13</td><td> 8</td><td>15</td><td>3</td></tr>\n",
       "\t<tr><td>415</td><td>twitter</td><td>3.2</td><td>14</td><td>14</td><td>11</td><td>12</td><td>10</td><td>11</td><td>3</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 60 × 10\n",
       "\\begin{tabular}{llllllllll}\n",
       " folder\\_id & interrupt & SUQ & BSMARS & META\\_CC & META\\_POS & META\\_CSC & META\\_NEG & META\\_NC & ENGAGE\\\\\n",
       " <int> & <chr> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <int>\\\\\n",
       "\\hline\n",
       "\t 101 & rest    & 4.5 & 15 & 14 & 21 & 16 & 15 &  8 & 5\\\\\n",
       "\t 102 & rest    & 4.9 &  6 & 10 & 15 & 20 & 11 &  9 & 3\\\\\n",
       "\t 103 & rest    & 1.9 &  9 & 11 & 12 & 16 & 11 & 11 & 4\\\\\n",
       "\t 104 & rest    & 3.6 &  8 &  9 & 12 & 12 & 11 & 12 & 5\\\\\n",
       "\t 105 & rest    & 4.4 &  8 & 11 & 11 & 11 &  7 &  6 & 1\\\\\n",
       "\t 106 & rest    & 4.3 & 13 &  9 & 11 & 13 &  7 &  8 & 3\\\\\n",
       "\t 107 & rest    & 2.1 &  5 & 11 &  8 & 14 &  8 &  9 & 3\\\\\n",
       "\t 108 & rest    & 6.1 & 17 &  9 &  9 & 20 & 20 & 17 & 5\\\\\n",
       "\t 109 & rest    & 3.6 &  5 & 15 & 17 & 16 & 17 & 10 & 1\\\\\n",
       "\t 110 & rest    & 4.7 & 11 & 18 & 15 & 20 & 15 & 12 & 4\\\\\n",
       "\t 111 & rest    & 3.8 &  6 &  7 &  5 & 14 & 11 & 12 & 1\\\\\n",
       "\t 112 & rest    & 4.2 & 14 & 12 & 14 & 12 & 18 & 17 & 4\\\\\n",
       "\t 113 & rest    & 3.9 & 18 & 17 & 16 & 14 & 17 & 10 & 4\\\\\n",
       "\t 114 & rest    & 1.6 &  8 & 11 &  8 & 21 & 18 & 15 & 3\\\\\n",
       "\t 115 & rest    & 3.4 &  7 & 10 &  6 & 24 & 11 & 14 & 1\\\\\n",
       "\t 201 & tiktok  & 5.5 & 15 & 20 & 15 & 16 & 20 & 13 & 2\\\\\n",
       "\t 202 & tiktok  & 6.8 & 16 & 17 & 21 & 11 & 23 & 19 & 3\\\\\n",
       "\t 203 & tiktok  & 5.4 & 17 & 13 &  7 & 13 & 11 &  7 & 3\\\\\n",
       "\t 204 & tiktok  & 4.8 & 12 & 12 & 11 & 17 & 16 &  8 & 2\\\\\n",
       "\t 205 & tiktok  & 3.8 & 11 & 16 & 18 & 24 & 17 & 11 & 5\\\\\n",
       "\t 206 & tiktok  & 4.0 & 10 &  7 & 13 & 13 & 12 &  9 & 4\\\\\n",
       "\t 207 & tiktok  & 4.9 & 12 &  8 & 14 & 17 & 13 & 10 & 4\\\\\n",
       "\t 208 & tiktok  & 4.5 &  7 & 16 & 14 & 19 & 16 &  8 & 4\\\\\n",
       "\t 209 & tiktok  & 4.8 & 16 & 10 &  8 &  8 & 10 & 12 & 3\\\\\n",
       "\t 210 & tiktok  & 4.1 &  5 &  8 &  6 & 15 &  9 & 12 & 4\\\\\n",
       "\t 211 & tiktok  & 6.2 & 17 & 11 & 17 & 21 & 22 & 13 & 5\\\\\n",
       "\t 212 & tiktok  & 3.9 & 11 & 14 & 15 & 17 & 16 & 12 & 4\\\\\n",
       "\t 213 & tiktok  & 5.0 & 13 & 11 & 10 & 14 & 19 & 12 & 4\\\\\n",
       "\t 214 & tiktok  & 4.0 & 10 &  8 &  6 & 12 & 13 &  6 & 2\\\\\n",
       "\t 215 & tiktok  & 3.6 &  9 &  9 & 11 & 18 &  7 &  6 & 2\\\\\n",
       "\t 301 & youtube & 4.0 &  7 &  9 & 22 & 19 &  7 & 12 & 5\\\\\n",
       "\t 302 & youtube & 4.8 & 12 & 12 & 10 & 15 & 10 & 12 & 4\\\\\n",
       "\t 303 & youtube & 3.7 & 14 & 11 & 12 & 16 & 16 & 12 & 3\\\\\n",
       "\t 304 & youtube & 2.2 &  9 &  7 & 15 & 24 & 12 & 13 & 4\\\\\n",
       "\t 305 & youtube & 5.2 & 16 & 16 & 15 & 12 & 15 & 13 & 5\\\\\n",
       "\t 306 & youtube & 6.2 & 17 & 16 & 11 & 15 & 22 & 18 & 5\\\\\n",
       "\t 307 & youtube & 3.8 &  8 &  9 & 14 & 14 &  6 &  7 & 5\\\\\n",
       "\t 308 & youtube & 4.0 & 11 &  8 &  8 & 11 & 11 & 10 & 5\\\\\n",
       "\t 309 & youtube & 4.9 &  9 & 17 & 12 & 17 &  9 & 10 & 5\\\\\n",
       "\t 310 & youtube & 2.9 & 12 & 22 & 19 & 23 & 24 & 16 & 5\\\\\n",
       "\t 311 & youtube & 5.6 &  8 & 18 & 16 & 17 & 19 & 16 & 3\\\\\n",
       "\t 312 & youtube & 5.2 & 16 & 17 & 16 & 13 & 17 & 13 & 4\\\\\n",
       "\t 313 & youtube & 6.1 & 12 & 13 & 11 & 19 & 15 & 15 & 3\\\\\n",
       "\t 314 & youtube & 4.2 & 11 &  6 &  6 & 16 &  6 & 14 & 2\\\\\n",
       "\t 315 & youtube & 4.2 & 17 & 12 &  9 & 23 & 14 & 11 & 5\\\\\n",
       "\t 401 & twitter & 4.9 & 10 & 15 & 13 & 19 &  9 &  6 & 4\\\\\n",
       "\t 402 & twitter & 5.6 &  7 &  7 & 13 & 17 &  7 &  8 & 4\\\\\n",
       "\t 403 & twitter & 4.5 & 12 &  9 & 18 & 19 & 13 & 11 & 4\\\\\n",
       "\t 404 & twitter & 6.0 & 10 & 10 & 21 & 24 & 18 & 19 & 5\\\\\n",
       "\t 405 & twitter & 4.7 & 12 &  9 &  6 & 13 & 14 &  6 & 2\\\\\n",
       "\t 406 & twitter & 4.6 &  8 &  8 &  6 & 18 &  9 & 13 & 3\\\\\n",
       "\t 407 & twitter & 3.2 & 10 &  6 & 12 & 24 & 19 & 16 & 1\\\\\n",
       "\t 408 & twitter & 3.5 &  9 & 12 &  8 & 14 & 14 & 11 & 4\\\\\n",
       "\t 409 & twitter & 3.9 &  8 & 13 & 16 & 21 & 14 & 10 & 4\\\\\n",
       "\t 410 & twitter & 4.3 & 12 & 12 &  7 & 22 & 15 &  7 & 3\\\\\n",
       "\t 411 & twitter & 4.1 & 14 & 14 & 11 & 20 & 11 & 12 & 2\\\\\n",
       "\t 412 & twitter & 4.8 &  7 & 12 & 10 & 14 & 15 &  9 & 2\\\\\n",
       "\t 413 & twitter & 6.2 & 16 & 12 & 20 & 17 & 19 & 15 & 4\\\\\n",
       "\t 414 & twitter & 4.0 & 15 & 15 & 11 & 13 &  8 & 15 & 3\\\\\n",
       "\t 415 & twitter & 3.2 & 14 & 14 & 11 & 12 & 10 & 11 & 3\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 60 × 10\n",
       "\n",
       "| folder_id &lt;int&gt; | interrupt &lt;chr&gt; | SUQ &lt;dbl&gt; | BSMARS &lt;dbl&gt; | META_CC &lt;dbl&gt; | META_POS &lt;dbl&gt; | META_CSC &lt;dbl&gt; | META_NEG &lt;dbl&gt; | META_NC &lt;dbl&gt; | ENGAGE &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|\n",
       "| 101 | rest    | 4.5 | 15 | 14 | 21 | 16 | 15 |  8 | 5 |\n",
       "| 102 | rest    | 4.9 |  6 | 10 | 15 | 20 | 11 |  9 | 3 |\n",
       "| 103 | rest    | 1.9 |  9 | 11 | 12 | 16 | 11 | 11 | 4 |\n",
       "| 104 | rest    | 3.6 |  8 |  9 | 12 | 12 | 11 | 12 | 5 |\n",
       "| 105 | rest    | 4.4 |  8 | 11 | 11 | 11 |  7 |  6 | 1 |\n",
       "| 106 | rest    | 4.3 | 13 |  9 | 11 | 13 |  7 |  8 | 3 |\n",
       "| 107 | rest    | 2.1 |  5 | 11 |  8 | 14 |  8 |  9 | 3 |\n",
       "| 108 | rest    | 6.1 | 17 |  9 |  9 | 20 | 20 | 17 | 5 |\n",
       "| 109 | rest    | 3.6 |  5 | 15 | 17 | 16 | 17 | 10 | 1 |\n",
       "| 110 | rest    | 4.7 | 11 | 18 | 15 | 20 | 15 | 12 | 4 |\n",
       "| 111 | rest    | 3.8 |  6 |  7 |  5 | 14 | 11 | 12 | 1 |\n",
       "| 112 | rest    | 4.2 | 14 | 12 | 14 | 12 | 18 | 17 | 4 |\n",
       "| 113 | rest    | 3.9 | 18 | 17 | 16 | 14 | 17 | 10 | 4 |\n",
       "| 114 | rest    | 1.6 |  8 | 11 |  8 | 21 | 18 | 15 | 3 |\n",
       "| 115 | rest    | 3.4 |  7 | 10 |  6 | 24 | 11 | 14 | 1 |\n",
       "| 201 | tiktok  | 5.5 | 15 | 20 | 15 | 16 | 20 | 13 | 2 |\n",
       "| 202 | tiktok  | 6.8 | 16 | 17 | 21 | 11 | 23 | 19 | 3 |\n",
       "| 203 | tiktok  | 5.4 | 17 | 13 |  7 | 13 | 11 |  7 | 3 |\n",
       "| 204 | tiktok  | 4.8 | 12 | 12 | 11 | 17 | 16 |  8 | 2 |\n",
       "| 205 | tiktok  | 3.8 | 11 | 16 | 18 | 24 | 17 | 11 | 5 |\n",
       "| 206 | tiktok  | 4.0 | 10 |  7 | 13 | 13 | 12 |  9 | 4 |\n",
       "| 207 | tiktok  | 4.9 | 12 |  8 | 14 | 17 | 13 | 10 | 4 |\n",
       "| 208 | tiktok  | 4.5 |  7 | 16 | 14 | 19 | 16 |  8 | 4 |\n",
       "| 209 | tiktok  | 4.8 | 16 | 10 |  8 |  8 | 10 | 12 | 3 |\n",
       "| 210 | tiktok  | 4.1 |  5 |  8 |  6 | 15 |  9 | 12 | 4 |\n",
       "| 211 | tiktok  | 6.2 | 17 | 11 | 17 | 21 | 22 | 13 | 5 |\n",
       "| 212 | tiktok  | 3.9 | 11 | 14 | 15 | 17 | 16 | 12 | 4 |\n",
       "| 213 | tiktok  | 5.0 | 13 | 11 | 10 | 14 | 19 | 12 | 4 |\n",
       "| 214 | tiktok  | 4.0 | 10 |  8 |  6 | 12 | 13 |  6 | 2 |\n",
       "| 215 | tiktok  | 3.6 |  9 |  9 | 11 | 18 |  7 |  6 | 2 |\n",
       "| 301 | youtube | 4.0 |  7 |  9 | 22 | 19 |  7 | 12 | 5 |\n",
       "| 302 | youtube | 4.8 | 12 | 12 | 10 | 15 | 10 | 12 | 4 |\n",
       "| 303 | youtube | 3.7 | 14 | 11 | 12 | 16 | 16 | 12 | 3 |\n",
       "| 304 | youtube | 2.2 |  9 |  7 | 15 | 24 | 12 | 13 | 4 |\n",
       "| 305 | youtube | 5.2 | 16 | 16 | 15 | 12 | 15 | 13 | 5 |\n",
       "| 306 | youtube | 6.2 | 17 | 16 | 11 | 15 | 22 | 18 | 5 |\n",
       "| 307 | youtube | 3.8 |  8 |  9 | 14 | 14 |  6 |  7 | 5 |\n",
       "| 308 | youtube | 4.0 | 11 |  8 |  8 | 11 | 11 | 10 | 5 |\n",
       "| 309 | youtube | 4.9 |  9 | 17 | 12 | 17 |  9 | 10 | 5 |\n",
       "| 310 | youtube | 2.9 | 12 | 22 | 19 | 23 | 24 | 16 | 5 |\n",
       "| 311 | youtube | 5.6 |  8 | 18 | 16 | 17 | 19 | 16 | 3 |\n",
       "| 312 | youtube | 5.2 | 16 | 17 | 16 | 13 | 17 | 13 | 4 |\n",
       "| 313 | youtube | 6.1 | 12 | 13 | 11 | 19 | 15 | 15 | 3 |\n",
       "| 314 | youtube | 4.2 | 11 |  6 |  6 | 16 |  6 | 14 | 2 |\n",
       "| 315 | youtube | 4.2 | 17 | 12 |  9 | 23 | 14 | 11 | 5 |\n",
       "| 401 | twitter | 4.9 | 10 | 15 | 13 | 19 |  9 |  6 | 4 |\n",
       "| 402 | twitter | 5.6 |  7 |  7 | 13 | 17 |  7 |  8 | 4 |\n",
       "| 403 | twitter | 4.5 | 12 |  9 | 18 | 19 | 13 | 11 | 4 |\n",
       "| 404 | twitter | 6.0 | 10 | 10 | 21 | 24 | 18 | 19 | 5 |\n",
       "| 405 | twitter | 4.7 | 12 |  9 |  6 | 13 | 14 |  6 | 2 |\n",
       "| 406 | twitter | 4.6 |  8 |  8 |  6 | 18 |  9 | 13 | 3 |\n",
       "| 407 | twitter | 3.2 | 10 |  6 | 12 | 24 | 19 | 16 | 1 |\n",
       "| 408 | twitter | 3.5 |  9 | 12 |  8 | 14 | 14 | 11 | 4 |\n",
       "| 409 | twitter | 3.9 |  8 | 13 | 16 | 21 | 14 | 10 | 4 |\n",
       "| 410 | twitter | 4.3 | 12 | 12 |  7 | 22 | 15 |  7 | 3 |\n",
       "| 411 | twitter | 4.1 | 14 | 14 | 11 | 20 | 11 | 12 | 2 |\n",
       "| 412 | twitter | 4.8 |  7 | 12 | 10 | 14 | 15 |  9 | 2 |\n",
       "| 413 | twitter | 6.2 | 16 | 12 | 20 | 17 | 19 | 15 | 4 |\n",
       "| 414 | twitter | 4.0 | 15 | 15 | 11 | 13 |  8 | 15 | 3 |\n",
       "| 415 | twitter | 3.2 | 14 | 14 | 11 | 12 | 10 | 11 | 3 |\n",
       "\n"
      ],
      "text/plain": [
       "   folder_id interrupt SUQ BSMARS META_CC META_POS META_CSC META_NEG META_NC\n",
       "1  101       rest      4.5 15     14      21       16       15        8     \n",
       "2  102       rest      4.9  6     10      15       20       11        9     \n",
       "3  103       rest      1.9  9     11      12       16       11       11     \n",
       "4  104       rest      3.6  8      9      12       12       11       12     \n",
       "5  105       rest      4.4  8     11      11       11        7        6     \n",
       "6  106       rest      4.3 13      9      11       13        7        8     \n",
       "7  107       rest      2.1  5     11       8       14        8        9     \n",
       "8  108       rest      6.1 17      9       9       20       20       17     \n",
       "9  109       rest      3.6  5     15      17       16       17       10     \n",
       "10 110       rest      4.7 11     18      15       20       15       12     \n",
       "11 111       rest      3.8  6      7       5       14       11       12     \n",
       "12 112       rest      4.2 14     12      14       12       18       17     \n",
       "13 113       rest      3.9 18     17      16       14       17       10     \n",
       "14 114       rest      1.6  8     11       8       21       18       15     \n",
       "15 115       rest      3.4  7     10       6       24       11       14     \n",
       "16 201       tiktok    5.5 15     20      15       16       20       13     \n",
       "17 202       tiktok    6.8 16     17      21       11       23       19     \n",
       "18 203       tiktok    5.4 17     13       7       13       11        7     \n",
       "19 204       tiktok    4.8 12     12      11       17       16        8     \n",
       "20 205       tiktok    3.8 11     16      18       24       17       11     \n",
       "21 206       tiktok    4.0 10      7      13       13       12        9     \n",
       "22 207       tiktok    4.9 12      8      14       17       13       10     \n",
       "23 208       tiktok    4.5  7     16      14       19       16        8     \n",
       "24 209       tiktok    4.8 16     10       8        8       10       12     \n",
       "25 210       tiktok    4.1  5      8       6       15        9       12     \n",
       "26 211       tiktok    6.2 17     11      17       21       22       13     \n",
       "27 212       tiktok    3.9 11     14      15       17       16       12     \n",
       "28 213       tiktok    5.0 13     11      10       14       19       12     \n",
       "29 214       tiktok    4.0 10      8       6       12       13        6     \n",
       "30 215       tiktok    3.6  9      9      11       18        7        6     \n",
       "31 301       youtube   4.0  7      9      22       19        7       12     \n",
       "32 302       youtube   4.8 12     12      10       15       10       12     \n",
       "33 303       youtube   3.7 14     11      12       16       16       12     \n",
       "34 304       youtube   2.2  9      7      15       24       12       13     \n",
       "35 305       youtube   5.2 16     16      15       12       15       13     \n",
       "36 306       youtube   6.2 17     16      11       15       22       18     \n",
       "37 307       youtube   3.8  8      9      14       14        6        7     \n",
       "38 308       youtube   4.0 11      8       8       11       11       10     \n",
       "39 309       youtube   4.9  9     17      12       17        9       10     \n",
       "40 310       youtube   2.9 12     22      19       23       24       16     \n",
       "41 311       youtube   5.6  8     18      16       17       19       16     \n",
       "42 312       youtube   5.2 16     17      16       13       17       13     \n",
       "43 313       youtube   6.1 12     13      11       19       15       15     \n",
       "44 314       youtube   4.2 11      6       6       16        6       14     \n",
       "45 315       youtube   4.2 17     12       9       23       14       11     \n",
       "46 401       twitter   4.9 10     15      13       19        9        6     \n",
       "47 402       twitter   5.6  7      7      13       17        7        8     \n",
       "48 403       twitter   4.5 12      9      18       19       13       11     \n",
       "49 404       twitter   6.0 10     10      21       24       18       19     \n",
       "50 405       twitter   4.7 12      9       6       13       14        6     \n",
       "51 406       twitter   4.6  8      8       6       18        9       13     \n",
       "52 407       twitter   3.2 10      6      12       24       19       16     \n",
       "53 408       twitter   3.5  9     12       8       14       14       11     \n",
       "54 409       twitter   3.9  8     13      16       21       14       10     \n",
       "55 410       twitter   4.3 12     12       7       22       15        7     \n",
       "56 411       twitter   4.1 14     14      11       20       11       12     \n",
       "57 412       twitter   4.8  7     12      10       14       15        9     \n",
       "58 413       twitter   6.2 16     12      20       17       19       15     \n",
       "59 414       twitter   4.0 15     15      11       13        8       15     \n",
       "60 415       twitter   3.2 14     14      11       12       10       11     \n",
       "   ENGAGE\n",
       "1  5     \n",
       "2  3     \n",
       "3  4     \n",
       "4  5     \n",
       "5  1     \n",
       "6  3     \n",
       "7  3     \n",
       "8  5     \n",
       "9  1     \n",
       "10 4     \n",
       "11 1     \n",
       "12 4     \n",
       "13 4     \n",
       "14 3     \n",
       "15 1     \n",
       "16 2     \n",
       "17 3     \n",
       "18 3     \n",
       "19 2     \n",
       "20 5     \n",
       "21 4     \n",
       "22 4     \n",
       "23 4     \n",
       "24 3     \n",
       "25 4     \n",
       "26 5     \n",
       "27 4     \n",
       "28 4     \n",
       "29 2     \n",
       "30 2     \n",
       "31 5     \n",
       "32 4     \n",
       "33 3     \n",
       "34 4     \n",
       "35 5     \n",
       "36 5     \n",
       "37 5     \n",
       "38 5     \n",
       "39 5     \n",
       "40 5     \n",
       "41 3     \n",
       "42 4     \n",
       "43 3     \n",
       "44 2     \n",
       "45 5     \n",
       "46 4     \n",
       "47 4     \n",
       "48 4     \n",
       "49 5     \n",
       "50 2     \n",
       "51 3     \n",
       "52 1     \n",
       "53 4     \n",
       "54 4     \n",
       "55 3     \n",
       "56 2     \n",
       "57 2     \n",
       "58 4     \n",
       "59 3     \n",
       "60 3     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df <- read.csv(\"data/q.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "# df$interrupt <- factor(df$interrupt, levels=c('rest', 'twitter', 'youtube', 'tiktok'))\n",
    "df$interrupt <- as.factor(df$interrupt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(ENGAGE ~ interrupt, data = df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            Df Sum Sq Mean Sq F value Pr(>F)  \n",
       "interrupt    3  10.85   3.617   2.592 0.0617 .\n",
       "Residuals   56  78.13   1.395                 \n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(aov(ENGAGE ~ interrupt, data = df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bayes factor analysis\n",
       "--------------\n",
       "[1] interrupt : 1.12921 ±0%\n",
       "\n",
       "Against denominator:\n",
       "  Intercept only \n",
       "---\n",
       "Bayes factor type: BFlinearModel, JZS\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bf <- anovaBF(ENGAGE ~ interrupt, data = df)\n",
    "bf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            Df Sum Sq Mean Sq F value Pr(>F)\n",
       "interrupt    3   41.9   13.98   1.065  0.371\n",
       "Residuals   56  734.8   13.12               "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(aov(BSMARS ~ interrupt, data = df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bayes factor analysis\n",
       "--------------\n",
       "[1] interrupt : 0.2562115 ±0%\n",
       "\n",
       "Against denominator:\n",
       "  Intercept only \n",
       "---\n",
       "Bayes factor type: BFlinearModel, JZS\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bf <- anovaBF(BSMARS ~ interrupt, data = df)\n",
    "bf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "            Df Sum Sq Mean Sq F value Pr(>F)  \n",
       "interrupt    3   7.47   2.488   2.267 0.0907 .\n",
       "Residuals   56  61.47   1.098                 \n",
       "---\n",
       "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "summary(aov(SUQ ~ interrupt, data = df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Bayes factor analysis\n",
       "--------------\n",
       "[1] interrupt : 0.8243245 ±0%\n",
       "\n",
       "Against denominator:\n",
       "  Intercept only \n",
       "---\n",
       "Bayes factor type: BFlinearModel, JZS\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "bf <- anovaBF(SUQ ~ interrupt, data = df)\n",
    "bf"
   ]
  }
 ],
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