Metodos-exploratorios-mutlivariados/Cuadernos/ACScienciaDatos.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "1Ch3SsEFYI1u"
   },
   "source": [
    "**<p align=\"center\"><font size=5 color=#006600>Diplomado en Ciencia de Datos**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OOJ7NOMnelA2"
   },
   "source": [
    "**<p align=\"center\"><font size=5 color=#0000FF>Análisis de correspondencias simples**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "z9oBWmjodpyc"
   },
   "source": [
    "**<font size=5 color=#0000FF>Profesores**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ms1l2HJYeCh7"
   },
   "source": [
    "1. Campo Elías Pardo Turriago, cepardot@unal.edu.co \n",
    "2. Alvaro Mauricio Montenegro Díaz,ammontenegrod@unal.edu.co \n",
    "3. Daniel Mauricio Montenegro Reyes, dextronomo@gmail.com\n",
    "4. Oleg Jarma, ojarmam@unal.edu.co"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TApWfcZxemhD"
   },
   "source": [
    "**<font size=5 color=#0000FF>Asesora de medios y marketing Digital**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "43gtv0Abextl"
   },
   "source": [
    "1. Maria del Pilar Montenegro, pmontenegro88@gmail.com"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "jLSx3bVoe9fZ"
   },
   "source": [
    "# **<font size=5 color=#0000FF>Asistentes**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "74W8jrBSfFXl"
   },
   "source": [
    "1. Jessica López Mejia, jelopezme@unal.edu.co"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "L7dnhZUdeyR7"
   },
   "source": [
    "## **Contenido**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ok00ZM5AgXw6"
   },
   "source": [
    "* [Introducción](#Introducción)\n",
    "* [Objetivos del ACS](#Objetivos-del-ACS)\n",
    "* [Ejemplo \"de juguete\" y notación](#Ejemplo-\"de-juguete\"-y-notación)\n",
    "* [El ACS como dos ACP](#El-ACS-como-dos-ACP)\n",
    "* [El ACS como un ACP(**X,M,N**)](#El-ACS-como-un-ACP(X,M,N))\n",
    "* [Ayudas para la interpretación](#Ayudas-para-la-interpretación)\n",
    "* [Filas y columnas suplementarias](#Filas-y-columnas-suplementarias)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Fi6OQ2SEfk6L"
   },
   "source": [
    "**Nota:** los trozos de código de este cuaderno son de R\n",
    "\n",
    "**Fuente:** Pardo CE (2020)  [PDF Estadística descriptiva multivariada](http://ciencias.bogota.unal.edu.co/fileadmin/Facultad_de_Ciencias/Publicaciones/Imagenes/Portadas_Libros/Estadistica/Estadistica_descriptiva_multivariada/libroEstadisiticaDescriptivaMultivariadaDigital.pdf).\n",
    "Capítulo 5."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introducción"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los objetos de entrada al análisis de correspondencias simples (ACS), son tablas de contingencia y tablas de números positivos donde las transformaciones a la tabla tengan sentido. Una tabla de contingencia (TC) es una tabla de resumen de dos variables cualitativas, las filas son categorías de una variable y las columnas las categorías de la otra. Una celda $(i,j)$ cuenta los objetos que asumen simultáneamente las categorías de la fila $i$ y de la columna $j$. Las suma de una fila $i$ (columna $j$) es el total de de objetos que  asumen la categoría $i$, ($j$), estas suman se denominan marginales. \n",
    "\n",
    "Si se divide la fila $i$ (columna $j$) por su total, se obtiene la distribución de frecuencias relativas condicional de la fila (columna), denominada también perfil fila (columna). Son estos perfiles los que se ponen en geometría. Cuando los objetos son colectivos (países, departamentos o provincias de un país, municipios, etc.), se pueden  considerar categorías de una variable: país, departamento, municipio, etc. Entonces se pone en columnas una variable cualitiva de interés, por ejemplo, las pirámides poblacionales por rangos de edad, combinadas por género. \n",
    "\n",
    "Un ejemplo pequeño de una tabla de interés para describir mediante el ACS es una tabla del producto interno bruto (PIB) clasificado según *departamentos* $\\times$ *subsectores de la economía*. La suma de las filas es la distribución del PIB por departamentos y la de las columnas la distribución del PIB por subsectores de la economía, el total de la tabla es el PIB del país. Los perfiles fila son las distribuiones del PIB en cada uno de los departamentos según los subsectores de la economía. Los perfiles columna son las distribuciones de los subsectores de la economía según los departamenos."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "liXrxkeGMutK",
    "tags": []
   },
   "source": [
    "# **Objetivos del ACS**\n",
    "\n",
    "Explorar y describir tablas de contingencia (TC), tablas de frecuencias y algunas tablas de números positivos.\n",
    "\n",
    "- Comparar los perfiles fila.\n",
    "- Comparar los perfiles columna.\n",
    "- Estudiar las correspondencias entre perfiles fila y columna.\n",
    "\n",
    "Adicionalmente:\n",
    "\n",
    "- Cuantificación de las categorías fila y columna\n",
    "- Reducción de la dimensión\n",
    "- Filtro: separar información de ruido.\n",
    "\n",
    "El ACS se puede ver como:\n",
    "- Dos ACP:  uno de los perfiles fila y otro de perfiles columna, que se superponen.\n",
    "- Un ACP de los desvíos de la tabla de frecuencias relativas a la tabla del modelo de independencia.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tn5sP7WofAu6"
   },
   "source": [
    "# **Ejemplo \"de juguete\" y notación**\n",
    "\n",
    "- Ejemplo TC de los 445 admitidos: 7 carreras $\\times$ 4 edades\n",
    "- La tabla de contingencia.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 130
    },
    "id": "ox324ZoCutjW",
    "outputId": "9eeb3b38-629b-4df1-e705-af5a0aa20a87"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loading required package: ade4\n",
      "\n",
      "Loading required package: ggplot2\n",
      "\n",
      "Loading required package: ggrepel\n",
      "\n",
      "Loading required package: xtable\n",
      "\n",
      "Loading required package: scatterplot3d\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(FactoClass)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "eo6Efj56uE0Z",
    "outputId": "15003abf-37fa-4c41-8dc0-011ce4a576ca"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Extracto de tabla admi, dimensión 445 15"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 11 × 15</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>carr</th><th scope=col>mate</th><th scope=col>cien</th><th scope=col>soci</th><th scope=col>text</th><th scope=col>imag</th><th scope=col>exam</th><th scope=col>gene</th><th scope=col>estr</th><th scope=col>orig</th><th scope=col>edad</th><th scope=col>niLE</th><th scope=col>niMa</th><th scope=col>stra</th><th scope=col>age</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&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;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>Biol</td><td>12.03</td><td>10.84</td><td>12.08</td><td>10.62</td><td>10.68</td><td>696.4424</td><td>F</td><td>alto </td><td>Bogo</td><td>a17 </td><td>noLE</td><td>siMa</td><td>E4</td><td>17</td></tr>\n",
       "\t<tr><th scope=row>45</th><td>Biol</td><td>11.21</td><td>11.16</td><td>11.36</td><td>12.35</td><td>11.26</td><td>701.0641</td><td>F</td><td>medio</td><td>Bogo</td><td>a16m</td><td>noLE</td><td>siMa</td><td>E3</td><td>16</td></tr>\n",
       "\t<tr><th scope=row>89</th><td>Esta</td><td> 9.68</td><td>10.51</td><td>11.71</td><td>13.56</td><td>10.96</td><td>652.5703</td><td>F</td><td>bajo </td><td>Bogo</td><td>a19M</td><td>noLE</td><td>siMa</td><td>E2</td><td>20</td></tr>\n",
       "\t<tr><th scope=row>133</th><td>Farm</td><td>10.64</td><td>12.45</td><td>10.70</td><td>10.62</td><td>11.60</td><td>679.3191</td><td>F</td><td>medio</td><td>Bogo</td><td>a16m</td><td>noLE</td><td>siMa</td><td>E3</td><td>16</td></tr>\n",
       "\t<tr><th scope=row>177</th><td>Farm</td><td>10.64</td><td> 9.37</td><td>10.38</td><td>10.91</td><td>10.68</td><td>546.9806</td><td>F</td><td>bajo </td><td>Otro</td><td>a16m</td><td>siLE</td><td>siMa</td><td>E2</td><td>16</td></tr>\n",
       "\t<tr><th scope=row>221</th><td>Fisi</td><td>11.21</td><td>12.12</td><td>12.48</td><td>12.35</td><td>10.96</td><td>763.0880</td><td>M</td><td>alto </td><td>Bogo</td><td>a17 </td><td>noLE</td><td>siMa</td><td>E5</td><td>17</td></tr>\n",
       "\t<tr><th scope=row>265</th><td>Fisi</td><td>10.64</td><td>10.16</td><td>11.36</td><td>11.92</td><td>12.54</td><td>670.9812</td><td>M</td><td>medio</td><td>Bogo</td><td>a19M</td><td>noLE</td><td>siMa</td><td>E3</td><td>20</td></tr>\n",
       "\t<tr><th scope=row>309</th><td>Geol</td><td>12.03</td><td>11.16</td><td>11.03</td><td>11.54</td><td>10.68</td><td>689.3005</td><td>M</td><td>bajo </td><td>Otro</td><td>a16m</td><td>siLE</td><td>siMa</td><td>E1</td><td>15</td></tr>\n",
       "\t<tr><th scope=row>353</th><td>Mate</td><td>11.48</td><td>13.17</td><td>10.05</td><td>11.21</td><td>10.96</td><td>706.0888</td><td>M</td><td>bajo </td><td>Bogo</td><td>a19M</td><td>noLE</td><td>siMa</td><td>E2</td><td>44</td></tr>\n",
       "\t<tr><th scope=row>397</th><td>Quim</td><td>11.21</td><td>10.51</td><td>10.38</td><td>12.87</td><td>11.26</td><td>655.7160</td><td>M</td><td>medio</td><td>Bogo</td><td>a19M</td><td>noLE</td><td>siMa</td><td>E3</td><td>21</td></tr>\n",
       "\t<tr><th scope=row>441</th><td>Quim</td><td>12.03</td><td>11.16</td><td>11.03</td><td>11.21</td><td>13.37</td><td>749.4165</td><td>M</td><td>bajo </td><td>Otro</td><td>a19M</td><td>noLE</td><td>siMa</td><td>E1</td><td>19</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 11 × 15\n",
       "\\begin{tabular}{r|lllllllllllllll}\n",
       "  & carr & mate & cien & soci & text & imag & exam & gene & estr & orig & edad & niLE & niMa & stra & age\\\\\n",
       "  & <fct> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <fct> & <dbl>\\\\\n",
       "\\hline\n",
       "\t1 & Biol & 12.03 & 10.84 & 12.08 & 10.62 & 10.68 & 696.4424 & F & alto  & Bogo & a17  & noLE & siMa & E4 & 17\\\\\n",
       "\t45 & Biol & 11.21 & 11.16 & 11.36 & 12.35 & 11.26 & 701.0641 & F & medio & Bogo & a16m & noLE & siMa & E3 & 16\\\\\n",
       "\t89 & Esta &  9.68 & 10.51 & 11.71 & 13.56 & 10.96 & 652.5703 & F & bajo  & Bogo & a19M & noLE & siMa & E2 & 20\\\\\n",
       "\t133 & Farm & 10.64 & 12.45 & 10.70 & 10.62 & 11.60 & 679.3191 & F & medio & Bogo & a16m & noLE & siMa & E3 & 16\\\\\n",
       "\t177 & Farm & 10.64 &  9.37 & 10.38 & 10.91 & 10.68 & 546.9806 & F & bajo  & Otro & a16m & siLE & siMa & E2 & 16\\\\\n",
       "\t221 & Fisi & 11.21 & 12.12 & 12.48 & 12.35 & 10.96 & 763.0880 & M & alto  & Bogo & a17  & noLE & siMa & E5 & 17\\\\\n",
       "\t265 & Fisi & 10.64 & 10.16 & 11.36 & 11.92 & 12.54 & 670.9812 & M & medio & Bogo & a19M & noLE & siMa & E3 & 20\\\\\n",
       "\t309 & Geol & 12.03 & 11.16 & 11.03 & 11.54 & 10.68 & 689.3005 & M & bajo  & Otro & a16m & siLE & siMa & E1 & 15\\\\\n",
       "\t353 & Mate & 11.48 & 13.17 & 10.05 & 11.21 & 10.96 & 706.0888 & M & bajo  & Bogo & a19M & noLE & siMa & E2 & 44\\\\\n",
       "\t397 & Quim & 11.21 & 10.51 & 10.38 & 12.87 & 11.26 & 655.7160 & M & medio & Bogo & a19M & noLE & siMa & E3 & 21\\\\\n",
       "\t441 & Quim & 12.03 & 11.16 & 11.03 & 11.21 & 13.37 & 749.4165 & M & bajo  & Otro & a19M & noLE & siMa & E1 & 19\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 11 × 15\n",
       "\n",
       "| <!--/--> | carr &lt;fct&gt; | mate &lt;dbl&gt; | cien &lt;dbl&gt; | soci &lt;dbl&gt; | text &lt;dbl&gt; | imag &lt;dbl&gt; | exam &lt;dbl&gt; | gene &lt;fct&gt; | estr &lt;fct&gt; | orig &lt;fct&gt; | edad &lt;fct&gt; | niLE &lt;fct&gt; | niMa &lt;fct&gt; | stra &lt;fct&gt; | age &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
       "| 1 | Biol | 12.03 | 10.84 | 12.08 | 10.62 | 10.68 | 696.4424 | F | alto  | Bogo | a17  | noLE | siMa | E4 | 17 |\n",
       "| 45 | Biol | 11.21 | 11.16 | 11.36 | 12.35 | 11.26 | 701.0641 | F | medio | Bogo | a16m | noLE | siMa | E3 | 16 |\n",
       "| 89 | Esta |  9.68 | 10.51 | 11.71 | 13.56 | 10.96 | 652.5703 | F | bajo  | Bogo | a19M | noLE | siMa | E2 | 20 |\n",
       "| 133 | Farm | 10.64 | 12.45 | 10.70 | 10.62 | 11.60 | 679.3191 | F | medio | Bogo | a16m | noLE | siMa | E3 | 16 |\n",
       "| 177 | Farm | 10.64 |  9.37 | 10.38 | 10.91 | 10.68 | 546.9806 | F | bajo  | Otro | a16m | siLE | siMa | E2 | 16 |\n",
       "| 221 | Fisi | 11.21 | 12.12 | 12.48 | 12.35 | 10.96 | 763.0880 | M | alto  | Bogo | a17  | noLE | siMa | E5 | 17 |\n",
       "| 265 | Fisi | 10.64 | 10.16 | 11.36 | 11.92 | 12.54 | 670.9812 | M | medio | Bogo | a19M | noLE | siMa | E3 | 20 |\n",
       "| 309 | Geol | 12.03 | 11.16 | 11.03 | 11.54 | 10.68 | 689.3005 | M | bajo  | Otro | a16m | siLE | siMa | E1 | 15 |\n",
       "| 353 | Mate | 11.48 | 13.17 | 10.05 | 11.21 | 10.96 | 706.0888 | M | bajo  | Bogo | a19M | noLE | siMa | E2 | 44 |\n",
       "| 397 | Quim | 11.21 | 10.51 | 10.38 | 12.87 | 11.26 | 655.7160 | M | medio | Bogo | a19M | noLE | siMa | E3 | 21 |\n",
       "| 441 | Quim | 12.03 | 11.16 | 11.03 | 11.21 | 13.37 | 749.4165 | M | bajo  | Otro | a19M | noLE | siMa | E1 | 19 |\n",
       "\n"
      ],
      "text/plain": [
       "    carr mate  cien  soci  text  imag  exam     gene estr  orig edad niLE niMa\n",
       "1   Biol 12.03 10.84 12.08 10.62 10.68 696.4424 F    alto  Bogo a17  noLE siMa\n",
       "45  Biol 11.21 11.16 11.36 12.35 11.26 701.0641 F    medio Bogo a16m noLE siMa\n",
       "89  Esta  9.68 10.51 11.71 13.56 10.96 652.5703 F    bajo  Bogo a19M noLE siMa\n",
       "133 Farm 10.64 12.45 10.70 10.62 11.60 679.3191 F    medio Bogo a16m noLE siMa\n",
       "177 Farm 10.64  9.37 10.38 10.91 10.68 546.9806 F    bajo  Otro a16m siLE siMa\n",
       "221 Fisi 11.21 12.12 12.48 12.35 10.96 763.0880 M    alto  Bogo a17  noLE siMa\n",
       "265 Fisi 10.64 10.16 11.36 11.92 12.54 670.9812 M    medio Bogo a19M noLE siMa\n",
       "309 Geol 12.03 11.16 11.03 11.54 10.68 689.3005 M    bajo  Otro a16m siLE siMa\n",
       "353 Mate 11.48 13.17 10.05 11.21 10.96 706.0888 M    bajo  Bogo a19M noLE siMa\n",
       "397 Quim 11.21 10.51 10.38 12.87 11.26 655.7160 M    medio Bogo a19M noLE siMa\n",
       "441 Quim 12.03 11.16 11.03 11.21 13.37 749.4165 M    bajo  Otro a19M noLE siMa\n",
       "    stra age\n",
       "1   E4   17 \n",
       "45  E3   16 \n",
       "89  E2   20 \n",
       "133 E3   16 \n",
       "177 E2   16 \n",
       "221 E5   17 \n",
       "265 E3   20 \n",
       "309 E1   15 \n",
       "353 E2   44 \n",
       "397 E3   21 \n",
       "441 E1   19 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data(admi)\n",
    "cat(\"\\nExtracto de tabla admi, dimensión\",dim(admi))\n",
    "admi[seq(1,445,44),] # un extracto de la tabla"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JjZzHn6quySD",
    "tags": []
   },
   "source": [
    "#### **Tabla de contingencia**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tabla de contingencia y marginales fila y columna, dimensión 7 4"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 8 × 5 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>a16m</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19M</th><th scope=col>Sum</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td> 15</td><td> 27</td><td> 9</td><td> 12</td><td> 63</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td> 18</td><td> 28</td><td> 5</td><td> 15</td><td> 66</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td> 18</td><td> 26</td><td>15</td><td> 14</td><td> 73</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td> 21</td><td> 34</td><td>12</td><td> 15</td><td> 82</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td> 11</td><td> 25</td><td> 2</td><td>  7</td><td> 45</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td> 11</td><td> 14</td><td> 5</td><td> 23</td><td> 53</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td> 24</td><td> 17</td><td> 8</td><td> 14</td><td> 63</td></tr>\n",
       "\t<tr><th scope=row>Sum</th><td>118</td><td>171</td><td>56</td><td>100</td><td>445</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 8 × 5 of type dbl\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & a16m & a17 & a18 & a19M & Sum\\\\\n",
       "\\hline\n",
       "\tBiol &  15 &  27 &  9 &  12 &  63\\\\\n",
       "\tEsta &  18 &  28 &  5 &  15 &  66\\\\\n",
       "\tFarm &  18 &  26 & 15 &  14 &  73\\\\\n",
       "\tFisi &  21 &  34 & 12 &  15 &  82\\\\\n",
       "\tGeol &  11 &  25 &  2 &   7 &  45\\\\\n",
       "\tMate &  11 &  14 &  5 &  23 &  53\\\\\n",
       "\tQuim &  24 &  17 &  8 &  14 &  63\\\\\n",
       "\tSum & 118 & 171 & 56 & 100 & 445\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 8 × 5 of type dbl\n",
       "\n",
       "| <!--/--> | a16m | a17 | a18 | a19M | Sum |\n",
       "|---|---|---|---|---|---|\n",
       "| Biol |  15 |  27 |  9 |  12 |  63 |\n",
       "| Esta |  18 |  28 |  5 |  15 |  66 |\n",
       "| Farm |  18 |  26 | 15 |  14 |  73 |\n",
       "| Fisi |  21 |  34 | 12 |  15 |  82 |\n",
       "| Geol |  11 |  25 |  2 |   7 |  45 |\n",
       "| Mate |  11 |  14 |  5 |  23 |  53 |\n",
       "| Quim |  24 |  17 |  8 |  14 |  63 |\n",
       "| Sum | 118 | 171 | 56 | 100 | 445 |\n",
       "\n"
      ],
      "text/plain": [
       "      \n",
       "       a16m a17 a18 a19M Sum\n",
       "  Biol  15   27  9   12   63\n",
       "  Esta  18   28  5   15   66\n",
       "  Farm  18   26 15   14   73\n",
       "  Fisi  21   34 12   15   82\n",
       "  Geol  11   25  2    7   45\n",
       "  Mate  11   14  5   23   53\n",
       "  Quim  24   17  8   14   63\n",
       "  Sum  118  171 56  100  445"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#TC \"de juguete\" como ejemplo\n",
    "K<-unclass(table(admi$carr,admi$edad))\n",
    "cat(\"\\nTabla de contingencia y marginales fila y columna, dimensión\",dim(K))\n",
    "addmargins(K) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hZrvhNXfNAWd"
   },
   "source": [
    "#### Notación\n",
    "\n",
    "Tabla de contingencia $\\mathbf{K}$\n",
    "- Termino general $k_{ij}$ \n",
    "- Marginal de filas  $k_{i \\cdot}$ \n",
    "- Marginal de columnas $k_{\\cdot j}$ \n",
    "- Total  $k=k_{\\cdot\\cdot}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "ndlTAr81x50G"
   },
   "source": [
    "#### **Tabla de frecuencias relativas**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 189
    },
    "id": "gyqGaZuP8SXZ",
    "outputId": "a0a5a87c-6653-46c8-d56f-035bd1b4009e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tabla de frecuencias relativas, en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 8 × 5 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>a16m</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19M</th><th scope=col>Sum</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td> 3.37</td><td> 6.07</td><td> 2.02</td><td> 2.70</td><td>14.16</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td> 4.04</td><td> 6.29</td><td> 1.12</td><td> 3.37</td><td>14.82</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td> 4.04</td><td> 5.84</td><td> 3.37</td><td> 3.15</td><td>16.40</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td> 4.72</td><td> 7.64</td><td> 2.70</td><td> 3.37</td><td>18.43</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td> 2.47</td><td> 5.62</td><td> 0.45</td><td> 1.57</td><td>10.11</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td> 2.47</td><td> 3.15</td><td> 1.12</td><td> 5.17</td><td>11.91</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td> 5.39</td><td> 3.82</td><td> 1.80</td><td> 3.15</td><td>14.16</td></tr>\n",
       "\t<tr><th scope=row>Sum</th><td>26.50</td><td>38.43</td><td>12.58</td><td>22.48</td><td>99.99</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 8 × 5 of type dbl\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & a16m & a17 & a18 & a19M & Sum\\\\\n",
       "\\hline\n",
       "\tBiol &  3.37 &  6.07 &  2.02 &  2.70 & 14.16\\\\\n",
       "\tEsta &  4.04 &  6.29 &  1.12 &  3.37 & 14.82\\\\\n",
       "\tFarm &  4.04 &  5.84 &  3.37 &  3.15 & 16.40\\\\\n",
       "\tFisi &  4.72 &  7.64 &  2.70 &  3.37 & 18.43\\\\\n",
       "\tGeol &  2.47 &  5.62 &  0.45 &  1.57 & 10.11\\\\\n",
       "\tMate &  2.47 &  3.15 &  1.12 &  5.17 & 11.91\\\\\n",
       "\tQuim &  5.39 &  3.82 &  1.80 &  3.15 & 14.16\\\\\n",
       "\tSum & 26.50 & 38.43 & 12.58 & 22.48 & 99.99\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 8 × 5 of type dbl\n",
       "\n",
       "| <!--/--> | a16m | a17 | a18 | a19M | Sum |\n",
       "|---|---|---|---|---|---|\n",
       "| Biol |  3.37 |  6.07 |  2.02 |  2.70 | 14.16 |\n",
       "| Esta |  4.04 |  6.29 |  1.12 |  3.37 | 14.82 |\n",
       "| Farm |  4.04 |  5.84 |  3.37 |  3.15 | 16.40 |\n",
       "| Fisi |  4.72 |  7.64 |  2.70 |  3.37 | 18.43 |\n",
       "| Geol |  2.47 |  5.62 |  0.45 |  1.57 | 10.11 |\n",
       "| Mate |  2.47 |  3.15 |  1.12 |  5.17 | 11.91 |\n",
       "| Quim |  5.39 |  3.82 |  1.80 |  3.15 | 14.16 |\n",
       "| Sum | 26.50 | 38.43 | 12.58 | 22.48 | 99.99 |\n",
       "\n"
      ],
      "text/plain": [
       "      \n",
       "       a16m  a17   a18   a19M  Sum  \n",
       "  Biol  3.37  6.07  2.02  2.70 14.16\n",
       "  Esta  4.04  6.29  1.12  3.37 14.82\n",
       "  Farm  4.04  5.84  3.37  3.15 16.40\n",
       "  Fisi  4.72  7.64  2.70  3.37 18.43\n",
       "  Geol  2.47  5.62  0.45  1.57 10.11\n",
       "  Mate  2.47  3.15  1.12  5.17 11.91\n",
       "  Quim  5.39  3.82  1.80  3.15 14.16\n",
       "  Sum  26.50 38.43 12.58 22.48 99.99"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "F<-K/sum(K)\n",
    "cat(\"\\nTabla de frecuencias relativas, en porcentaje\")\n",
    "addmargins(round(F*100,2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ilcura-rqvT-"
   },
   "source": [
    "Tabla de frecuencias relativas $\\mathbf{F} = \\frac{1}{k}\\mathbf{K}$\n",
    "\n",
    "- Termino general $f_{ij}=\\frac{k_{ij}}{k}$ \n",
    "- Marginal de filas  $f_{i \\cdot}$ \n",
    "- Marginal de columnas $f_{\\cdot j}$ \n",
    "- Total  $f_{\\cdot\\cdot}=1$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zvWsYb5JNPbS"
   },
   "source": [
    "## Perfiles fila\n",
    "\n",
    "Sea $\\mathbf{D}_n = diag(f_{i \\cdot})$, los perfiles fila son $\\mathbf{D}_n^{-1} \\mathbf{F}$:\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "fnXHufbfe1Ey",
    "outputId": "0a5fb139-cc30-44ce-a285-49706b6ded55"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Matriz diagonal con los valores maginales fila, en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 7 × 7 of type dbl</caption>\n",
       "<tbody>\n",
       "\t<tr><td>14.2</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td>14.8</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td> 0.0</td><td>16.4</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td> 0.0</td><td> 0.0</td><td>18.4</td><td> 0.0</td><td> 0.0</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td>10.1</td><td> 0.0</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td>11.9</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td> 0.0</td><td>14.2</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 7 × 7 of type dbl\n",
       "\\begin{tabular}{lllllll}\n",
       "\t 14.2 &  0.0 &  0.0 &  0.0 &  0.0 &  0.0 &  0.0\\\\\n",
       "\t  0.0 & 14.8 &  0.0 &  0.0 &  0.0 &  0.0 &  0.0\\\\\n",
       "\t  0.0 &  0.0 & 16.4 &  0.0 &  0.0 &  0.0 &  0.0\\\\\n",
       "\t  0.0 &  0.0 &  0.0 & 18.4 &  0.0 &  0.0 &  0.0\\\\\n",
       "\t  0.0 &  0.0 &  0.0 &  0.0 & 10.1 &  0.0 &  0.0\\\\\n",
       "\t  0.0 &  0.0 &  0.0 &  0.0 &  0.0 & 11.9 &  0.0\\\\\n",
       "\t  0.0 &  0.0 &  0.0 &  0.0 &  0.0 &  0.0 & 14.2\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 7 × 7 of type dbl\n",
       "\n",
       "| 14.2 |  0.0 |  0.0 |  0.0 |  0.0 |  0.0 |  0.0 |\n",
       "|  0.0 | 14.8 |  0.0 |  0.0 |  0.0 |  0.0 |  0.0 |\n",
       "|  0.0 |  0.0 | 16.4 |  0.0 |  0.0 |  0.0 |  0.0 |\n",
       "|  0.0 |  0.0 |  0.0 | 18.4 |  0.0 |  0.0 |  0.0 |\n",
       "|  0.0 |  0.0 |  0.0 |  0.0 | 10.1 |  0.0 |  0.0 |\n",
       "|  0.0 |  0.0 |  0.0 |  0.0 |  0.0 | 11.9 |  0.0 |\n",
       "|  0.0 |  0.0 |  0.0 |  0.0 |  0.0 |  0.0 | 14.2 |\n",
       "\n"
      ],
      "text/plain": [
       "     [,1] [,2] [,3] [,4] [,5] [,6] [,7]\n",
       "[1,] 14.2  0.0  0.0  0.0  0.0  0.0  0.0\n",
       "[2,]  0.0 14.8  0.0  0.0  0.0  0.0  0.0\n",
       "[3,]  0.0  0.0 16.4  0.0  0.0  0.0  0.0\n",
       "[4,]  0.0  0.0  0.0 18.4  0.0  0.0  0.0\n",
       "[5,]  0.0  0.0  0.0  0.0 10.1  0.0  0.0\n",
       "[6,]  0.0  0.0  0.0  0.0  0.0 11.9  0.0\n",
       "[7,]  0.0  0.0  0.0  0.0  0.0  0.0 14.2"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# valores marginales por filas\n",
    "Dn <- diag(rowSums(F))\n",
    "cat(\"\\nMatriz diagonal con los valores maginales fila, en porcentaje\")\n",
    "round(Dn*100,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Perfiles fila en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 7 × 5 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>a16m</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19M</th><th scope=col>Sum</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td>23.8</td><td>42.9</td><td>14.3</td><td>19.0</td><td>100</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td>27.3</td><td>42.4</td><td> 7.6</td><td>22.7</td><td>100</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td>24.7</td><td>35.6</td><td>20.5</td><td>19.2</td><td>100</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td>25.6</td><td>41.5</td><td>14.6</td><td>18.3</td><td>100</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td>24.4</td><td>55.6</td><td> 4.4</td><td>15.6</td><td>100</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td>20.8</td><td>26.4</td><td> 9.4</td><td>43.4</td><td>100</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td>38.1</td><td>27.0</td><td>12.7</td><td>22.2</td><td>100</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 7 × 5 of type dbl\n",
       "\\begin{tabular}{r|lllll}\n",
       "  & a16m & a17 & a18 & a19M & Sum\\\\\n",
       "\\hline\n",
       "\tBiol & 23.8 & 42.9 & 14.3 & 19.0 & 100\\\\\n",
       "\tEsta & 27.3 & 42.4 &  7.6 & 22.7 & 100\\\\\n",
       "\tFarm & 24.7 & 35.6 & 20.5 & 19.2 & 100\\\\\n",
       "\tFisi & 25.6 & 41.5 & 14.6 & 18.3 & 100\\\\\n",
       "\tGeol & 24.4 & 55.6 &  4.4 & 15.6 & 100\\\\\n",
       "\tMate & 20.8 & 26.4 &  9.4 & 43.4 & 100\\\\\n",
       "\tQuim & 38.1 & 27.0 & 12.7 & 22.2 & 100\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 7 × 5 of type dbl\n",
       "\n",
       "| <!--/--> | a16m | a17 | a18 | a19M | Sum |\n",
       "|---|---|---|---|---|---|\n",
       "| Biol | 23.8 | 42.9 | 14.3 | 19.0 | 100 |\n",
       "| Esta | 27.3 | 42.4 |  7.6 | 22.7 | 100 |\n",
       "| Farm | 24.7 | 35.6 | 20.5 | 19.2 | 100 |\n",
       "| Fisi | 25.6 | 41.5 | 14.6 | 18.3 | 100 |\n",
       "| Geol | 24.4 | 55.6 |  4.4 | 15.6 | 100 |\n",
       "| Mate | 20.8 | 26.4 |  9.4 | 43.4 | 100 |\n",
       "| Quim | 38.1 | 27.0 | 12.7 | 22.2 | 100 |\n",
       "\n"
      ],
      "text/plain": [
       "      \n",
       "       a16m a17  a18  a19M Sum\n",
       "  Biol 23.8 42.9 14.3 19.0 100\n",
       "  Esta 27.3 42.4  7.6 22.7 100\n",
       "  Farm 24.7 35.6 20.5 19.2 100\n",
       "  Fisi 25.6 41.5 14.6 18.3 100\n",
       "  Geol 24.4 55.6  4.4 15.6 100\n",
       "  Mate 20.8 26.4  9.4 43.4 100\n",
       "  Quim 38.1 27.0 12.7 22.2 100"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ECAwHUCZ+Vn3Xb2qeTK66b84ccFGX1W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\nAgQIECBAgAABAgQIEDjAAv8P9FXS+4feygMAAAAASUVORK5CYII=",
      "text/plain": [
       "Plot with title “Perfiles fila”"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# perfil fila\n",
    "perFila <- solve(Dn)%*%F\n",
    "rownames(perFila)<-rownames(F)\n",
    "colnames(perFila)<-colnames(F)\n",
    "cat(\"\\nPerfiles fila en porcentaje\")\n",
    "round(addmargins(perFila*100,2),1)\n",
    "\n",
    "# gráfica de los perfiles,  plotct es función de FactoClass\n",
    "plotct(K,\"row\",col=c(\"red\",\"orange\",\"green\",\"blue\"),main=\"Perfiles fila\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Kj2REGrSe1Ez"
   },
   "source": [
    "## Perfiles columna\n",
    "\n",
    "Sea $\\mathbf{D}_p = diag(f_{\\cdot j})$, los perfiles columna son $\\mathbf{D}_p^{-1} \\mathbf{F'}$ (puestos como filas): \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Matriz diagonal con los maginales columna en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 4 × 4 of type dbl</caption>\n",
       "<tbody>\n",
       "\t<tr><td>26.5</td><td> 0.0</td><td> 0.0</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td>38.4</td><td> 0.0</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td> 0.0</td><td>12.6</td><td> 0.0</td></tr>\n",
       "\t<tr><td> 0.0</td><td> 0.0</td><td> 0.0</td><td>22.5</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 4 × 4 of type dbl\n",
       "\\begin{tabular}{llll}\n",
       "\t 26.5 &  0.0 &  0.0 &  0.0\\\\\n",
       "\t  0.0 & 38.4 &  0.0 &  0.0\\\\\n",
       "\t  0.0 &  0.0 & 12.6 &  0.0\\\\\n",
       "\t  0.0 &  0.0 &  0.0 & 22.5\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 4 × 4 of type dbl\n",
       "\n",
       "| 26.5 |  0.0 |  0.0 |  0.0 |\n",
       "|  0.0 | 38.4 |  0.0 |  0.0 |\n",
       "|  0.0 |  0.0 | 12.6 |  0.0 |\n",
       "|  0.0 |  0.0 |  0.0 | 22.5 |\n",
       "\n"
      ],
      "text/plain": [
       "     [,1] [,2] [,3] [,4]\n",
       "[1,] 26.5  0.0  0.0  0.0\n",
       "[2,]  0.0 38.4  0.0  0.0\n",
       "[3,]  0.0  0.0 12.6  0.0\n",
       "[4,]  0.0  0.0  0.0 22.5"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cat(\"\\nMatriz diagonal con los maginales columna en porcentaje\")\n",
    "Dp<-diag(colSums(F))\n",
    "round(Dp*100,1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "AM8A3F9Re1E0",
    "outputId": "eeb4a465-b468-4a10-83a9-47293d75c857"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Perfiles columna en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 8 × 4 of type dbl</caption>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td> 12.7</td><td> 15.8</td><td> 16.1</td><td> 12</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td> 15.3</td><td> 16.4</td><td>  8.9</td><td> 15</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td> 15.3</td><td> 15.2</td><td> 26.8</td><td> 14</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td> 17.8</td><td> 19.9</td><td> 21.4</td><td> 15</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td>  9.3</td><td> 14.6</td><td>  3.6</td><td>  7</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td>  9.3</td><td>  8.2</td><td>  8.9</td><td> 23</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td> 20.3</td><td>  9.9</td><td> 14.3</td><td> 14</td></tr>\n",
       "\t<tr><th scope=row>Sum</th><td>100.0</td><td>100.0</td><td>100.0</td><td>100</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 8 × 4 of type dbl\n",
       "\\begin{tabular}{r|llll}\n",
       "\tBiol &  12.7 &  15.8 &  16.1 &  12\\\\\n",
       "\tEsta &  15.3 &  16.4 &   8.9 &  15\\\\\n",
       "\tFarm &  15.3 &  15.2 &  26.8 &  14\\\\\n",
       "\tFisi &  17.8 &  19.9 &  21.4 &  15\\\\\n",
       "\tGeol &   9.3 &  14.6 &   3.6 &   7\\\\\n",
       "\tMate &   9.3 &   8.2 &   8.9 &  23\\\\\n",
       "\tQuim &  20.3 &   9.9 &  14.3 &  14\\\\\n",
       "\tSum & 100.0 & 100.0 & 100.0 & 100\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 8 × 4 of type dbl\n",
       "\n",
       "| Biol |  12.7 |  15.8 |  16.1 |  12 |\n",
       "| Esta |  15.3 |  16.4 |   8.9 |  15 |\n",
       "| Farm |  15.3 |  15.2 |  26.8 |  14 |\n",
       "| Fisi |  17.8 |  19.9 |  21.4 |  15 |\n",
       "| Geol |   9.3 |  14.6 |   3.6 |   7 |\n",
       "| Mate |   9.3 |   8.2 |   8.9 |  23 |\n",
       "| Quim |  20.3 |   9.9 |  14.3 |  14 |\n",
       "| Sum | 100.0 | 100.0 | 100.0 | 100 |\n",
       "\n"
      ],
      "text/plain": [
       "      \n",
       "       [,1]  [,2]  [,3]  [,4]\n",
       "  Biol  12.7  15.8  16.1  12 \n",
       "  Esta  15.3  16.4   8.9  15 \n",
       "  Farm  15.3  15.2  26.8  14 \n",
       "  Fisi  17.8  19.9  21.4  15 \n",
       "  Geol   9.3  14.6   3.6   7 \n",
       "  Mate   9.3   8.2   8.9  23 \n",
       "  Quim  20.3   9.9  14.3  14 \n",
       "  Sum  100.0 100.0 100.0 100 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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7fXVQF1UHeeuuLU305PR+/26qpVXTH6x77+vOx8MVlVIxoBAgQIECBAgAABAu0Q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\nrkJggg==",
      "text/plain": [
       "Plot with title “Perfiles columna”"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "perColum <- F%*%solve(Dp)\n",
    "cat(\"\\nPerfiles columna en porcentaje\")\n",
    "round(addmargins(perColum,1)*100,1)\n",
    "plotct(t(K),\"row\",col=2:8,main=\"Perfiles columna\") "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VC1qjTsxe1E0"
   },
   "source": [
    "## El modelo de independencia\n",
    "Sea $a_{ij}=f_{i\\cdot}f_{\\cdot j}$, el término general de la tabla de independencia $\\mathbf{A}$ \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "kgwrPHBie1E1",
    "outputId": "1b40d19c-6bd4-40fa-d764-9137b44922ba"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tabla de frecuencias relativas en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 7 × 4 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>a16m</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19M</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td>3.4</td><td>6.1</td><td>2.0</td><td>2.7</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td>4.0</td><td>6.3</td><td>1.1</td><td>3.4</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td>4.0</td><td>5.8</td><td>3.4</td><td>3.1</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td>4.7</td><td>7.6</td><td>2.7</td><td>3.4</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td>2.5</td><td>5.6</td><td>0.4</td><td>1.6</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td>2.5</td><td>3.1</td><td>1.1</td><td>5.2</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td>5.4</td><td>3.8</td><td>1.8</td><td>3.1</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 7 × 4 of type dbl\n",
       "\\begin{tabular}{r|llll}\n",
       "  & a16m & a17 & a18 & a19M\\\\\n",
       "\\hline\n",
       "\tBiol & 3.4 & 6.1 & 2.0 & 2.7\\\\\n",
       "\tEsta & 4.0 & 6.3 & 1.1 & 3.4\\\\\n",
       "\tFarm & 4.0 & 5.8 & 3.4 & 3.1\\\\\n",
       "\tFisi & 4.7 & 7.6 & 2.7 & 3.4\\\\\n",
       "\tGeol & 2.5 & 5.6 & 0.4 & 1.6\\\\\n",
       "\tMate & 2.5 & 3.1 & 1.1 & 5.2\\\\\n",
       "\tQuim & 5.4 & 3.8 & 1.8 & 3.1\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 7 × 4 of type dbl\n",
       "\n",
       "| <!--/--> | a16m | a17 | a18 | a19M |\n",
       "|---|---|---|---|---|\n",
       "| Biol | 3.4 | 6.1 | 2.0 | 2.7 |\n",
       "| Esta | 4.0 | 6.3 | 1.1 | 3.4 |\n",
       "| Farm | 4.0 | 5.8 | 3.4 | 3.1 |\n",
       "| Fisi | 4.7 | 7.6 | 2.7 | 3.4 |\n",
       "| Geol | 2.5 | 5.6 | 0.4 | 1.6 |\n",
       "| Mate | 2.5 | 3.1 | 1.1 | 5.2 |\n",
       "| Quim | 5.4 | 3.8 | 1.8 | 3.1 |\n",
       "\n"
      ],
      "text/plain": [
       "      \n",
       "       a16m a17 a18 a19M\n",
       "  Biol 3.4  6.1 2.0 2.7 \n",
       "  Esta 4.0  6.3 1.1 3.4 \n",
       "  Farm 4.0  5.8 3.4 3.1 \n",
       "  Fisi 4.7  7.6 2.7 3.4 \n",
       "  Geol 2.5  5.6 0.4 1.6 \n",
       "  Mate 2.5  3.1 1.1 5.2 \n",
       "  Quim 5.4  3.8 1.8 3.1 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tabla del modelo de independencia en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 7 × 4 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>a16m</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19M</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td>3.8</td><td>5.4</td><td>1.8</td><td>3.2</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td>3.9</td><td>5.7</td><td>1.9</td><td>3.3</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td>4.3</td><td>6.3</td><td>2.1</td><td>3.7</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td>4.9</td><td>7.1</td><td>2.3</td><td>4.1</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td>2.7</td><td>3.9</td><td>1.3</td><td>2.3</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td>3.2</td><td>4.6</td><td>1.5</td><td>2.7</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td>3.8</td><td>5.4</td><td>1.8</td><td>3.2</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 7 × 4 of type dbl\n",
       "\\begin{tabular}{r|llll}\n",
       "  & a16m & a17 & a18 & a19M\\\\\n",
       "\\hline\n",
       "\tBiol & 3.8 & 5.4 & 1.8 & 3.2\\\\\n",
       "\tEsta & 3.9 & 5.7 & 1.9 & 3.3\\\\\n",
       "\tFarm & 4.3 & 6.3 & 2.1 & 3.7\\\\\n",
       "\tFisi & 4.9 & 7.1 & 2.3 & 4.1\\\\\n",
       "\tGeol & 2.7 & 3.9 & 1.3 & 2.3\\\\\n",
       "\tMate & 3.2 & 4.6 & 1.5 & 2.7\\\\\n",
       "\tQuim & 3.8 & 5.4 & 1.8 & 3.2\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 7 × 4 of type dbl\n",
       "\n",
       "| <!--/--> | a16m | a17 | a18 | a19M |\n",
       "|---|---|---|---|---|\n",
       "| Biol | 3.8 | 5.4 | 1.8 | 3.2 |\n",
       "| Esta | 3.9 | 5.7 | 1.9 | 3.3 |\n",
       "| Farm | 4.3 | 6.3 | 2.1 | 3.7 |\n",
       "| Fisi | 4.9 | 7.1 | 2.3 | 4.1 |\n",
       "| Geol | 2.7 | 3.9 | 1.3 | 2.3 |\n",
       "| Mate | 3.2 | 4.6 | 1.5 | 2.7 |\n",
       "| Quim | 3.8 | 5.4 | 1.8 | 3.2 |\n",
       "\n"
      ],
      "text/plain": [
       "     a16m a17 a18 a19M\n",
       "Biol 3.8  5.4 1.8 3.2 \n",
       "Esta 3.9  5.7 1.9 3.3 \n",
       "Farm 4.3  6.3 2.1 3.7 \n",
       "Fisi 4.9  7.1 2.3 4.1 \n",
       "Geol 2.7  3.9 1.3 2.3 \n",
       "Mate 3.2  4.6 1.5 2.7 \n",
       "Quim 3.8  5.4 1.8 3.2 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tabla del desvios al modelo de independencia en porcentaje"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A matrix: 7 × 4 of type dbl</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>a16m</th><th scope=col>a17</th><th scope=col>a18</th><th scope=col>a19M</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td>-0.38</td><td> 0.63</td><td> 0.24</td><td>-0.48</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td> 0.11</td><td> 0.59</td><td>-0.74</td><td> 0.04</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td>-0.31</td><td>-0.46</td><td> 1.31</td><td>-0.54</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td>-0.17</td><td> 0.56</td><td> 0.38</td><td>-0.77</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td>-0.21</td><td> 1.73</td><td>-0.82</td><td>-0.70</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td>-0.69</td><td>-1.43</td><td>-0.38</td><td> 2.49</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td> 1.64</td><td>-1.62</td><td> 0.02</td><td>-0.04</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A matrix: 7 × 4 of type dbl\n",
       "\\begin{tabular}{r|llll}\n",
       "  & a16m & a17 & a18 & a19M\\\\\n",
       "\\hline\n",
       "\tBiol & -0.38 &  0.63 &  0.24 & -0.48\\\\\n",
       "\tEsta &  0.11 &  0.59 & -0.74 &  0.04\\\\\n",
       "\tFarm & -0.31 & -0.46 &  1.31 & -0.54\\\\\n",
       "\tFisi & -0.17 &  0.56 &  0.38 & -0.77\\\\\n",
       "\tGeol & -0.21 &  1.73 & -0.82 & -0.70\\\\\n",
       "\tMate & -0.69 & -1.43 & -0.38 &  2.49\\\\\n",
       "\tQuim &  1.64 & -1.62 &  0.02 & -0.04\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A matrix: 7 × 4 of type dbl\n",
       "\n",
       "| <!--/--> | a16m | a17 | a18 | a19M |\n",
       "|---|---|---|---|---|\n",
       "| Biol | -0.38 |  0.63 |  0.24 | -0.48 |\n",
       "| Esta |  0.11 |  0.59 | -0.74 |  0.04 |\n",
       "| Farm | -0.31 | -0.46 |  1.31 | -0.54 |\n",
       "| Fisi | -0.17 |  0.56 |  0.38 | -0.77 |\n",
       "| Geol | -0.21 |  1.73 | -0.82 | -0.70 |\n",
       "| Mate | -0.69 | -1.43 | -0.38 |  2.49 |\n",
       "| Quim |  1.64 | -1.62 |  0.02 | -0.04 |\n",
       "\n"
      ],
      "text/plain": [
       "      \n",
       "       a16m  a17   a18   a19M \n",
       "  Biol -0.38  0.63  0.24 -0.48\n",
       "  Esta  0.11  0.59 -0.74  0.04\n",
       "  Farm -0.31 -0.46  1.31 -0.54\n",
       "  Fisi -0.17  0.56  0.38 -0.77\n",
       "  Geol -0.21  1.73 -0.82 -0.70\n",
       "  Mate -0.69 -1.43 -0.38  2.49\n",
       "  Quim  1.64 -1.62  0.02 -0.04"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "A<-diag(Dn)%*%t(diag(Dp)) #modelo de independencia\n",
    "colnames(A)<-colnames(F); rownames(A)<-rownames(F)\n",
    "cat(\"\\nTabla de frecuencias relativas en porcentaje\")\n",
    "round(F*100,1)\n",
    "cat(\"\\nTabla del modelo de independencia en porcentaje\")\n",
    "round(A*100,1)\n",
    "cat(\"\\nTabla del desvios al modelo de independencia en porcentaje\")\n",
    "round((F-A)*100,2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**En el modelo de independencia los perfila fila y columna son iguales a los marginales**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MbjqlcCBAgQIECAAAECBFoooEBq4UEz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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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AECBAiMpIACaSSnzU4TIECAAAECBAgQILAcAgqk5VD1mgQIECBAgAABAgQIjKSA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\nJ4H/D5VRCkmeU79gAAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# perfiles fila y columna en el modelo de independencia\n",
    "plotct(A,\"row\",col=c(\"red\",\"orange\",\"green\",\"blue\")) \n",
    "plotct(A,\"col\",col=2:8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Las distribuciones marginales fila (columna) están en centro de la representación geométrica de las columnas (filas). El ACS va más allá de la prueba de independencia que se suele hacer para las tablas de contingencia, ya que describe las dependencias entre categorías fila y columna, al comparar perfiles fila y columna derivados de la tabla."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QRpwDOzMe1E2"
   },
   "source": [
    "# **El ACS como dos ACP**\n",
    "\n",
    "En el ACS (*Análisis de Correspondencias Simples*) se describen simultáneamente los perfiles fila y columna. Para cada tabla de perfiles se realiza un **ACP(X, M, N)**, pero los dos ACP (*Análisis de componentes principales*) están\n",
    "relacionados, lo que permite representaciones simultáneas de los planos factoriales."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3cOs2cJje1E2"
   },
   "source": [
    "## ACP de los perfiles-fila\n",
    "$$\n",
    "ACP(\\mathbf{X,M,N}) = ACP(\\mathbf{D}_n^{-1}\\mathbf{F},\\mathbf{D}^{-1}_p,\\mathbf{D_n})\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Diagrama de dualidad del ACS de los perfiles filas](../Imagenes/DuDiACSfilas.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La matriz a diagonalizar (hallarle valores y vectores propios) es:\n",
    "\n",
    "$$\n",
    "\\mathbf{F'D}_n^{-1} \\mathbf{D}_n \\mathbf{D}_n^{-1} \\mathbf{F} \\mathbf{D}_p^{-1}\n",
    "= \\mathbf{F'D}_n^{-1} \\mathbf{F} \\mathbf{D}_p^{-1} \n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "3cOs2cJje1E2"
   },
   "source": [
    "- Las coordenadas de los puntos son las filas dela tabla  $\\mathbf{D}_n^{-1}\\mathbf{F}$, es decir que cada histograma (perfil) se respresenta por un punto en $\\mathbb{R}^p$.\n",
    "- La diferencia entre dos histogramas = distancia entre los puntos en $\\mathbb{R}^p$.\n",
    "- Los pesos de los puntos fila: $f_{i\\cdot}$ están en la  la matriz diagonal $\\mathbf{D_n}$.\n",
    "- Las distancias entre distribuciones condicionales se definen a partir del producto punto dado por la matriz $\\mathbf{D}^{-1}_p$.\n",
    "- La matriz $\\mathbf{D}_n^{-1}\\mathbf{F}$ no está centrada.\n",
    "- El mayor valor propio de la matriz a diagonalizar $\\mathbf{F'D_n^{-1}FD_p^{-1}}$ es 1 y el vector propio asociado es el centro de gravedad de la nube.\n",
    "- Partir del segundo vector propio de esta matriz es equivalente a centrar, logrando una simplificación de las fórmulas del ACS.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Nube de perfiles fila \n",
    "\n",
    "- Coordenadas de los perfiles fila son: $\\mathbf{x}_i; i=1,2,\\cdots,n$; con:\n",
    "$$ \\mathbf{x}_i(j) = \\dfrac{f_{ij}}{f_{i\\cdot}}; \\ j=1,2,\\cdots,p$$\n",
    "    - Si tomamos $i=3$, se obtiene el perfil de Farmacia cuyas coordenadas son:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>a16m</dt><dd>0.247</dd><dt>a17</dt><dd>0.356</dd><dt>a18</dt><dd>0.205</dd><dt>a19M</dt><dd>0.192</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[a16m] 0.247\n",
       "\\item[a17] 0.356\n",
       "\\item[a18] 0.205\n",
       "\\item[a19M] 0.192\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "a16m\n",
       ":   0.247a17\n",
       ":   0.356a18\n",
       ":   0.205a19M\n",
       ":   0.192\n",
       "\n"
      ],
      "text/plain": [
       " a16m   a17   a18  a19M \n",
       "0.247 0.356 0.205 0.192 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(perFila[3,],3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Centro de gravedad:\n",
    "$$ \\mathbf{g}_p = \\sum_{i=1}^n f_{i\\cdot} \\mathbf{x}_i$$\n",
    "    - La coordenada $j$, notada $ \\mathbf{g}_p(j)$, del centro de gravedad es:\n",
    "$$ \n",
    "\\mathbf{g}_p(j)=\\sum_{i=1}^n f_{i\\cdot} \\dfrac{f_{ij}}{f_{i\\cdot}} = \\sum_{i=1}^n f_{ij} = f_{\\cdot j}\n",
    "$$\n",
    "Lo que indica que el centro de gravedad $\\mathbf{g}_p$ es la distribución marginal columna (suma vertical) de la tabla de frecuencias relativas $\\mathbf{F}$\n",
    "    - Centro de gravedad = Marginal columna de la tabla **F**, en el ejemplo es: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>a16m</dt><dd>0.265</dd><dt>a17</dt><dd>0.384</dd><dt>a18</dt><dd>0.126</dd><dt>a19M</dt><dd>0.225</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[a16m] 0.265\n",
       "\\item[a17] 0.384\n",
       "\\item[a18] 0.126\n",
       "\\item[a19M] 0.225\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "a16m\n",
       ":   0.265a17\n",
       ":   0.384a18\n",
       ":   0.126a19M\n",
       ":   0.225\n",
       "\n"
      ],
      "text/plain": [
       " a16m   a17   a18  a19M \n",
       "0.265 0.384 0.126 0.225 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(colSums(F),3)      "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "LwxsXAo88NOy"
   },
   "source": [
    "- Distancia entre perfiles fila = distancia $ji$ cuadrado o de Benzècri:\n",
    "la métrica es $\\mathbf{D}^{-1}_p$, elemento diagonal  $\\dfrac{1}{f_{\\cdot j}}$\n",
    "$$  \n",
    "d^2(i,l)=\\sum_{j=1}^p \\dfrac{1}{f_{\\cdot j}} (x_{ij}-x_{lj})^2 =\n",
    "\\sum_{j=1}^p \\dfrac{1}{f_{\\cdot j}} \\left(\\dfrac{f_{ij}}{f_{i\\cdot}}-\\dfrac{f_{lj}}{f_{l\\cdot}}\\right)^2\n",
    "$$\n",
    "\n",
    "    -  amplifica más las diferencias al cuadrado entre coordenadas cuando se deben a columnas de baja frecuencia marginal. \n",
    "    - La distancia $ji$ cuadrado le confiere al ACS dos propiedades: \n",
    "        + La equivalencia distribucional \n",
    "        + Las relaciones cuasi-baricéntricas,\n",
    "        \n",
    "&nbsp;\n",
    "\n",
    "- Inercia de la nube de perfiles fila:\n",
    "$$\n",
    "Inercia(N_n) = \\sum_{i=1}^n f_{i\\cdot } d^2(i,\\mathbf{g}_p)=\n",
    "\\sum_{i=1}^n f_{i\\cdot } \\sum_{j=1}^p \\dfrac{1}{f_{\\cdot j}} \\left(\\dfrac{f_{ij}}{f_{i\\cdot}}-f_{\\cdot j}\\right)^2\n",
    "$$\n",
    "$$\n",
    "=\n",
    "\\sum_{i=1}^n \\sum_{j=1}^p  \\frac{\\left(f_{ij} - f_{i\\cdot}f_{\\cdot j}\\right)^2}{f_{i\\cdot}f_{\\cdot j}}\n",
    "$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "La inercia de la nube Nn es:  0.0743"
     ]
    }
   ],
   "source": [
    "inerciaNn=sum((F-A)^2/F)\n",
    "cat(\"\\nLa inercia de la nube Nn es: \",round(inerciaNn,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "-Xux9-R6e1E7"
   },
   "source": [
    "###  Ejes y subespacios vectoriales\n",
    "Se obtienen con el procedimiento ACP generalizado descrito, que para el caso de las filas son los perfiles fila derivados de la tabla de contingencia y con pesos iguales a la marginal fila (suma horizontal) de al tabla de frecuencias relativas $\\mathbf{F}$. Las distancias son las sumas al cuadrado de las diferencias de los perfiles ponderadas por el inverso de las marginales columna de la tabla $\\mathbf{F}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Con la función *dudi.coa{ade4}* se tiene el objeto con todos los resultados del ACS."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Esquema de la función dudi.coa de ade4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Función dudi.coa de ade4](../Imagenes/Diagdudicoa.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### ACS de la tabla de contingencia $\\mathbf{K}$ $carreras \\times edades$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "acs<-dudi.coa(K,scannf=FALSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Perfiles fila de K"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BAgQIAAAQIECPQtoEDqm8wCBAgQIECA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\nAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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UCBdLOFIQIECBAgQIAAAQIEprmAAmma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\nQIAAAQJLJ/D/AcHcKvrcPcp6AAAAAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotct(K,\"row\",col=c(\"red\",\"yellow\",\"green\"))\n",
    "plot(acs,Tcol=FALSE)#,xlim=c(-0.7,0.3),cframe=1,asp=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Los perfiles de Estadística, Matemáticas y Farmacia son bastante parecidos; el de Química un poco menos a estos. El de Biología parecido al de Física y Geología diferente a todos y el menos parecido al perfil marginal. Esto se puede corroborar con la gráfica de perfiles fila (arriba)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ACP de los perfiles-columna\n",
    "\n",
    "\n",
    " ${\\Large \\qquad\\qquad ACP(\\mathbf{D}_p^{-1}\\mathbf{F'},\\mathbf{D}_n^{-1},\\mathbf{D}_p)}$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Diagrama de dualidad del ACP de los perfiles columna](../Imagenes/DuDiACScolumnas.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La matriz a diagonalizar (hallarle valores y vectores propios) es:\n",
    "\n",
    "$${\\large\n",
    "\\mathbf{FD}_p^{-1} \\mathbf{D}_p \\mathbf{D}_p^{-1} \\mathbf{F'} \\mathbf{D}_n^{-1}\n",
    "= \\mathbf{FD}_p^{-1} \\mathbf{F'} \\mathbf{D}_n^{-1} \n",
    "}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XJ7qvggve1E9"
   },
   "source": [
    " \n",
    "- Los histogramas de las distribuciones condicionales columna se representan como puntos en $\\mathbb{R}^n$\n",
    "-  A cada punto $j$ se le asigna el peso $f_{\\cdot j}$\n",
    "-  Este análisis es simétrico al de perfiles fila  \n",
    "\n",
    "### Primer plano factorial de los perfiles de las edades según carreras :\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 437
    },
    "id": "9C-Rs-1vHZZp",
    "outputId": "12384ed2-ce4b-484e-977f-f0c0bf78043c"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1tXCRAgQIAAAQIECBCYXkCBNL2PuQQIECBAgAABAgQINEhAgdSgk62rBAgQIECA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\nTPqeUpfsvi2pS0efljTldZm5uLlh2orAevts0v3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      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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rVavbqJp1l0DIGPfexjz8qd7Obk8eNj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\nAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotct(t(K),\"row\",col=2:8)\n",
    "plot(acs,Trow=FALSE,asp=1,cframe=1) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El perfil *a19M* es el más diferente del promedio y *a16m* el más parecido. Las tres categorías de más edad están ordenadas en el primer eje."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "thGLNtuDe1E-"
   },
   "source": [
    "# **El ACS como un ACP(X,M,N)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El ACS como un ACP es el de los desvios del modelo de independencia."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VrhFkQF1e1E-"
   },
   "source": [
    "- El ACS de la tabla $\\mathbf{F}$ también se obtiene mediante el ACP de\n",
    "la tabla $\\mathbf{X}$ \n",
    "- Usando $\\mathbf{N}=\\mathbf{D}_n=diag(f_{i\\cdot})$, como pesos de las filas y matriz de métrica en el espacio de las columnas.\n",
    "- Usando $\\mathbf{M}=\\mathbf{D}_p=diag(f_{\\cdot j})$, como pesos de las columnas y matriz de métrica en el espacio de las filas.\n",
    "- Y usando \n",
    "$$\n",
    "x_{ij} =\\frac{f_{ij} -f_{i\\cdot} f_{\\cdot j} }{f_{i\\cdot} f_{\\cdot j} }\n",
    "= \\frac{f_{ij}}{f_{i\\cdot} f_{\\cdot j}} - 1\n",
    "$$\n",
    "\n",
    "El vector de $n$ unos es el centro de gravedad, se puede hacer el ACP sin centrar y descartar el mayor valor propio $1$ y su vecor propio asociado: el vector de $n$ unos."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Diagrama de dualidad ACS como un ACP](../Imagenes/DuDiACSunACP.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La matriz a diagonalizar (hallarle valores y vectores propios) es:\n",
    "\n",
    "$${\\large\n",
    "\\mathbf{D}_p^{-1} \\mathbf{F'} \\mathbf{D}_n^{-1}\\mathbf{D}_n \\mathbf{D}_n^{-1} \\mathbf{F} \\mathbf{D}_p^{-1}\n",
    "\\mathbf{D}_p = \\mathbf{D}_p^{-1} \\mathbf{F'} \\mathbf{D}_n^{-1} \\mathbf{F}\n",
    "}$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "gv7pu4Q6e1E_"
   },
   "source": [
    "## Equivalencia distribucional\n",
    "- El ACS no se modifica si se unen dos puntos que tienen el mismo perfil. \n",
    "- El peso del punto colapsado es la suma de los pesos de los puntos que se unen.\n",
    "- Lo anterior permite unir filas o columnas con perfiles parecidos, para simplificar las tablas originales\n",
    "    - Por ejemplo las carreras Estadística, Matemáticas y Farmacia; o las carreras Biología y Física \n",
    "- Esta propiedad hace que el ACS sea robusto ante la \"arbitrariedad\" en la conformación de las categorías de una variable en un estudio\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "treOhm8LIQMk",
    "outputId": "e4dcc81d-4051-47fd-d1c8-a80ffaac160f"
   },
   "source": [
    "## Relaciones cuasibaricéntricas\n",
    "\n",
    "De las relaciones de transición del ACP generalizado:\n",
    "\n",
    "- Una coordenada de la fila en función de las coordenadas de las columnas\n",
    "\n",
    "$$\n",
    "F_s(i)=\\dfrac{1}{\\sqrt{\\lambda_s}}\\sum\\limits_{j=1}^p{x_{ij}m_j}G_s(j)\n",
    "= \\dfrac{1}{\\sqrt{\\lambda_s}}\\sum\\limits_{j=1}^p \\frac{f_{ij}}{f_{i\\cdot}f_{\\cdot j} } f_{\\cdot j} G_s(j)\n",
    "= \\frac{1}{\\sqrt{\\lambda_s}}\\sum_{j=1}^p{\\frac{f_{ij}}{f_{i\\cdot}} G_s(j)}\n",
    "$$\n",
    "\n",
    "- Una coordenada de la columna en función de las coordenadas de las filas\n",
    "\n",
    "$$ G_s(j)=\\dfrac{1}{\\sqrt{\\lambda_s}}\\sum\\limits_{i=1}^n{x_{ij}p_i}F_s(i)\n",
    "= \\frac{1}{\\sqrt{\\lambda_s}}\\sum_{i=1}^n{{\\frac{f_{ij}}{f_{\\cdot j}}\n",
    "  F_s(i)}}\n",
    "$$ \n",
    "\n",
    "- Estas dos fórmulas son las relaciones cuasibaricéntricas: \n",
    "\n",
    "$$\n",
    " F_s(i) = \\frac{1}{\\sqrt{\\lambda_s}}\\sum_{j=1}^p{\\frac{f_{ij}}{f_{i\\cdot}} G_s(j)}\n",
    "\\qquad \\qquad \\qquad\n",
    "  G_s(j) = \\frac{1}{\\sqrt{\\lambda_s}}\\sum_{i=1}^n{{\\frac{f_{ij}}{f_{\\cdot j}}\n",
    "  F_s(i)}}\n",
    "$$\n",
    "\n",
    "- Las relaciones cuasibaricéntricas hacen posible la representación simultánea y su interpretación. \n",
    "-  Un sumando $j$ es \n",
    "$\\dfrac{f_{ij}}{f_{i\\cdot}} G_s(j)$, donde $\\dfrac{f_{ij}}{f_{i\\cdot}}$ es la coordenada $j$ del perfil de la fila $i$, es decir la altura de la barra $j$ del histograma.\n",
    "- Como $\\sum\\limits_{j=1}^p \\frac{f_{ij}}{f_{i\\cdot}}=1$, la sumatoria es un promedio ponderado de las coordenadas de las columnas.\n",
    "- Cada fila tiene un promedio diferente porque las ponderaciones cambian.\n",
    "- El punto promedio se ubica dentro del polígono que une a los puntos columna, por las dilataciones $\\dfrac{1}{\\sqrt{\\lambda_s}}; s=1,2$, el punto puede ubicarse afuera."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Esquema de la representación simultánea de perfiles fila y columna"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"../Imagenes/ACSrepresentacionSimultanea.png\" alt=\"drawing\" width=\"400\"/>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Ejemplo\n",
    "\n",
    " Coordenada del perfil de Matemáticas sobre el primer eje. Teniendo en cuenta que:\n",
    "\n",
    "-  Perfil de Matemáticas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".dl-inline {width: auto; margin:0; padding: 0}\n",
       ".dl-inline>dt, .dl-inline>dd {float: none; width: auto; display: inline-block}\n",
       ".dl-inline>dt::after {content: \":\\0020\"; padding-right: .5ex}\n",
       ".dl-inline>dt:not(:first-of-type) {padding-left: .5ex}\n",
       "</style><dl class=dl-inline><dt>a16m</dt><dd>0.208</dd><dt>a17</dt><dd>0.264</dd><dt>a18</dt><dd>0.094</dd><dt>a19M</dt><dd>0.434</dd></dl>\n"
      ],
      "text/latex": [
       "\\begin{description*}\n",
       "\\item[a16m] 0.208\n",
       "\\item[a17] 0.264\n",
       "\\item[a18] 0.094\n",
       "\\item[a19M] 0.434\n",
       "\\end{description*}\n"
      ],
      "text/markdown": [
       "a16m\n",
       ":   0.208a17\n",
       ":   0.264a18\n",
       ":   0.094a19M\n",
       ":   0.434\n",
       "\n"
      ],
      "text/plain": [
       " a16m   a17   a18  a19M \n",
       "0.208 0.264 0.094 0.434 "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(perFila[\"Mate\",],3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-  Coordenadas de las edades sobre el primer eje "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>\n",
       ".list-inline {list-style: none; margin:0; padding: 0}\n",
       ".list-inline>li {display: inline-block}\n",
       ".list-inline>li:not(:last-child)::after {content: \"\\00b7\"; padding: 0 .5ex}\n",
       "</style>\n",
       "<ol class=list-inline><li>-0.008</li><li>-0.188</li><li>-0.015</li><li>0.34</li></ol>\n"
      ],
      "text/latex": [
       "\\begin{enumerate*}\n",
       "\\item -0.008\n",
       "\\item -0.188\n",
       "\\item -0.015\n",
       "\\item 0.34\n",
       "\\end{enumerate*}\n"
      ],
      "text/markdown": [
       "1. -0.008\n",
       "2. -0.188\n",
       "3. -0.015\n",
       "4. 0.34\n",
       "\n",
       "\n"
      ],
      "text/plain": [
       "[1] -0.008 -0.188 -0.015  0.340"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(acs$co[,1],3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-  Primer valor propio "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "0.0395"
      ],
      "text/latex": [
       "0.0395"
      ],
      "text/markdown": [
       "0.0395"
      ],
      "text/plain": [
       "[1] 0.0395"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "round(acs$eig[1],4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    " F_s(i) = \\frac{1}{\\sqrt{\\lambda_s}}\\sum_{j=1}^p{\\frac{f_{ij}}{f_{i\\cdot}} G_s(j)}\n",
    "$$ \n",
    "- La relación de transición que expresa la coordenada del perfil *Mate* en función de las coordenadas de los perfiles columnas es:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Calculo de la coordenada con la fórmula de trensición: 0.4759\n",
      "Coordenada de Mate: 0.4759"
     ]
    }
   ],
   "source": [
    "cat(\"\\nCalculo de la coordenada con la fórmula de trensición:\",\n",
    "    round(1/sqrt(acs$eig[1]) * sum(perFila[\"Mate\",]*acs$co[,1]),4))\n",
    "cat(\"\\nCoordenada de Mate:\",round(acs$li[\"Mate\",1],4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Cálculo paso a paso:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Sumandos en el cálculo del centroide de Mate: -0.0018 -0.0496 -0.0015 0.1474"
     ]
    }
   ],
   "source": [
    "cat(\"\\nSumandos en el cálculo del centroide de Mate:\",round(perFila[\"Mate\",]*acs$co[,1],4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "El sumando más alto es el de *a19m*, entonces el punto *Mate* va a proyectarse más cerca de es punto."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "El promedio ponderado por el perfil de Mate es: 0.0946\n",
      "Se aleja del centro (dilatación) en: 5.0298\n",
      "Coordenada de Mate: 0.4759"
     ]
    }
   ],
   "source": [
    "gMate=sum(perFila[\"Mate\",]*acs$co[,1])\n",
    "cat(\"\\nEl promedio ponderado por el perfil de Mate es:\",round(gMate,4))\n",
    "dilEje1=1/sqrt(acs$eig[1])\n",
    "cat(\"\\nSe aleja del centro (dilatación) en:\",round(dilEje1,4))\n",
    "coorMate=dilEje1*gMate\n",
    "cat(\"\\nCoordenada de Mate:\",round(coorMate,4))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "UDY2RfYOe1FA"
   },
   "source": [
    " ### Representación simultánea de carreras y edades"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "3xXQyPXZe1FB",
    "outputId": "1b755b0b-7475-488e-b078-33e23f6591ef"
   },
   "outputs": [
    {
     "data": {
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AAAIIIFDoAjSQCv0IsX0I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NxqI1a9b0yi7N9H78omODVSy9rKOvJn8+\nSp8uAgQIECAwLQJusZsWRishQIAAAQIECBAgQGAQBBRIg3AWHQMBAgQIECBAgAABAtMioECa\nFkYrIUCAAAECBAgQIEBgEAQUSINwFh0DAQIECBAgQIAAAQLTIuApdtPCaCUECBDYc4HVq1cv\n2rRp0xF7viZrIECAAAECBKYqoECaqpzXESBAYJoF1q5de9SGDRsOmebVWh0BAgQIECAwCQG3\n2E0Cy6IECBAgQIAAAQIECAy2gAJpsM+voyNAgAABAgQIECBAYBICCqRJYFmUAAECBAgQIECA\nAIHBFlAgDfb5dXQECBAgQIAAAQIECExCQIE0CSyLEiBAgAABAgQIECAw2AIKpME+v46OAIE+\nEpg3b97OZFcf7bJdJUCAAAECAyfgMd8Dd0odEAEC/SqwcuXKc7dt23b4smXL+vUQ7DcBAgQI\nEOh7AQVS359CB0CAwKAILFiwYHuj0dg+KMfjOAgQIECAQD8KuMWuH8+afSZAgAABAgQIECBA\noCsCCqSusFopAQIECBAgQIAAAQL9KKBA6sezZp8JECBAgAABAgQIEOiKgO8gdYXVSgkQIDB5\ngXXr1h2wdevW+ZN/pVcQIECAAAEC0yUw6AXS8YF6aHJe8o3kth6fW1fUHp3cK9mSfDW5KNEI\nECDQdYEzzjjjuI0bNx7d9Q3ZAAECBAgQIDCmwKAWSPvniM9JDkv+O3lT8tnk6clYT4i6XeZ9\nOTkuOTdZnCxIXpr8faIRIECgqwIjIyNzdu3a1ejqRqycAAECBAgQGFdgUL+D9IYcdRVJ90yW\nJg9JHpc8KxmrvT4z7pfcJzkhuVPygeRdyV0SjQABAgQIECBAgACBARcYxAKpfvv64uT9Sd0m\nV+1/kk8lz6+JMdox6f9EUstW25G8J9k7eVCiESBAgAABAgQIECAw4AKDeIvdHXPO9ku+23Hu\navrxHX3tkye3TzTH60pStYtvHPiXAAECBAgQIECAAIFBFhjEAuno5gm7vOPEXZnpA5L6rtHV\nHfNGm7x9Ol+WfCv5wWgLjNN3SOa9LdlnnGXaZ/3mYx/72Dmvec1r3j9v3ryd7TOM94TAgY1G\n4yXnnnvuk3pib+zEwAqcfvrpx/7iF7/YL++1fxnYg3RgvSKw+w6S/Gx7Xd5vV/TKTtmPgRWo\nh2b52Tawp3fOnJ07d8594xvfOOezn62v/Pd/G8QC6dDmadnacXquaU4fmOFtFUj1cIazkoOT\nurJ0W0+/yyK3aLX8dclEi53tO3bsmJMvaG/La+rWPq23BHJqRm7IB4k6pxqBrgnkAQ31s2Mk\n8V7rmrIVNwVat9hf7/3mPTEDAjvy/+hO/4/OgPTsbWJufZbVekOgipiftOVPM163xdUHjPsn\n7e25mbghaf2n0D6vffzITPx38rPk3u0zujj+vKy79rmucGk9JpDfrl5+zjnnPLnHdsvuDKDA\nqaee+s5Xv/rVFw7goTmkHhPIb3n3zc+2kfxsa91K3mN7aHcGSSDvs9OSjw/SMTmWWwnUXVP1\nWbb+vE7ft36/glR/2+iitrNQ4z9vTh/W1l+jhyf1XaLxrgbdPfO/mNTtePWfRmtdGdUIECDQ\nXYElS5Zclt+wXvHmN7+5uxuydgIECBAgQGBMgX4vkE4d5cjqCtGG5DHJF5JWOykjrSfUtfra\nh4sy8fXk/KS+a9J5i166NAIECBAgQIAAAQIEBlmg3wuk0c5NXSH62+SNyZrka8lzkgcnD0xa\nbXlGliYvSeq7P+9O6sEMdQn4CUl7qz86u669wzgBAgQIECBAgAABAoMnMIgFUp2l05PFSX1H\naa/kguQFyY+TVqs/Hlvf/fmz5KCk9Zjv92W8sz03HQqkThXTBAgQIECAAAECBAZMYFALpHqM\nxsrkVUnru0edp+4V6ahUuzqpPzCrESBAgAABAgQIECAwxAKDWiC1TmndOlcPZtAIECDQ8wKr\nVq06fv369cf0/I7aQQIECBAgMMAC9UADjQABAgRGF6hfIj0gqVt2u942b948f8uWLXt3fUM2\nQIAAAQIECIwpoEAak8YMAgSGXKAe6lJXoP8r+Wny6WT/RCNAgAABAgQGWECBNMAn16ERIDBl\ngfrZ+MmkvsPYaidm5HWtCUMCBAgQIEBgMAUUSIN5Xh0VAQJ7JlB/NPrOST0Fs9X2zciy1oQh\nAQIECBAgMJgCCqTBPK+OigCBPRP4dV4+0rGK+htrl3f0mSRAgAABAgQGTECBNGAn1OEQIDAt\nApdlLR9JbmiurYqjam++ceBfAgQIECBAYFAFBv0x34N63hwXAQLdF3h2NlF/XHp5cmWyKjk7\n6VpbuHDhlXPnzr3moosu6to2rJgAAQIECBAYX0CBNL6PuQQIDK/A9hz6m5qZEYUVK1ac32g0\nFq1Zs2ZGtmcjBAgQIECAwK0F3GJ3axM9BAgQIECAAAECBAgMqYACaUhPvMMmQIAAAQIECBAg\nQODWAgqkW5voIUCAAAECBAgQIEBgSAUUSEN64h02AQIECBAgQIAAAQK3FvCQhlub6CFAgMCs\nCKxevXrRpk2bjpiVjdsoAQIECBAgsFtAgeSNQIAAgR4RWLt27VEbNmw4pEd2x24QIECAAIGh\nFFAgDeVpd9AEhkbgiTnSu41ztO/MvB3jzDeLAAECBAgQGDIBBdKQnXCHS2DIBJ6V4z05+dUY\nx/2e9CuQxsDRTYAAAQIEhlFAgTSMZ90xExgugQtyuMcO1yE7WgIECBAgQGCqAgqkqcp5HQEC\ngyZwvxxQ5aDkp8kXk21JtcOTByVfT/4wWd8cPzHDHyYHJL+TXJ58Kbk6OSZ5ZPJfyfcSjQAB\nAgQIEOgDAQVSH5wku0iAQNcF3p8tPCs5L9k7qStOFybHJVuT45P/TM5Knpxcl9wx+bfkE0n1\nVdF0n+S7yfuS9yb/m9wrab0uoxoBAgQIECDQywIKpF4+O/aNAIHpEKjHZr9jlBVV3yVJXQV6\nTlLfVfpMUu1xyaeTJyQfSartk+yXHJzUVaarkmqPT+6bVIG0PPl4clRy1+RnydOTM5IFyeZk\nzDZv3rydya4xFzCDAAECBAgQ6LqAAqnrxDZAgMAsC9Ttb789yj78Y7Pv3AwfkNStcq32k4xU\noXJIq6M5/LsMf91Ma9bqjFRxVO0LNw7mfCrDKo6qfSepq1InJGcnY7aVK1eeu23btsOXLVs2\n5jJmECBAgAABAt0VUCB119faCRCYfYGLsgt1i9xY7erM2Dep2+Lq1rp7JHslc5vDDG5q624a\nu3lk482ju2/Hq8m1bX11O161Wue4bcGCBdsbjcb2cRcykwABAgQIEOiqQH0A0AgQIDDMAifl\n4L+V3CX5cPKo5A7JSNJI2tu29onmeKsAap/lNrl2DeMECBAgQKCPBFxB6qOTZVcJEOiKwJ9k\nrXWV6TFta79/xqs4us2rPm2vMUqAAAECBAgMgIArSANwEh0CAQJ7JFCP4D46eUhSPxOrOGo9\nmGH/jGsECBAgQIDAEAm4gjREJ9uhEiAwqkA94vthyVeSKpDqIQyvSp6WVNE0Y23dunUHbN26\ndf6MbdCGCBAgQIAAgVsJKJBuRaKDAIEBEnjSBI6lCqJargqTeoT3JUm1D9w42P1vPf678/tI\nNeP2u+fe/M/OjHYud+kofTe/om3sjDPOOG7jxo11NUsjQIAAAQIEZklAgTRL8DZLgEDPCVyb\nParMWhsZGZmza9euzgJr1vbHhgkQIECAwDAK+A7SMJ51x0yAAAECBAgQIECAwKgCCqRRWXQS\nIECAAAECBAgQIDCMAgqkYTzrjpkAAQIECBAgQIAAgVEFFEijsugkQIAAAQIECBAgQGAYBRRI\nw3jWHTMBAj0r0Gh4RkPPnhw7RoAAAQJDIaBAGorT7CAJEOgHgaVLl16wfPnyeiy4RoAAAQIE\nCMySgAJpluBtlgABAp0CS5YsuWzZsmVXdPabJkCAAAECBGZOQIE0c9a2RIAAAQIECBAgQIBA\njwsokHr8BNk9AgQIECBAgAABAgRmTkCBNHPWtkSAAAECBAgQIECAQI8LKJB6/ATZPQIECBAg\nQIAAAQIEZk5g3sxtypYIECBAYDyBVatWHb9+/fpjxlvGPAIECBAgQKC7Aq4gddfX2gkQIDBh\ngc2bN8/fsmXL3hN+gQUJECBAgACBaRdQIE07qRUSIECAAAECBAgQINCvAgqkfj1z9psAAQIE\nCBAgQIAAgWkXUCBNO6kVEiBAgAABAgQIECDQrwIKpH49c/abAAECBAgQIECAAIFpF1AgTTup\nFRIgQIAAAQIECBAg0K8CCqR+PXP2mwCBgRNYuHDhlYsXL75m4A7MAREgQIAAgT4S8HeQ+uhk\n2VUCBAZbYMWKFec3Go1Fa9asGewDdXQECBAgQKCHBVxB6uGTY9cIECBAgAABAgQIEJhZAQXS\nzHrbGgECBAgQIECAAAECPSygQOrhk2PXCBAgQIAAAQIECBCYWQEF0sx62xoBAgQIECBAgAAB\nAj0s4CENPXxy7BoBAsMlsHr16kWbNm06YriO2tESIECAAIHeElAg9db5sDcECAyxwNq1a4/a\nsGHDIUNM4NAJECBAgMCsC7jFbtZPgR0gQIAAAQIECBAgQKBXBBRIvXIm7AcBAgQIECBAgAAB\nArMuoECa9VNgBwgQIECAAAECBAgQ6BUBBVKvnAn7QYAAAQIECBAgQIDArAsokGb9FNgBAgQI\nECBAgAABAgR6RUCB1Ctnwn4QIDD0AvPmzduZ7Bp6CAAECBAgQGAWBTzmexbxbZoAAQLtAitX\nrjx327Zthy9btqy92zgBAgQIECAwgwIKpBnEtikCBAiMJ7BgwYLtjUZj+3jLmEeAAAECBAh0\nV8Atdt31tXYCBAgQIECAAAECBPpIQIHURyfLrhIgQIAAAQIECBAg0F0BBVJ3fa2dAAECBAgQ\nIECAAIE+EvAdpD46WXaVAIHBFli3bt0BW7dunT/YR+noCBAgQIBAbwsokHr7/Ng7AgSGSOCM\nM844buPGjUcP0SE7VAIECBAg0HMCbrHruVNihwgQGFaBkZGRObt27WoM6/E7bgIECBAg0AsC\nCqReOAv2gQABAgQIECBAgACBnhBQIPXEabATBAgQIECAAAECBAj0goACqRfOgn0gQIAAAQIE\nCBAgQKAnBBRIPXEa7AQBAgQIECBAgAABAr0goEDqhbNgHwgQINAUaDQ8o8GbgQABAgQIzKaA\nAmk29W2bAAECbQJLly69YPny5Ze2dRklQIAAAQIEZlhAgTTD4DZHgACBsQSWLFly2bJly64Y\na75+AgQIECBAoPsCCqTuG9sCAQIECBAgQIAAAQJ9IqBA6pMTZTcJECBAgAABAgQIEOi+gAKp\n+8a2QIAAAQIECBAgQIBAnwgokPrkRNlNAgQIECBAgAABAgS6LzCv+5uwBQIECBCYiMCqVauO\nX79+/TETWdYyBAgQIECAQHcEXEHqjqu1EiBAYNICmzdvnr9ly5a9J/1CLyBAgAABAgSmTUCB\nNG2UVkSAAAECBAgQIECAQL8LKJD6/QzafwIECBAgQIAAAQIEpk1AgTRtlFZEgAABAgQIECBA\ngEC/CyiQ+v0M2n8CBAgQIECAAAECBKZNQIE0bZRWRIAAAQIECBAgQIBAvwsokPr9DNp/AgQG\nRmDhwoVXLl68+JqBOSAHQoAAAQIE+lDA30Hqw5NmlwkQGEyBFStWnN9oNBatWbNmMA/QUREg\nQIAAgT4QcAWpD06SXSRAgAABAgQIECBAYGYEFEgz42wrBAgQIECAAAECBAj0gYACqQ9Okl0k\nQIAAAQIECBAgQGBmBBRIM+NsKwQIECBAgAABAgQI9IGAhzT0wUmyiwQIDIfA6tWrF23atOmI\n4ThaR0mAAAECBHpTQIHUm+fFXhEgMIQCa9euPWrDhg2HDOGhO2QCBAgQINAzAm6x65lTYUcI\nECBAgAABAgQIEJhtAQXSbJ8B2ydAgAABAgQIECBAoGcEFEg9cyrsCAECBAgQIECAAAECsy2g\nQJrtM2D7BAgQIECAAAECBAj0jIACqWdOhR0hQIAAAQIECBAgQGC2BRRIs30GbJ8AAQJNgXnz\n5u1MdgEhQIAAAQIEZk/AY75nz96WCRAgcAuBlStXnrtt27bDly1bdot+EwQIECBAgMDMCSiQ\nZs7alggQIDCuwIIFC7Y3Go3t4y5kJgECBAgQINBVAbfYdZXXygkQIECAAAECBAgQ6CcBBVI/\nnS37SoAAAQIECBAgQIBAVwUUSF3ltXICFBzcLAAAJUFJREFUBAgQIECAAAECBPpJwHeQ+uls\n2VcCBAZaYN26dQds3bp1/kAfpIMjQIAAAQI9LqBA6vETZPcIEBgegTPOOOO4jRs3Hj08R+xI\nCRAgQIBA7wm4xa73zok9IkBgYARG8kuokSMmejgjIyNzdu3a1Zjo8pYjQIAAAQIEpl9AgTT9\nptZIgACBlsApGXlXa8KQAAECBAgQ6H0Bt9j1/jmyhwQI9KXAyKHZ7dclC3IVacmcOY2v9+Vh\n2GkCBAgQIDBkAq4gDdkJd7gECMyYwBuzpRRHu1uuIo34edvEMCBAgAABAr0s4D/sXj479o0A\ngT4VGLlvdvy5bTt//47ptllGCRAgQIAAgV4SUCD10tmwLwQIDIpAfe9or46DyRWlkdt39N1q\nstHwjIZboeggQIAAAQIzKKBAmkFsmyJAYBgERp6co3zkKEd6WPpeO0r/TV1Lly69YPny5Zfe\n1GGEAAECBAgQmHEBBdKMk9sgAQKDKzCyX47tbeMc34tzFenuY81fsmTJZcuWLbtirPn6CRAg\nQIAAge4LKJC6b2wLBAgMj8ALcqiHJFeNkevS//pEI0CAAAECBHpUYF6P7pfdIkCAQB8KNOq7\nR/7uUR+eObtMgAABAgRaAq4gtSQMCRAgQIAAAQIECBAYegEF0tC/BQAQIECAAAECBAgQINAS\ncItdS8KQAAECsyywatWq49evX3/MLO+GzRMgQIAAgaEWcAVpqE+/gydAoJcENm/ePH/Lli17\n99I+2RcCBAgQIDBsAgqkYTvjjpcAAQIECBAgQIAAgTEFFEhj0phBgAABAgQIECBAgMCwCSiQ\nhu2MO14CBGZYYOSF+eOwdxt9oyO/l3l/ljwrOXz0ZfQSIECAAAECMymgQJpJbdsiQGDIBEZe\nnAP+++TutzzwkfzsHflU+j6fPDlZlVy4adNDF2SoESBAgAABArMooECaRXybJkBgUAVG5qcA\nenuO7p1jHOEfpP/xyRPnzGk8LMOFyU8vvPBP752hRoAAAQIECMyigAJpFvFtmgCBfhUYuV8K\noD9OXpqcnOzXcSTfyfSzk5d39Lcm64rStuTsGzsa12f4yW3bDpu/aNFdr7mxz78ECBAgQIDA\nbAgokGZD3TYJEOhjgZH3Z+e/n6Q4mvOc5KzkhymSDsyw1T6akSqC/qPV0TH8SqarqEqRVW2k\nbq178sKFN2z4m795w/rdXf4hQIAAAQIEZkVAgTQr7DZKgEB/CoycmP2uoqhujXtQct+M5wrS\nnPrjrk9Imq3xlsy7vDV162HjG+mr2+zem+JoXYaXJle94x0XfiRDjQABAgQIEJhFAQXSLOLb\nNAECfSdwbvb4ASl+PtO25z/J+K7kkLa+2xgdqYKqbr/7eVJF0ZeSB/zLvyzMrXsaAQIECBAg\nMJsC82Zz47ZNgACB/hJoXJ0rPvsm78t+H5vcI9krqV821XCi7Q1Z8M7J0Sm2dtz4opEVZ511\n6OlPecplP5joSixHgAABAgQITL+AK0jTb2qNBAgMrMDISTm0byV3ST6cPCq5QzKSNJKJtkdn\nwby+VRztftm/NBojO7/61QUHTXQlliNAgAABAgSmX8AVpOk3tUYCBAZX4E9yaBelsHnMzYc4\ncv+MV3E0mStIV2b5I25ex+6xe4yMNPa64IKvtD/soWMRkwQIECBAgEC3BVxB6raw9RMgMEgC\n38vB5La4kYck+fm5uzhqPVhh/0kcaP3x2Kfn9S9IbpcsyfQ75s276vpLL31XbuHTCBAgQIAA\ngdkScAVptuRtlwCBfhSoR3zXH3atx3TXL5h+nbwqeVqSomnC7R1Zsgqqv02qWKorUGvve9/X\nfv+qqzbXd5s0AgQIECBAYJYEFEizBG+zBAj0o0CjCqIn5YrP/AwPTl1zSfMoPjD60eyeX8VP\nR2vUU+/+Out5U4a5IjUnt9w1rjz44BPPvuqqjkVNEiBAgAABAjMqoECaUW4bI0BgMAQa1+Y4\nKnvYGjuzgnynSSNAgAABAgR6RcB3kHrlTNgPAgQIECBAgAABAgRmXUCBNOunwA4QIECAAAEC\nBAgQINArAgqkXjkT9oMAgaEXmDdv3s6kvp+kESBAgAABArMk4DtIswRvswQIEOgUWLly5bnb\ntm07fNmyZZ2zTBMgQIAAAQIzJKBAmiFomyFAgMBtCSxYsGB7o9HYflvLmU+AAAECBAh0T2DQ\nb7E7PnQvSR6RTPZY75vXrEg0AgQIECBAgAABAgSGRGCyRUO/sNQfYDwv+WRycvKZ5GPJ3slE\n2oFZ6D+T109kYcsQIECAAAECBAgQIDAYAoNaIL0hp6eKpHsmS5P6C/ePS56VTKS9MwstmsiC\nliFAgAABAgQIECBAYHAEBrFAqr9a/+Lk/cmW5qn6nww/lTy/OT3e4EmZWd+Q/sfxFjKPAAEC\n0y2wbt26A84777z5071e6yNAgAABAgQmLjCID2m4Yw5/v+S7HQw1/fiOvs7JI9JRhdELk3t1\nzpzk9H2y/ERv6Tvy0EMPnXP66aff9853vvO2SW7H4t0X2CubOPrb3/72A7q/KVsYZoG3vOUt\nj7rwwgvv6r02zO+CGTv23f8/5aEgd8/77foZ26oNDaVA3meH7tq1a4GfbYN7+rds2TLvGc94\nxpzLL798IA5yEAuko5tnpvMMXZn+A5LbJVc3l2kf1JWnM5LPJv+evDaZartrXvijpNY5ofac\n5zxnzlFHHfXtCS1soRkXyA/3t+21V9VJGoHuCSxcuHBOriLNyXvtv7q3FWsmcAuBD/jZdgsP\nE10SmDt3901LfrZ1yXe2V3vwwQfPqc+yb33rW2d7V6Zl+4NYIB3alNnaIXRNc/rADEcrkE5J\nf31n6Q+by+3J4KK8uLYzUd/j3/72t3/xyCOPPPS4447ziN89ke/Oa9dntS9N6jZNjUDXBFIc\n/ef111//4JGRkTt3bSNWTCAC11133T7z58/flNHfzfttLRQCXRZYlfUfljyzy9ux+lkSWLt2\n7d75LHv5LG1+2jc70Q/w077haVrhWVnPMW3relfGv9+cXtDWX6M1XcXHZTXR0ep2uip5fz+p\nWw3qFr2WTY3X63Ymk2nXTmLha3fs2DHnlFNOqcLthkm8zqIzIHDuuefm88PIdSeccMJVM7A5\nmxhigRNPPHFH3mtzvNeG+E0wQ4f+2c9+dt8USHPyfrvW+22G0Id4M+ecc059jtrhvTbQb4J9\nBunoWkVAvx7TN7LjdbWm1Wr8582J+k1Fezs8Excnu9o7m+MnZ7h/8rlR5l2Xvlcmbxtlni4C\nBAgQIECAAAECBAZIoN8LpFNHORd1k+uG5DHJF5JWOykj9TS70drH0vm9jhl/nOl6ml1dVfpp\nxzyTBAgQIECAAAECBAgMoEC/F0ijnZK6QvS3yRuTNcnXkuckD04emLTa8ozU30h6SVJXlirt\n7bczUbe7faW90zgBAgS6KZAHgnRz9dZNgAABAgQI3IZAXW0ZxHZ6Duqfk/qOUj2c4UXJC5If\nJ61Wfzz2eclEH8Xdep0hAQIEuiKwdOnSC5YvX35pV1ZupQQIECBAgMCEBAa1QNqRo1+Z1CO9\nFyX1EIYPJO3tFZmoX9WO9kS7Wu6vkjvUiEaAAIGZEFiyZMlly5Ytu2ImtmUbBAgQIECAwOgC\ng1ogtY62/ujqxa0JQwIECBAgQIAAAQIECIwnMOgF0njHbh4BAgQIECBAgAABAgRuIaBAugWH\nCQIECBAgQIAAAQIEhllAgTTMZ9+xEyBAgAABAgQIECBwC4FBfMz3LQ7QBAECBPpFYNWqVcev\nX7/+mH7ZX/tJgAABAgQGUcAVpEE8q46JAIG+FNi8efP8LVu2+NMDfXn27DQBAgQIDIqAAmlQ\nzqTjIECAAAECBAgQIEBgjwUUSHtMaAUECBAgQIAAAQIECAyKgAJpUM6k4yBAgAABAgQIECBA\nYI8FFEh7TGgFBAgQIECAAAECBAgMioACaVDOpOMgQIAAAQIECBAgQGCPBRRIe0xoBQQIEJge\ngYULF165ePHia6ZnbdZCgAABAgQITEXA30GaiprXECBAoAsCK1asOL/RaCxas2ZNF9ZulQQI\nECBAgMBEBFxBmoiSZQgQIECAAAECBAgQGAoBBdJQnGYHSYAAAQIECBAgQIDARAQUSBNRsgwB\nAgQIECBAgAABAkMhoEAaitPsIAkQIECAAAECBAgQmIiAhzRMRMkyBAgQmAGB1atXL9q0adMR\nM7ApmyBAgAABAgTGEFAgjQGjmwABAjMtsHbt2qM2bNhwyExv1/YIECBAgACBmwXcYnezhTEC\nBAgQIECAAAECBIZcQIE05G8Ah0+AAAECBAgQIECAwM0CCqSbLYwRIECAAAECBAgQIDDkAgqk\nIX8DOHwCBAgQIECAAAECBG4W8JCGmy16YWyfXtgJ+3Brgc2bN++b3gNuPUcPgekTGBkZ2au5\nNu+16WO1plEETjvttH1e+9rXzrn00kv3y2zvt1GMdE2fwPbt2+elNbJGn3Omj7XX1jRQ51aB\n1Btvr+3N3bi6N3bHXrQLfOhDH5pz9tlnf7i9zziBbghccsklc253u9vVqrd2Y/3WSaAl8LnP\nfW7Ofe5znzlnnnnmV1p9hgS6JfD6179+zgEH7K7Dr+/WNqy3ZwRu6Jk92YMdqWpe6w2B47Ib\ne/fGrtiLDoGzM10F0g86+k0SmG6Bk7LC+yVvne4VWx+BDoH6BenpyZuT9R3zTBKYboE/ygrr\nPffn071i6+spgSqOvt9Te2RnCBDomsDlWfOTu7Z2KyZws8CrM/rtmyeNEeiaQN02PJKc0LUt\nWDGBmwVOy+jHb540RqC3BTykobfPj70jQIAAAQIECBAgQGAGBRRIM4htUwQIECBAgAABAgQI\n9LaAAqm3z4+9I0CAAAECBAgQIEBgBgUUSDOIbVMECBAgQIAAAQIECPS2gAKpt8+PvSNAgAAB\nAgQIECBAYAYFFEgziG1TBAgQIECAAAECBAj0toACqbfPj70jQIAAAQIECBAgQGAGBRRIM4ht\nUwQIECBAgAABAgQI9LaAAqm3z4+9I0CAAAECBAgQIEBgBgUUSDOIbVN9K3BD9ryiEei2wPZs\nwHut28rWXwK7kp2J91tpaN0W8P9ot4WtnwABAjMssCjb22uGt2lzwykwP4d9p+E8dEc9CwK/\nOQvbtMnhFLh9DvvQ4Tx0R02AAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECA\nAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECA\nAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECA\nAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECA\nAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECAAAECBAgQIECA\nAAECBAgQIECAAIHJCuw12RdYnsCACxyf41ue7Jf8LBlJxmtzM/Ok5InJvZOrkisTjcBYApN9\nj9V6FiZPS45KfplsSzQCtyUwlffNsVnp7ye/leyfbEg0ArclUO+VxydLkquTK5LJtPp/94hk\n/WReZFkCBAgQ6K5A/XA/L/lFsibZmvxbsncyVrtdZnwvqSLqnORXyQ3JikQj0CkwlfdYreNN\nybXJF5ONyYbkbolGYDyBqbxv/iYr3JXU++yHSf1s+3QyL9EIjCXw8Myo/zO/n9T/hduTZyYT\nbY/MgjuT90z0BZYjQIAAgZkRODWb+Uly++bm6mrQNcnzmtOjDd6eziqIatlq9SHiH5Pqu0ui\nEWgXmMp77CFZQX1weERzRftl+I3kC81pAwKjCUzlffPQrKgKolcndWW82mOT6ntxTWgERhHY\nN33/m5zWNu+VGb8+Obytb6zRBZlxcbIjUSCNpaSfAAECsyDQyDavS+qHenv7aCbqCtFYrX6z\n+q8dM++X6fpA8aSOfpPDLTDV99gHw7a2g67eW/Vb/qM7+k0SaAlM5X3zwrz450l9YG1v9Yuj\nj7R3GCfQJvD4jNf/eYvb+upqed1u/oq2vrFG6721Ovnv5N1jLaSfwEwLzJ3pDdoegR4UuGP2\nqX4z/92Ofavpe3b0tU+enIk/bO/I+AnN6Ys7+k0Ot8BU32P1oePcDrp6X1bBNd57s+MlJodM\nYCrvm/fGaGGyuc2qrgAsSvw8a0MxeguB+kXNpmRdW2/9wrEKnnu19Y02+rR0/m5Sd2pUkaUR\n6BmBuT2zJ3aEwOwJtH4Tf3nHLtTDFg5IbtfRP9Zk3Z73suRbyQ/GWkj/UApM9T22KFqd78tf\nNwWr6NIIjCawKJ3T8b75i6ynbn36p0QjMJpA/Wy7YpQZ9f/neD+j6jb0ui3vuUkVWBqBnhJQ\nIPXU6bAzsyRwaHO7Wzu2X99BqnbgjYNx/63bUj6dHJw8K6lboDQCLYGpvscOywpa78PWuuq3\ns/Xb1om8L1uvMRwugel437w2ZPXdo5ck/zdcfI52EgL1s63z/856+bXJWL9crM+eH0z+PTkr\n0Qj0nIAn0/TcKbFDXRaoH8bHtG3jXRn/fnO68977mt6eXNacP9bgyMz4XFJXkB6VXJRoBNoF\nftWcmOx7rN579b5qb7+RiUZSj6HXCIwmsCfvm72ywtOT5yT1vaT3JxqBsQTqZ9sJo8ysn3Vj\n/Yx6ReYtSpYndXt7tSqa6jNpTdcDHtxyFwRt9gQUSLNnb8uzI/CNbLa9gKnx+mJytfqta3ur\n++8vTsa7GnT3zP9iUrcT1H8SrXVlVCNwk0DrfTHZ99gvsoZ6H7a31jo2tHcaJ9AmMNX3zT5Z\nx0eSk5J6GIjf7gdBG1eg3mutK+TtC9bPqbXtHW3jVRgdlXTeWlffWaqifFGyMdEIECBAYBYF\n6jdX65N3dOzD1zP9yY6+9slFmfhlUo9cdrtTELQxBab6HluVNVaRXleMWq1ue6rb7OpKkkZg\nNIGpvm+qIKorAg8abaX6CIwi8JD01dWeekx8q90pI/XnCZ7e6ugYHpfpR3Wk/g/+RLOvriJp\nBAgQINADAi/JPtRjSes3p/snpyTbkvqNVqvVb73+IWn98K4PE/VB9flJPY2nPYszrRFoF5jI\ne+zNecFL215UX2Su2zyrvx4Y8uCkfmNbf6tGIzCWwETeN4vy4vp59vDmSp6RYX3QPS1p/1lW\n449MNAJjCXwzM85N6n1XV5M+lXwvqds1W63zZ1urvzU8PyPvbk0YEiBAgEBvCNTtpu9M6sNo\n3VL34+SZSXt7WybqA0R98fSI5nhNj5a6f18j0C4wkfdY3VZydvuLMv6E5PKk3pdXJO9L3B4d\nBG1cgdt631SxXT+7Wj+r6vbj0X6WVV/nezJdGoGbBKow+k5S75UbkjVJ+y8XM7n7lrnx3kcK\npFLSCBAg0KMCdXWofthrBLolMJX3WN1id3SiMOrWWRnM9XrfDOZ57dWjqu8d1ZNcNQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQIECBAg\nQIAAAQIECBAgQIAAAQIECBAgQIAAAQL9KNDox522zwQIEBhQgXvmuB43zrF9LvP+Z5z5k521\nX16wbbIvmuTyh2T5FyRvmuTr2hc/PhMPTc5LvpHsSm6rLcwCJyebkq8kv07aW/3/91vJ/ZJz\nk7XJSNLeat9PSn4jWZP8NOlsdb46/y/9Vfq+27lgx/TBmX598tKktntE8qCks9Ux/6yt89iM\nPzypc1fz6tgm05Zn4bL4UtuLjsr4KcklyRnJVUl7e3smPpjU9trbqkzUvEvbO40TIECAAAEC\nBAgQmC6Bp2VF9WG5PmD/fJQ8JX3T1f4kK/q36VrZGOuZl/4vJ9eOMf+2uvfPAvWh/BdJFShb\nk9rnvZPxWhVjtc0vJhuTDcndkla7e0aqGLgi+WZSBVcVBrW/rfawjFyWbE/OSVrLZPSmtihj\ndb46c/ZNS4w98o7MWtk2+xUZ71xPTdd5arW/yUjtRx3TD5Oa/+mkfb8zOWZ7ZObsTN7TscRP\nMn1m8q7k4qS94KsC8YJkr6SzPScd7+/sNE2AAAECBAgQIEBgugRaBVJdSep2+0Q28JkubqSK\nkLraUx/ip1ognZrX1of32yfV7p1ckzyvJsZoD0l/FQGPaM6vKy21H19oTtfg48l3kn1qIu2R\nSe1nqwCt/ouSHyVHJdXukWxJXl4TzbYswypY7pQc2Jba5nhtcWauT/ZtW+gjGa99bF9PjbeK\nn7qCVvv46mRuUu2xSfW9uCZuoy3I/Cp+diTtBdK9Ml1FYBWj1X6VnLB77MZ/1mbw1Lbp9tEq\nmur83Ke90zgBAgQIECBAgACB6RKYTIF0x2z0SUl9YP+j5Miks9UH9UcmL0zar6A8ONNVIHwv\nOTlpfTjO6JxHJS9Jap31wb+93S8T909qXS9Iqggard03ndcl5yb1YXy0Aqk+mNe260P2aK2u\nYtQ6Xtkx86OZrv0eq30wM+pDfXsrpypkjk7qWE9Pfi9ptdqHzclbmx0PyHC0wqPWfUlzmRq8\nIfm/tumJjv5rFqwrSO3tx5l4U3tHx3idw58nVei0typQqri6rVbLrE7+O3l328Jls6Ft+rsZ\nX9GcrnnnJXUuxmp/lRmfHWumfgIECBAgQIAAAQJ7IjDRAqmudNT3RC5OvpZsS65NTkxarQqm\nnyV1deBbyfVJXaGoD7t/l9T3UKooqGLjiGR+UuuqwuBHydVJbaP96sGZma7b1n6Z1HL/mYzW\n6orC/0uq8HhZUld9Olt9d6XWcUDnjOZ07VPNf2RzujWo9W1tTYwy/Gb6TuvoX5jpWtdjO/pb\nk8/KSM1/XLOjlqvpzu8EvbLZf4fmcp/M8GPJA5M3JLVvta3x2l0ys9b90LaFqmirKzt1/p+Q\nvCV5RtK6epTRUdvh6b0hqeXHa7Xey5LDkvOT9gKpCq5ax0FJba/O1W8mc5Mqpp6YjNeOzcw6\nnnuPt5B5BAgQIECAAAECBKYiUB9k68PmmUldYWhPXW2ptk9SBcqZSasdmJH6APyJVkeGVeR8\nNWldWbp7xuuDcG2jWi37md1jN/7zdxnUd3KWNPvqA/O/JPWBuT7UVzszqf370+R2SRUxt9Wq\naKh1dLb6QP34pIqo0drD0lnbqmKrvT0zE9Vf2x+tXZLOKlbaWxV/9Zo/ae/M+GOS/0lq3p8l\nrVZW1ffXrY7m8JvN/ns2pzdmWKb/l3w12ZlU4dkyzOitWh3zrmSftjkPznhtr5yqmL2gOb02\nwzq3Y7U6Z1UY322sBdJf5672qbZbrbNAqr4zkiqGvpe0it6nZ/y7yURaXelrva8msrxlCBAg\nQIAAAQIECExIoD5k1gfl1ofV+sDayouba6iCoj6gVwHTarfPyJeTbzQ7qiiq9fxOc7o1qKJj\ncXOis0DalP6/aS3YHNaVkVrPy5vTZ2a4pTk+0cFYBdJtvb6upNS2F3UsuLzZP1Zxdn3m15We\n9tbIRBUlL2nvzPjS5HXJj5P1ye8mrfbZjNQVttcnv5W8N6kitPbpXsneyb8mr0larYqRi5J1\nSV2BGa29Kp2Xdsyoq0lnJbWdVluWkdrWqlZHx/C1zfnP7ehvn6x9+Gryj22doxVINfvY5AHN\n5eZlWEVf+ZTd85NTk3sno7WfpLPzvTPacvoIECBAgAABAgQITEqgVSC1rlCM9eK6xev1yeeT\n1lWMrRn/dlLt5KQ+XN+5JsZo7QXSIVmmlq+rBu2tPhzXh/nTm51nZviD5vhEB1MtkE7IBmqf\n7t+xoSoIbkjGKkAuzrzOD+tVQNa6npSM1cquCtNWK5OPJ7WtukKyOnlqUutZmIzVXpcZtczd\nx1jgg+mf6JWZurp1Xsd6qkB+X7IjeUHHvM7JP0/HhuTQZL9map1/3xyv8ztae146v96csTLD\nKvpqXZck9d7qbF9KR72fNAIECAyEwFj/wQzEwTkIAgQIDKDAghzTd5L/l3wr+ZPk4GRN0mp1\nq1e1+lDc3sb6QLytuVDn8vVBv9ZVRVKrtZZtTXdr+PPmig/r2MDhmb44qStCo7VfpLOWaW+t\ndWxIZxUYi5N9kvb20UzUFZIjmp1XZPiU5HbJQcmypIqmq5O6xbEsy33vpL1d2JwY79a432h/\nQcbrik2tu7NdkI4D2jprn+uqVRWyVexVoTReq6ttRyWbkiryKnX164XN8bri1dn2TcdfJn/R\nnFHbeVfy1uSfk1pnZ+s8ns75pgkQINBXAgqkvjpddpYAAQK7n752dBx+P/mrpH57f01SH+7r\nw3+1+mBd7fgbBzf9+82Mta4GVfHT+j+gXr8xWZK0t9/MxJ2SH7Z3ztB4FUgbksd0bO+kTP9P\nR1/7ZB3jo5P2YrDWUYXdT5P7NIfPy7C9/VYm6mpRFUZVsHw8qaLo+qRVFD4141WIVtH4wKSW\nfVHS3p6ciSpEWoVS+7wavzQp1/bC6o2ZrqKrvWCpwqiOtf2K3X9kus7RI5KzkttqK7LA73Rk\nQ6ZXN/suy7CzVfH0v8nXmzPukWHdbldtXfKg3WO3/OeYTNZxaQQIECBAgAABAgSmVeBpWVsV\nLvccZ62LM68+oL822S85IqkrCfW685NWqw/4Fyd/nByS1PdvdiT1gbfah5L1yW8n+yfPT2r+\nW5MjkycmVRjVbWd1i1q1M5Pv1Mgk2suybBVgne0p6fiHZN/OGW3Ttc9XJScltY+nJFWs1FWQ\nVntzRl7amsjwLsn2pPqryHhwUleVXp1Uq8KpjqFsTkzq9rPaxyqO3pa02jsz8uPk2OSgpIqY\ny5M7JdXmJt9PLkkenRyW1DZq/96QjNWqsK1z1ToPtVwVbfW6TybHJPdN6vzVPj0gqfaMpF53\nWvK0jjwy09UWJf+QPDwZq9V75N1jzCyvXybHt83/cMb/vDn9txm+o21ejS5Mar+eWRMaAQIE\nCBAgQIAAgekUqA++9WFzvAKptveXSX0wv76Z92T48uZ4fZivVsOPJlX01DqvSVYmrVbFwZak\n5j0iqcKh1lEFSfXVVZDPJ3dIWu3MjFRxMZn2sixc2+5sb09Hbac+lI/V5mVGFSpV8OxKqmB5\nZtLeNmbi7PaOjD8hqWKmXnNF8r6k1tVqd8rI55Lafi1Tjm9K6ha2VrtjRspva1Lb/0byu0l7\nq2JsTdJaz9UZ/4ukLMdqB2ZGFUN/0LHA4zJdRVutq7IuqeK11Wr7rXmdw9bxVzFY857TetEo\nw/EKpFdl+dUdr3l0pqvA/I+k9u+BSXur4nVnclh7p3ECBAgQIECAAAECMy1QH8KPTtpv1Rpt\nH+rKy12T9g//reVqHQe3JprDujJS6923o382J/fLxqsYmUxr+bQXRp2vr2M/JhnPcH7m11Wm\n8dqCzCzjsptIe1cW+vIoC9Y+H5lUcTYbrQr0xaNsuK4gVtFZ56GzfTId/9TZaZoAAQIECBAg\nQIAAAQITFTgoC9YVrrri08+tbnXcksxWQdfPdvadAAECBAgQIECAAIE2gT/NeN221s/tzOx8\n3ZanESBAgAABAgQIECBAYI8E6ta/uqWtbqvr1/bU7Hgv3YrZr472mwABAgQIECBAgAABAgQI\nECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI\nECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI\nECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI\nECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI\nECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI\nECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI\nECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQIECBAgAABAgQI\nECBAgACB6RP4/wGpDH+M84kZkwAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “Representación simultanea de carreras y edades”"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(acs,cframe=1.1,\n",
    "     main=\"Representación simultanea de carreras y edades\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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BAgQIAAAQIECPQtoEDqm8wCBAgQIECA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\nAElFTkSuQmCC",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotct(K,\"row\",col=c(\"red\",\"yellow\",\"green\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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1tXCRAgQIAAAQIECBCYXkCBNL2PuQQIECBAgAABAgQINEhAgdSgk62rBAgQIECA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\nRK5CYII=",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotct(t(K),\"row\",col=2:8)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La representación simultánea permite la lectura de los planos de perfiles y columna, ya realizadada y adicionalmente la lectura simultánea como la atracción o \"jalonamiento\" de las  coordenadas de los perfiles columna a cada una de las filas y, simétricamente, los de las filas a cada uno los perfiles columna.  La posición de Matemáticas sobre el primer eje se debe a que *a19M* la jalona, porque Matemáticas tiene mayor proporción de 19 o más años de edad que los demás perfiles y a que *a19M* tiene una coordenada positiva alejada del centro. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6rwpZBz_e1FC"
   },
   "source": [
    "# **Ayudas para la interpretación**\n",
    "\n",
    "**Contribución absoluta** La contribución de un perfil a la varianza del eje (inercia proyectada), depende del peso y de la coordenada al cuadrado: \n",
    "\n",
    "$$\n",
    "Ca_s(i) = \\dfrac{f_{i\\cdot}(F_s(i))^2}{\\lambda_s}\n",
    "$$\n",
    "\n",
    "**Coseno cuadrado:** calidad de la representación o contribución relativa:\n",
    "\n",
    "$$\n",
    "Cos^2_s(i) = \\dfrac{(F_s(i))^2}{d^2(i,\\mathbf{g})}\n",
    "$$\n",
    "\n",
    "¿Por qué cree que se da el nombre de **contribución relativa**?\n",
    "\n",
    "$$\n",
    "Cos^2_s(i) = \\dfrac{F_s^2(i)}{d^2(i,\\mathbf{g})} =  \\dfrac{f_{i\\cdot} F_s^2(i)} {f_{i\\cdot} d^2(i,\\mathbf{g})}\n",
    "$$\n",
    "\n",
    "Contribuciones del punto  a la inercia:  proyectada sobre el eje *s*  en el espacio completo\n",
    "\n",
    "Inercia sobre el eje *s*: \n",
    "    \n",
    " $$\n",
    " \\sum\\limits_{i=1}^n f_{i\\cdot} F^2_s(i)$\n",
    " $$\n",
    " \n",
    "Inercia en $\\mathbb{R}^p$:  \n",
    " \n",
    " $$\n",
    " \\sum\\limits_{i=1}^n f_{i\\cdot} d^2(i,\\mathbf{g})\n",
    " $$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Ayudas para la interpretación  del ejemplo"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Tabla e hitograma de valores propios"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 3 × 3</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>inertia</th><th scope=col>cum</th><th scope=col>cum(%)</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Ax1</th><td>0.040</td><td>0.040</td><td> 52.423</td></tr>\n",
       "\t<tr><th scope=row>Ax2</th><td>0.024</td><td>0.063</td><td> 84.002</td></tr>\n",
       "\t<tr><th scope=row>Ax3</th><td>0.012</td><td>0.075</td><td>100.000</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 3 × 3\n",
       "\\begin{tabular}{r|lll}\n",
       "  & inertia & cum & cum(\\%)\\\\\n",
       "  & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tAx1 & 0.040 & 0.040 &  52.423\\\\\n",
       "\tAx2 & 0.024 & 0.063 &  84.002\\\\\n",
       "\tAx3 & 0.012 & 0.075 & 100.000\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 3 × 3\n",
       "\n",
       "| <!--/--> | inertia &lt;dbl&gt; | cum &lt;dbl&gt; | cum(%) &lt;dbl&gt; |\n",
       "|---|---|---|---|\n",
       "| Ax1 | 0.040 | 0.040 |  52.423 |\n",
       "| Ax2 | 0.024 | 0.063 |  84.002 |\n",
       "| Ax3 | 0.012 | 0.075 | 100.000 |\n",
       "\n"
      ],
      "text/plain": [
       "    inertia cum   cum(%) \n",
       "Ax1 0.040   0.040  52.423\n",
       "Ax2 0.024   0.063  84.002\n",
       "Ax3 0.012   0.075 100.000"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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gQIECAwKiAgjQqqJ0CAAAECBAgQIECgjICAVGaUNkKAAAECBAgQIECAwKiAgDQq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\nNAAAAABJRU5ErkJggg==",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ayuacs<-inertia(acs,T,T)\n",
    "cat(\"\\nTabla e hitograma de valores propios\")\n",
    "round(ayuacs$tot.inertia,3)\n",
    "barplot(acs$eig[3:1],horiz=TRUE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "klqGkUdYe1FB",
    "outputId": "8a268657-212b-4b4f-a285-7113551f793e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Coordenadas y ayudas para la representación de las carreras"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 7 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>Axis1</th><th scope=col>Axis2</th><th scope=col>Ca.Axis1</th><th scope=col>Ca.Axis2</th><th scope=col>cos2.Axis1</th><th scope=col>cos2.Axis2</th><th scope=col>conInercia</th></tr>\n",
       "\t<tr><th></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></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>Biol</th><td>-0.10</td><td>-0.02</td><td> 3.62</td><td> 0.15</td><td>-65.65</td><td> -1.68</td><td> 2.89</td></tr>\n",
       "\t<tr><th scope=row>Esta</th><td>-0.03</td><td> 0.14</td><td> 0.33</td><td>12.59</td><td> -3.65</td><td> 83.05</td><td> 4.79</td></tr>\n",
       "\t<tr><th scope=row>Farm</th><td>-0.04</td><td>-0.22</td><td> 0.51</td><td>31.90</td><td> -2.11</td><td>-79.05</td><td>12.75</td></tr>\n",
       "\t<tr><th scope=row>Fisi</th><td>-0.10</td><td>-0.05</td><td> 4.78</td><td> 1.69</td><td>-74.24</td><td>-15.78</td><td> 3.38</td></tr>\n",
       "\t<tr><th scope=row>Geol</th><td>-0.27</td><td> 0.28</td><td>19.03</td><td>32.73</td><td>-48.96</td><td> 50.73</td><td>20.37</td></tr>\n",
       "\t<tr><th scope=row>Mate</th><td> 0.48</td><td> 0.14</td><td>68.23</td><td> 9.64</td><td> 89.58</td><td>  7.63</td><td>39.93</td></tr>\n",
       "\t<tr><th scope=row>Quim</th><td> 0.10</td><td>-0.14</td><td> 3.49</td><td>11.29</td><td> 11.52</td><td>-22.43</td><td>15.90</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 7 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & Axis1 & Axis2 & Ca.Axis1 & Ca.Axis2 & cos2.Axis1 & cos2.Axis2 & conInercia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\tBiol & -0.10 & -0.02 &  3.62 &  0.15 & -65.65 &  -1.68 &  2.89\\\\\n",
       "\tEsta & -0.03 &  0.14 &  0.33 & 12.59 &  -3.65 &  83.05 &  4.79\\\\\n",
       "\tFarm & -0.04 & -0.22 &  0.51 & 31.90 &  -2.11 & -79.05 & 12.75\\\\\n",
       "\tFisi & -0.10 & -0.05 &  4.78 &  1.69 & -74.24 & -15.78 &  3.38\\\\\n",
       "\tGeol & -0.27 &  0.28 & 19.03 & 32.73 & -48.96 &  50.73 & 20.37\\\\\n",
       "\tMate &  0.48 &  0.14 & 68.23 &  9.64 &  89.58 &   7.63 & 39.93\\\\\n",
       "\tQuim &  0.10 & -0.14 &  3.49 & 11.29 &  11.52 & -22.43 & 15.90\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 7 × 7\n",
       "\n",
       "| <!--/--> | Axis1 &lt;dbl&gt; | Axis2 &lt;dbl&gt; | Ca.Axis1 &lt;dbl&gt; | Ca.Axis2 &lt;dbl&gt; | cos2.Axis1 &lt;dbl&gt; | cos2.Axis2 &lt;dbl&gt; | conInercia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| Biol | -0.10 | -0.02 |  3.62 |  0.15 | -65.65 |  -1.68 |  2.89 |\n",
       "| Esta | -0.03 |  0.14 |  0.33 | 12.59 |  -3.65 |  83.05 |  4.79 |\n",
       "| Farm | -0.04 | -0.22 |  0.51 | 31.90 |  -2.11 | -79.05 | 12.75 |\n",
       "| Fisi | -0.10 | -0.05 |  4.78 |  1.69 | -74.24 | -15.78 |  3.38 |\n",
       "| Geol | -0.27 |  0.28 | 19.03 | 32.73 | -48.96 |  50.73 | 20.37 |\n",
       "| Mate |  0.48 |  0.14 | 68.23 |  9.64 |  89.58 |   7.63 | 39.93 |\n",
       "| Quim |  0.10 | -0.14 |  3.49 | 11.29 |  11.52 | -22.43 | 15.90 |\n",
       "\n"
      ],
      "text/plain": [
       "     Axis1 Axis2 Ca.Axis1 Ca.Axis2 cos2.Axis1 cos2.Axis2 conInercia\n",
       "Biol -0.10 -0.02  3.62     0.15    -65.65      -1.68      2.89     \n",
       "Esta -0.03  0.14  0.33    12.59     -3.65      83.05      4.79     \n",
       "Farm -0.04 -0.22  0.51    31.90     -2.11     -79.05     12.75     \n",
       "Fisi -0.10 -0.05  4.78     1.69    -74.24     -15.78      3.38     \n",
       "Geol -0.27  0.28 19.03    32.73    -48.96      50.73     20.37     \n",
       "Mate  0.48  0.14 68.23     9.64     89.58       7.63     39.93     \n",
       "Quim  0.10 -0.14  3.49    11.29     11.52     -22.43     15.90     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Promedio de contribución para las carreras 14.29"
     ]
    }
   ],
   "source": [
    "# carreras\n",
    "cat(\"\\nCoordenadas y ayudas para la representación de las carreras\")\n",
    "round(cbind(acs$li,Ca=ayuacs$row.abs,cos2=ayuacs$row.rel,conInercia=ayuacs$row.contrib),2)\n",
    "cat(\"Promedio de contribución para las carreras\",round(100/7,2))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La contribución absoluta (Ca) promedio es un umbral para poner atención en las categorías que tienen valores por encima del promedio: en el primer eje *Geol* y *Mate*, en el segundo eje *Farm* y *Geol*.\n",
    "\n",
    "*Quim* es la única categoría que tiene una calidad de representación en el primer plano factorial un poco baja: 11.52+22.43 = 33.95%. Los cosenos cuadros son positivos, el signo es el de la coordenada.\n",
    "\n",
    "En el espaco completo las categorías que más contribuyen a la inercia son: *Geol*, *Mate* y *Quim*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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AAAIIIFDoAjSQCv0IsX0I\nIFBWAokEz2goqwPOziKAAAIIFJwADaSCOyRsEAIIlKvA0KFDpwwbNuyTct1/9hsBBBBAAIFC\nEKCBVAhHgW1AAAEEJDB48OBptbW1n4OBAAIIIIAAAl0nUOo/FDtItNsqrypPKy1KtuIG4+7K\nhsosZbzyrkJBAAEEEEAAAQQQQACBMhAo1QZSTx2755VVldeV3ysPK4cpc5V0ZTlVPqFsqUxU\nBihVysnKNQoFAQQQQAABBBBAAAEESlygVG+xO1fHzY2kDZShytbKXsoRSqZyjkZsqmysbKN8\nT/mrcoWylkJBAAEEEEAAAQQQQACBEhcoxQaSHwF1knKD4tvkXCYr9yvHeCBDWU/19yme1uU7\n5Sqlm7KFQkEAAQQQQAABBBBAAIESFyjFW+xW1zFbRnkh5dh5eJ+Uuujg3tGBoN9Xklzen9/h\nXwQQQKDjBEaNGjVo6tSp/rCGggACCCCAAAJdJFCKDaT+geX0FNMvNNxb8XeNZqeMSze4gipP\nUZ5RXkk3QZY6r+N0pXuWaaKj+u2www4VI0eOvHDppZdu60ES0fno7xyBXvptmp8+99xzW3XO\n6lhLuQpcddVVm86ZM6e3Xmt/KFcD9rtzBPQ3bWmvSd3j9Xrbv3PWylrKVWCppZbapqWlhb9t\nJfwCmDdv3lJnnXVWxdNP+5loxV9KsYG0SnBYmlIOz1fB8LLqttVA8sMZHlBWUnxlKddGSy/N\ns4ni2/PilDX69Onj/6g2UebFmYFpOlVgaR2XtZQenbpWVlZ2At27d19OJxJ+vX2/7HaeHe5s\ngfAW+4F6vYX/b3b2NrC+MhFQ42hlvc78oTF/20r0mOsD/oTPZSmFK+Db4pLKD1I28SgNf6uE\n/ymkjF4wuKb6Xlc+UDZaUNuxPUdr8d5mX+GiFJjAxIkTpz///PMHFNhmsTklKDBkyJBHBw4c\n+GUJ7hq7VGACDz/8cA/9bUvqb1t4K3mBbSGbU0oCep39WbmrlPaJfVlMwA1gn8v653WKvrTV\nWCjGHfwo2Gg/4jta3Kz1d4myXQ1aV+N9S50f0OD/NMIHNqiXggACCCCAAAIIIIAAAqUuUKoN\npHoduD1TDt4eGs7W4KnR+AnKW8r2StjQUi8FAQQQQAABBBBAAAEEykGgFL+D5CtElykXKOOU\np5RfKP6C/eZKWIapZ6jyS6VZuVLxgxl8CXhfJVr8o7N10Qr6EUAAAQQQQAABBBBAoPQESrGB\n5KN0tTJA8YMW/KSeKcqxyhtKWPzjsf7uz6nKikr4mO/r1J9a/P0lGkipKgwjgEBeBaqrq7/Q\nQxq+evfdd/O6XBaGAAIIIIAAAvEFSrWB5O8QjVDOVMLvHqWqnKYKx2W24h+YpSCAAAJdJjB8\n+PDX9KSnmnHjfPGbggACCCCAAAJdIVCK30GKOvrWufejFfQjgAACCCCAAAIIIIAAApkESr2B\nlGm/qUcAAQQQQAABBBBAAAEEFhOggbQYCRUIIIAAAggggAACCCBQrgI0kMr1yLPfCCCAAAII\nIIAAAgggsJhAqT6kYbEdpQIBBBAodIGxY8fWNDY29i307WT7EEAAAQQQKGUBGkilfHTZNwQQ\nKCqBSZMm9auvr1+5qDaajUUAAQQQQKDEBLjFrsQOKLuDAAIIIIAAAggggAAC7ReggdR+O+ZE\nAAEEEEAAAQQQQACBEhOggVRiB5TdQQABBBBAAAEEEEAAgfYL0EBqvx1zIoAAAggggAACCCCA\nQIkJ0EAqsQPK7iCAAAIIIIAAAggggED7BWggtd+OORFAAIG8ClRWVs5TWvK6UBaGAAIIIIAA\nAjkJ8JjvnLiYGAEEEOg4gREjRkxsbm7uU1tb23ErYckIIIAAAgggkFWABlJWHkYigAACnSdQ\nVVU1N5FIzO28NbImBBBAAAEEEEgV4Ba7VBGGEUAAAQQQQAABBBBAoGwFuIJUtoeeHUegrAV6\naO9PakPgFo3/tI1pwtHd1fOdwveHQhG6CCCAAAIIFKkADaQiPXBsNgIILJFAL819sfKl0pRh\nSY+rPk4DaQNNd6+ypfKVQkEAAQQQQACBIhaggVTEB49NRwCBJRY4V0u4dAmXspnmX38Jl9E6\ne11dXe+mpiY33igIIIAAAggg0EUCNJC6CJ7VIoBAUQkM1NbuonRTXlcmKEllTcUNJJc9lFeU\nOg+orK5sq/RXPlH+rXygZCyjR4/esqGhwdNTEEAAAQQQQKCLBGggdRE8q0UAgaIROFRberPy\ntvK5srXypLKn4sbRAYrLb5TLFDeQDlRuVGYqUxXP4+8n7av8S0lbkslkRUtLSyLtSCoRQAAB\nBBBAoFMEaCB1CjMrQQCBAhUYpu1aN822uVHzh6D+t+pep5wQDPtK0oPKIOV+ZVnlVmUHxd9B\n8gMbrlT8vaQjFBdP857iZWRsIGkcBQEEEEAAAQS6WIAGUhcfAFaPAAJdKtBHa18vzRZEn0bn\nq0A7K76FbrzyhJLte0LzNN7TRx/wsLSGJyurKBQEEEAAAQQQKGABGkgFfHDYNAQQ6HCBq7WG\nth7SMFzT+GrQI8rXihtI1yq+ipSuuIH0hXKy4u8g+QEOfZVvlf8qFAQQQAABBBAoYIGlCnjb\n2DQEEECgEARe1Uaso/xQ8aPB11QeUA5T0pUqVT6n/FR5RjlSWUkZp1AQQAABBBBAoMAFuIJU\n4AeIzUMAgS4V8A/KjlL8XaPHlGeV8xR/n8gPafB3j/w0O5fw4Qq7qb+/sqkSXjHyuI0U366X\ntSQS4WKyTsZIBBBAAAEEEOggARpIHQTLYhFAoCgENtdW+il16YqvHPl7QysqlytHKa8pQ5Q1\nFF8lcmma32l9mp1vv3tJ8XeYahU/+c7zn6P4YRCvKxnL0KFDp8yYMaP/yJEjM07DCAQQQAAB\nBBDoWAFusetYX5aOAAKFLeDb5HwVKF32Czb91+pOUR5WZiue9hLlGsXlaeU/yhjlDKVOOUc5\nRpml1CtzlVMVN5LcYEpbBg8ePK22ttaPEqcggAACCCCAQBcJVHbRelktAggg0JUCM7TyuPey\nva9pD1D8JLq1lAbFV4jC4tvmNlOqlPBq0vnqv0CpUT5U3EByaeuBEPOn4l8EEEAAAQQQ6DIB\nGkhdRs+KEUCgyAT8dDr/PlKm4oZStPi7Sdmmj05LPwIIIIAAAggUiAC32BXIgWAzEEAAAQQQ\nQAABBBBAoOsFaCB1/TFgCxBAAAEEEEAAAQQQQKBABLjFrkAOBJuBAAIIjBo1atDUqVPXQwIB\nBBBAAAEEuk6AK0hdZ8+aEUAAgUUEZs6c2WvWrFndFqlkAAEEEEAAAQQ6VYArSJ3KzcoQQAAB\nBBBAAAEEEFhM4Geq6aO8qDy12NiKCl/UOFnxE1WvU/yzE3HLMpqwOe7ETFdRQQOJVwECCCCA\nAAIIIIAAAl0rcIpW/wPlBWXrNJsyWHXhT0Xcof64DaQjNe0eykEKJaYAt9jFhGIyBBAoe4Ee\nEviT4h9/9SO9RyncDicECgIIIIBAXgQ+1VK2UvqlWdpPVOf/f3It+2iG3rnOVO7T00Aq91cA\n+48AAnEFrtCExyjLKysoJyl/VCgIIIAAAgjkQ2CCFvKZcmDKwnzHl3+w/L6Ueg92V4YoJyhH\nK9GrT25sra741r29lZ5KWGrU49v6hiubK5SIAA2kCAa9CCCAQAaBhOqPUHwVKSz+T+mocIAu\nAggggEDZC/gDNN/KdrBS1Q6N7zTPPYqXES1uAPnHxx+PVqq/Rpmk3Ku4UXWB8rxymeLyU2V9\nZR3ld0q4Tcepf4riD/m8rc8qf1YogQANJF4KCCCAQNsCbiCl+3vpL8vmrVRXV38xYMCAr/K2\nQBaEAAIIINBZAptoRXXKLcrflKnKFkquxd8vGqTURGb07XV3KXMjde49S/HVoWplJ6WvMkY5\nUfHVol8q45VnFC/zE2VD5UrlUmVNZSdlZ8VXktxYokgg3X/4wCCAAAIILCrQosE7lW8i1e6/\nNTK8xL3Dhw9/7fzzz/d/qhQEEEAAgeISuFGb69uvuwVZVt2blFzL05rBDZkDgxl950Ktclsw\nHO2cp4HtlPCBDT6vn6xUKt6WdOUIVfr/rz8oYYPrOfU7vuWOIgEaSLwMEEAAgXgCviXBtzH4\nFgjHn/KdrFAQQAABBBDYTARumITF/b6qlOudBv5AzleLwgbSnur/UvFVoNQyTRWDFX+A97rS\npJytuGRa7zoa11P5QPFyw/gK00CFIoHogQQEAQQQQCCzgP/jOVQ5XEkqbiRREEAAAQQQsMBH\nim9Z8y3ZLv5/wg2YeR7Isdyh6X17XH/Ft9d52MtLLVerwld9blD83SU3onZQ/q5kKt9qhLd1\nWJoJPI4iARpIvAwQQACB3ATCWxJym4upEUAAAQRKWeBX2jlfyfGHZ24k+S4t17Wn+HY3X+H5\nqeKnz/kqUWrxg4L8gd0flfCqkaf5vv9RCa8guWEVvWPMt+D5IRDNyn+VsIxUz7vKf8KKcu5G\nwcrZgX1HAAEEEEAAAQQQQKC9Ar6C4+8DXRfEjZrblPYUN2rc2DpT8dWel5XU4qs9buDspKyu\n9FIOVcJGmYddvlL8JDtfWfKtddcoMxVffRqirKy4gXW68oZCkQBXkHgZIIAAAgUiMHbs2JrG\nxsa+BbI5bAYCCCCAQG4CEzW5k4/i2+pOVbI1styA8pUfN6J85epFZXflcWVrZYryV2VfZYKy\nk/KU4obRDcpjihtjryj+HaXnFIoEaCDxMkAAAQQKRGDSpEn96uvr/WkeBQEEEECgvAT8kIdo\ncWPHt+pFixtNTljcENpK8RWkOcqXikv0/P5fGvbvH62ofKG4vKR4fa7roXyqUCICUcBINb0I\nIIAAAggggAACCCBQBAJtNXB8lShsHEV3Z0Z0gP6FAnwHaaEFfQgggAACCCCAAAIIIFDmAjSQ\nyvwFwO4jgAACCCCAAAIIIIDAQgEaSAst6EMAAQQQQAABBBBAAIEyF6CBVOYvAHYfAQQQQAAB\nBBBAAAEEFgrQQFpoQR8CCCDQpQKVlZXzlJYu3QhWjgACCCCAQJkL8BS7Mn8BsPsIIFA4AiNG\njJjY3Nzcp7a2tnA2ii1BAAEEEECgzARoIJXZAWd3EUCgcAWqqqrmJhKJuYW7hWwZAggggAAC\npS/ALXalf4zZQwQQQAABBBBAAAEEEIgpwBWkmFBMVuwCyeO0B/rF6cQ78/ckuZK622fZqyc1\n7ews4xmFAAIIIIAAAgggUIICNJBK8KCyS6kCyZNU8ydlbyVoIFVspP5/KJnK+hrxVqaR1COA\nAAIIIIAAAgiUpgANpNI8ruxVq0CylzrnKyPSgDyjumVT6lfQ8CTlWV09yrFxlFxa822h+V5I\nWSaDCMQWqKur693U1OTXLQUBBBBAAAEEukiABlIXwbPaJRVIdtcSBivrKd8q/1XjZKK60fKc\nBtZUfqVcHh2haf0o5a8WrUteoeGkcuyi9bGGfAvfyZp9Yy3b20NBIGeB0aNHb9nQ0NA/5xmZ\nAQEEEEAAAQTyJsBDGvJGyYI6TyBZo3X5Ss+9yoHKBcrzapxcpm603KaBdZV7opXp+5N7qv5I\n5edq4HyefppMta3fZzpPY9dR1EiiINA+gWQyWdHS0pJo39zMhQACCCCAAAL5EKCBlA9FltHZ\nAmdphX2UajVmdlK3rzJGOVGNpJ7qBiVxkcZPD4fa6F6s8eM1/bg2pks3+lxV+qEPLr/VNqw2\nv5d/EUAAAQQQQAABBIpNgAZSsR0xttcCvlqznRoz4VPm/DqerPiWUX+PKMeS1LJaH9rw5xxn\n1ORJP+zBt9eFZXn1XBgO0EUAAQQQQAABBBAoLgEaSMV1vNja+QLT1NH3j5J3Kq+rv0k5e/6o\nCj8sIddytGb4SMn2VLtMy/Rtfanf5dNtesnNM81APQIIIIAAAggggEDhCtBAKtxjw5ZlFrha\no65VPlP8lLqBSvQqjgbjluSymvIg5S+6IvVd3LnmT5fcV93d0szj95Uf+EBBAAEEEEAAAQQQ\nKDKB1E++i2zz2dzyE2h9et3h2u8/qkETXjXSYPL7gUWuV5A21Xx+rLJ+RDaX0rodl2SZQz9C\nmzxY23hHlmkYhcBiAokEz2hYDIUKBBBAAAEEOlGABlInYrOqfAj4EdpJPdK7Yid1V1f3S6VW\n+ZXi4sZOLmXDYGJ/hymXsocmbgySaT5tl28DTPjR4RQE2hQYOnTolBkzZvQfOXJkm9MyAQII\nIIAAAgh0jAANpI5xZakdK3CmFu8zSH9vyLfFvajsrvgq0NbKFCVucQPpQzViZsadYf50ifvV\ndSgI5E1g8ODB03QF6XMaSHkjZUEIIIAAAgjkLEADKWcyZuh6gYQbQlsFV5DmqHHjq0guGV7P\nCTWAKjLct5Q4ReMcCgIIIIAAAggggAACmU4okUGgGAQSnxbDVrKNCCCAAAIIIIAAAsUjwFPs\niudYsaUIIIAAAggggEAHCyRX1h0av06/kuTGGne8cqCS8ruDySrV/W8Qf0c4TUmuG4w/NM1I\nqhAoGAEaSAVzKNgQBBBAAAEEEEAgm0Cyd7axSz4u6VvV71J+u/iykr9R3avK7xT/xIYeVJTc\nT92wrKqei4P8NKxM6Z4cjP9lSj2DCBSUAA2kgjocbAwCCJSzwKhRowYdf/zx65WzAfuOAAKZ\nBJK7aMw1mcYueb2v7lQ8qey8+LKS26rOjSL/DmGNsoFyqnKLGknujxbf/q4rTIuWefNavwo8\nTLWzFh3DEAKFJ0ADqfCOCVuEAAJlKjBz5sxes2bN6lamu89uI4BARoGkf+PvckVXZpJ+WmuO\nxT+Lkdxf0U9iJA9R1lx0AclNNOyrQ92VPy86rnXIP4zun6zQE2QTXyvu1w+sV8xTjlGi5W4N\n+EFKNdHKxx5bqY+GvR8TovX0I1CIAjSQCvGosE0IIIAAAggggMBCgWPV6x9E92WYK9T4aL0c\ns3B0tj5/X6ji7fnzVfiWuNHKW1rGEHXD0qKeo5XtlPcUN4Cipa8GGrT6jxdWJr5R/7vKFgvr\nWvvG699piq8WLSiPPbaKG2X3KHMXVNKDQIEK0EAq0APDZiGAAAIIIIAAAmqrrCiF8yISvoKU\n6Ts+kcncm/QVoSuVe9W4WUvZUf2rKLOVE5SgJF7XON0ul/AVoXTlHVX21/LcSAtKslo9myve\nvmjxMnwV6aCw8ptvll7qpZeW9/S3hXV0EShkARpIhXx02DYEEEAAAQQQKHeBcwSwcgrCRWqs\n9E6pSzfoxsrOyimRkb7NbbLihlLc4qtO/s1Bf+fIt/n5StSdynQl3bnkHaofpOlq1K34xz9W\nWatbtxZvywQPUxAodIF0L+pC32a2DwEEEEAAAQQQKAOB1gcg6LHai5XvqebXi9UuVtF6RegL\nVevpccl/KrpNzk+f83eEWr8PpE6c0npr3Z6aslL5m3Kd8rByvzJLSS3/VsVHim/vq3jiiZUH\nbrPNrA90hcq38lEQKHgBGkgFf4jYQAQQQAABBBAoUwE/mMGNknTFD1yoSTdiYZ1/m6jiOcW3\n5D2jHKmspIxTciyJZ9XA2UgzraCuHvqQuFD96yhvL76g1oc43KV63WaX7Dl5cu/+e+01XQ0k\nCgLFIUADqTiOE1uJAAJlIFBdXf3FgAEDviqDXWUXEUCgTYHk3ppkaJbJltG4UVnGe9Ruir47\nVPFjNWjOUx5Xv//GuKHjW+1iluSWwRUoNa4SX86fqfU7SD9U/yMZFuLb7DRfxfBll22Zs802\nM2dkmI5qBApOINOnEgW3oWwQAgggUOoCw4cPfy2RSNSMG9eOD3dLHYf9Q6D8BJ7XLrtxk62k\nPm0uddqXVOHb2mrVwPGVHj9Q4RxlXUUPZohdXtWU6yn+7tOv1fVyxigPqcHkhlC6MlGVvqXv\n/EGDZr2RbgLqEChUAa4gFeqRYbsQQAABBBBAoIwFEnoAQqK+jbgBkqUk6jTyHOUYxd8Vqlfm\nKqcqaiS1PiFPvW2VhOfxMjZUpimTFN8y9wslQ2m9zc4Pcui1336N72SYiGoEClKABlJBHhY2\nCgEEEEAAAQQQyIdA4nwtZU1lfWVZNbhOVC5VeihpbntLXKb63ouvOaFL24ntVf89ZVX1/0RR\nIy4sCTWCEgllbFij/tNdt8UWsyLrSRygum0WTkMfAoUnwC12hXdM2CIEEEAAAQQQQCCPAq1X\nc6bmZ4EJX0GiIFDSAlxBKunDy84hgAACCCCAAAIIIIBALgJcQcpFi2kRQACBDhQYO3ZsTWNj\nY98OXAWLRgABBBBAAIE2BGggtQHEaAQQQKCzBCZNmtSvvr5+5c5aH+tBAAEEEEAAgcUFuMVu\ncRNqEEAAAQQQQAABBBBAoEwFaCCV6YFntxFAAAEEEEAAAQQQQGBxARpIi5tQgwACCCCAAAII\nIIAAAmUqQAOpTA88u40AAggggAACCCCAAAKLC9BAWtyEGgQQQAABBBBAAAEEEChTARpIZXrg\n2W0EECg8gcrKynlKS+FtGVuEAAIIIIBA+QjwmO/yOdbsKQIIFLjAiBEjJjY3N/epra0t8C1l\n8xBAAAEEEChdARpIpXts2TMEECgygaqqqrmJRGJukW02m4sAAggggEBJCbS3gdRHCoOUjZWN\nlFWUacoU5SHldYWCAAIIIIAAAggggAACCBSVQK7fQVpeezdSaVDuV05UBio9laHKRcpryovK\n9goFAQQQQAABBBBAAAEEECgagbgNpG7ao5OUV5XVlB8rbhStqWyn7KxUKytji9MLAABAAElE\nQVQoWylPKA8qdyj9FAoCCCCAAAIIIIAAAgggUPACcW+x89WhdRQ3fhqz7NWXGuerR87vleHK\nb5WjFQoCCCCAQBaBurq63k1NTb2yTMIoBBBAAAEEEOhggbgNJH+vyMmlzNLEvuWOggACCCAQ\nQ2D06NFbNjQ09I8xKZMggAACCCCAQAcJxL3FroNWz2IRQAABBEKBZDJZ0dLSkgiH6SKAAAII\nIIBA5wvks4HkW/D8vSQKAggggAACCCCAAAIIIFCUAvloIP1Ce/6O8rYyXblHWVahIIAAAggg\ngAACCCCAAAJFJbCkDSR/mfh3ynHKcsoWyjfKzxUKAggggAACCCCAAAIIIFBUAnEbSNtor36m\npE7/A9XNVvxY7ybFPxT7L2VThYIAAggggAACCCCAAAIIFJVAaoMn08Z/phHHKq8rByrhl4hf\nUb+XMVn5q/JP5U/KnxUKAggggECOAolE+Oc1xxmZHAEEEEAAAQTyIhC3gVSntf1QOU05S3lZ\n2Vv5WhmknK34CtJYZQPFDScKAggggEAOAkOHDp0ybNiwT3KYhUkRQAABBBBAIM8CcRtI4Wof\nUo+/Z3Sh8kflOWVrxQ9mOEG5RvlAoSCAAAII5CgwePDgabW1tZ/nOBuTI4AAAggggEAeBXJt\nIHnVSeVu5fuKG0TXK08qvsJEQQABBBBAAAEEEEAAAQSKViCXBtKa2stfKX4Iw5XKYOVmZT3l\njiAPq+srTBQEEEAAAQQQQAABBBBAoOgEcmkg3a+921bxgxh8FelvynbKXOVaZaDixpMbSZcp\nFAQQQAABBBBAAAEEEECgqAQqY26tH8TghtCBkelfVP9RyrNBXbO6lyp/UXYL6ugggAACCCCA\nAAIIIIAAAkUjELeB1Kg92lj5peKGUV/Fj/32d5BSi59md19qJcMIIIAAAtkFRo0aNWjq1Km+\nbZmCAAIIIIAAAl0kEPcWu3pt3/8o+yrjlf8LuneqS0EAAQQQyIPAzJkze82aNatbHhbFIhBA\nAAEEEECgnQJxryB58X6Ut+N5vlPC4kZWtfKxMi+spIsAAggggAACCCCAAAIIFJtA3CtI3i83\njI5QLldc/Cnn7xXfUve+MkNxA2olhYIAAggggAACCCCAAAIIFJ1ALg2ki7R3fry3rxS5+Mdi\n/1d5RDlC8feRNleeVnopFAQQQAABBBBAAAEEEECgqATi3mKX0F4drByv+PHeHj5OuU45SQmL\nry5NVfwbSY+GlXQRQAABBBBAAAEEEEAAgWIQiHsFaXXtzBpK2Ojpof6eim+pi5ZPNDBe+UG0\nkn4EEEAAAQQQQAABBBBAoBgE4jaQ3PCZrvws2Cn/5tHzyv7BcNhZRT3+zaQ3wwq6CCCAAALx\nBKqrq78YMGDAV/GmZioEEEAAAQQQ6AiBuLfYed2nKzcpGyl3K+cFwysGw36S3alKg/JPhYIA\nAgggkIPA8OHDX0skEjXjxo3LYS4mRQABBBBAAIF8CuTSQBqtFc9Wfq38PLIR/n0kx4/4vkM5\nU/EVJgoCCCCAAAIIIIAAAgggUFQCuTSQvGO+cuT0V/ydJF81SiofKu8q0xQKAggggAACCCCA\nAAIIIFCUArk2kMKd9JPqHAoCCCCAAAIIIIAAAgggUDICcR/SEHeHl9aEyyvtbXjFXQ/TIYAA\nAggggAACCCCAAAJ5F8h3Q2ZnbeFjykHKXXnfWhaIAAIIlLDA2LFjaxobG/uW8C6yawgggAAC\nCBS8QL4bSA3a41HKWwW/52wgAgggUGACkyZN6ldfX79ygW0Wm4MAAggggEBZCeS7gfSO9E4r\nK0F2FgEEEEAAAQQQQAABBEpGIN/fQSoZGHYEAQQQQAABBBBAAAEEyk+ABlL5HXP2GAEEEEAA\nAQQQQAABBDII0EDKAEM1AggggAACCCCAAAIIlJ9A3AbS+qKZk0P2Lz9K9hgBBBBAAAEEEEAA\nAQSKXSDuQxr8VLqRyrnKM8p9SrYyOdtIxiGAAAIILC5QWVk5T2lZfAw1CCCAAAIIINBZAnEb\nSElt0PnKV8qFynEKjSAhUBBAAIF8CYwYMWJic3Nzn9ra2nwtkuUggAACCCCAQI4CcW+xCxd7\nuXpeUXw1iYIAAgggkEeBqqqquX379p2bx0WyKAQQQAABBBDIUSDuFaRwsb7148fKBkpC8ZUl\nCgIIIIAAAggggAACCCBQEgK5NpC8058GKQkAdgIBBBBAAAEEEEAAAQQQCAVyvcUunC+1u7wq\nVkytZBgBBBBAAAEEEEAAAQQQKCaBXK8gbamd21f5SLlN8W12dyo7K92Up5QjlHqFggACCCCQ\ng0BdXV3vpqamXjnMwqQIIIAAAgggkGeBXBpI+2nd9yh+kp2vGA1T3lM2Vi5S3ED6ufKQspny\nrUJBAAEEEIgpMHr06C0bGhr6x5ycyRBAAAEEEECgAwRyucXuCq3fT7Hro2yh1CjHKkOV/1PO\nUrZW/KOy+ygUBBBAAIEcBJLJZEVLS0sih1mYFAEEEEAAAQTyLBC3gbSa1ttPuUT5RnlZuVV5\nQ4n+HlKDhscrfsodBQEEEEAAAQQQQAABBBAoKoG4DaRG7dUnyg8ie3ez+q+NDLvXt+z5ljtP\nT0EAAQQQQAABBBBAAAEEikogbgPJv3/khzHcpJypeL465UolLDupZ5zSU3lAoSCAAAIIIIAA\nAggggAACRSWQy0MafqM9+1w5RvFDGVLLKFUMUA5WPk4d2UXDg7TebZVXlacVN/TaKtWaYG/F\nV8GeVGYoFAQQQAABBBBAAAEEECgDgbhXkEzhp9edr2zkgTTlcNW5cfFImnGdXeWrWG4U/UNx\nY8dP1rtd8ZP2spXfa+Q7yoHKZcoryjoKBQEEEOgwAT2cIaEcMHDgwI2WUVH/KYqfFkpBAAEE\nEEAAgU4WiNtA8pWYHwXb9nWGbZys+tRx/s7S8AzTd2T1uVq4G0kbKEOVrZW9lCOUTMXTnKHs\nqQxR1lM+UK5WKAgggECHCKgh1F0L9oc4N++xxx5zDjnkkK/Uf4ryusb57xAFAQQQQAABBDpR\nIG4DybfMHa+MVw5U2vohw501zaOK/9OfpnRm8SNyT1JuUGYFK56s7v3KMcFwus4JqvQVo6eC\nkc3qXqrsqvQP6ugggAAC+RY4VwvcRPn+6quvPmbIkCFvqn9dxVfB71AjKe7faU1OQQABBBBA\nAIElFYj7HaSPtCLfqraLcrEyRnlGaVB8lcWP/vZ/6P4NJMcNKD8S3D8m26R0ZlldK1tGeSFl\npR7eJ6UuOjhAAxOjFer3PAnFV6KmKrmUlTRxXN/lunfvXrHbbrutX1VV9XXqSnbZZZeZ66+/\n/nep9U8++WTPN998s3dqvYf79+//9Z577ulPohcp06dPT9x5550rL1IZDCy11FLJ4447zt8z\nW6yMGTOmas6cOWn3pwy2z6+B5Z955pk++C18afD6W2ixJO+PDz/88Bjl0quuumqZ2traVX2L\n3dlnn933xBNPPGullVZ6tampaXe99l7y2nj9LTTn9bfQoj2vv4kTJy6/wQYbVNTX19ccdthh\nXy5cGv9/RC3K4P+3BbvbwX9feurDnh7+f9Qr5P27gL2iPe/fQvR79913ux1zzDEV33zjJkHx\nl7QnvFl26wmN21Jxw2ewsrGyn+LGQKPyljJSuUNxw6krSv9gpdNTVv6Fht2YWE6ZnTLOgzXK\n4+6JlBlBvxtduZSBmtjfZYpdNtxww4qHHnpoUroZdIJUsfHGpl603HzzzRVvv/32opXB0LLL\nLluxzz6LtwcfffTRiltvvTXtPK4cNGhQxdZb+27DheWDDz6ouP766xdWpPSVw/YlEombKisr\nK/BbePB5/c23WNL3R/B+vEBLuyB8b+r9W+f3b0NDg1fysF97Lrz+Whla/+H1N9+iva+/a6+9\nNvz/47aFqvP7+P9joUg5/P8W7m1H/33R/6MV+iC29a4i3r/z1dv7/i1EP32QX3HKKadUXHTR\nReFLqqi7uTaQvLNJ5a4gHnbxLSBxnhDXOnEH/7NKsPzUK1fh1ZRlNT5dA2lV1YfThJvoqzne\nX8+TS3lXE7uR1D3mTMPq6urO23///Q/o0aPHYk3vwYMHf9rS0jIndVmHHnroilOmTFkxtd7D\nffv2bdI8n6WO22677brPmDFjjdR6D+sqVsumm25ar/kWGV1dXV1x5JFHrqkrSN0WGREMlPr2\n6Q/6szL5nXb3MfwWvgJ4/c23WJL3hz5xW3HEiBG364OO6+6///4nt99++wOXX375rV555ZXh\nunr0rZY9YebMmUeoofSy18brj9dfvv4+H3HEEX0GDBgwXv+HnKr4w80Fhf8/FlBUlPr/bwv3\ntGP/vqhxdLbWtZKuIvn7lRX8/zFffkn+/yi087/PPvusmz548a3hlAIV2Ebb5UZN9EdtvalH\nKd8qme7nf1/jLlSiZQUNeFn7Rys7oP/oYD1pb5frgPWxyBwEdCvK9Oeff/6AHGZhUgRiC+iE\n4XLlPWV1vc7O0uvtWfUvrfxdecv9sRfGhAjEFHj44Yd76LWW1GvO/2dSEOhQAb3O/qz4w3VK\n6Qr4ooDPmbcthV1szxWkQt/vj4IN9BWhaPF9r24ELXp5ZOEUH6u39d7YhVUV4TLqI3X0IoAA\nAvkU+I0WNkiZPHbs2JkTJkzoq/v0/SncaspQffI6T10KAggggAACCHSSQKarKZ20+g5ZjRtI\n9cqeKUvfQ8OTU+qig//WwO6Kv5AfFi+jWXkvrKCLAAII5FNADaCvtLydlDP1fYfes2fP7qb+\n+5SNNe4VdSkIIIAAAggg0IkCpdhA8hWiyxTfUudGUU/lRGUr5SwlLH7QxF8UP/HO5U9KX+X3\nim91C6c/T/2LPOFHwxQECknAl7P/N5JT1X+QspGSWsL3Qmp9puEfacRPMo2kPj8CagjNVa7X\nPeX/+VpF/WcrrV9mzs8aWAoCCCCAAAIIxBXI1y12fjKcv6/zYdwVd/B0V2v5A5QHFN+/P0U5\nVnlDCYsf1ebv/vhk0leJ3lf8PZOblDOUGcrdysUKBYFCFthNG3eu8oni+399H7CfLOkPQK5T\nTlDC27TOV78fMeNH2Mcph2qifsrtcSZmGgQQQAABBBBAoNgFfAKVSzlEE9+mXKhUK7768g9l\nuuLHer+upD4cQVWdXvybQSMUN9xqlA2VvyrRcpoGfDvd7Ejl/epfVVlb8f3/blQt9vtDqqMg\nUIgCbsj4fenXcA/lZMWv4b2VsGyjnhvCAboIIIAAAggggAACiwrk0kA6S7P+XRmknKTcpfxR\n2VQ5Rzle8afUvmqzrFIIJbwylMu2+BP4qQoNo1zUmLbQBPz6vUqZo/hqaVhq1FMVDgTdndX9\npeIPQL4X1NFBAAEEEEAAAQTKUiBuA8m3qf02yDrq+lNq31LnhtJeykjlGsUnWv70el+FggAC\nXSuwpVbfS3kmshm+VW5YMOxxTylPKP7Onr+T59tRf6JQEEAAAQQQQACBshSI20BaQzo+mbpB\n8RUW35Z2r+Lv9ExWwvKFenyyNSCsoIsAAp0mMEZrukXxld7HlAnKr5WHlHTF30XaWNlR2URZ\nS/FtpjcG/erkXLppDn9vb6bih5tcqfhWXEoMAf1o4Bf68c6vYkzKJAgggAACCCDQQQJxG0h+\nmlKLsktkO9y/rhK9JcdXmjZQCuVhDdoUCgJlI+AHM6wYZGV15yp7Kr7qm674lrprFTekXPxg\nkksVfxgSXmVSb07FV5N/qfgKs78DeLTiRhIlhsDw4cNfO//8832LLwUBBBBAAAEEukggbgPJ\n3+UZo/xVuUfxbTirKP5k+jZlH2WQcqfi7zc8olAQQKBzBfbV6nzLqxtFmyv+AMPvU79vU4sb\nUB4XfbKjp3lF+VQZ6IF2lGM0T/fIfD3U/zMl7t+ayKz0IoAAAggggAACnS9QmcMqT9C0flqd\nT74mK+cqnynPKb4tx+Vz5TBlmgcoCCDQpQKfaO13KL9TfHXpCyUs/tDDJfX2N99C64eteN72\nlHQNIdcl2rMw5kEAAQQQQAABBDpbIN3JTKZt8AnVGcomygHKfxV/0txf8afVuyoDlIcVCgII\nFIbAetoMf6dlVsrmuK5BGZxS70fc+7bZ/6TUxx28VRN+E5nY/b6yHP4OU2QUvQgggAACCCCA\nQOEJ5HIFKdvWv6eR/v7Rl9kmYhwCCHSowE+09LAh4itDOyv+ntElkXr1Lii/V9/Vij/ouErx\nBx3nKr7tboLSnjJCM/kWu58GM49V97ignw4CCCCAAAIIIFDwArk2kLbUHvl7Dh8ptykJxZ8O\n+0Ssm/KUcoRSr1AQQKBzBW6OrG6m+t9XTlMuj9RHe6/XgH+z7BzldMVXid0w8neGUq84qSpW\n+VpT/Vw5WvHfBz8oghJTYOzYsTWNjY19Y07OZAgggAACCCDQAQK5NJD20/r9gAbfmrO8Mkzx\nlSM/JvgixQ0knxg9pGymfKtQEECg4wXO0yqcOMVPuQuLv290qeIGVD/lYyV6e5wGF1wJcn8u\n5btcJmba+QKTJk3qV19f7wdoUBBAAAEEEECgiwSWymG9V2han0j1UbZQapRjlaHK/ylnKVsr\n6yt+qh0FAQSKQ6BFmzlVSW0cFcfWs5UIIIAAAggggEAeBeI2kFbTOv0Js7/L4JOol5VbFX9X\nYbISlgb1jFc2CCvoIoAAAggggAACCCCAAALFIhC3gdSoHfpE+UFkx25W/7WRYff6lj3fcufp\nKQgggAACCCCAAAIIIIBAUQnEbSD5Fhw/jOEm5UzF89UpVyph2Uk945SeygMKBQEEEEAAAQQQ\nQAABBBAoKoG4DSTv1G+Uq5VjFDeYUssoVfgK08GKv+xNQQABBBBAAAEEEEAAAQSKSiCXBpKf\nXne+slGGPTxc9dXKIxnGU40AAgggkEWgsrJynpLuA6gsczEKAQQQQAABBPIpkMtjvsP1fq0e\n/75JMqwIuuHDGvwI8DkKj/lNAWIQAQQQyCYwYsSIic3NzX1qa2uzTcY4BBBAAAEEEOhAgVyu\nIPXWdvihDDOUz5W/Kasq0eIGl39gcv9oJf0IIIAAAm0LVFVVze3bty8/rts2FVMggAACCCDQ\nYQK5NJAu01b8TPGPxTr+4djXFD+1joIAAggggAACCCCAAAIIFL1A3AZSN+3pz5WTlKOUo5Ua\nxU+y+5fSX6EggAACCCCAAAIIIIAAAkUtELeB5Icv+Pa5ByN7+4X6hyp+Yt3DyooKBQEEEEAA\nAQQQQAABBBAoWoG4D2n4VHvohzLsotwW2dsm9e+lPKvcp+yjUBBAoPMFNtAq/V7MVPx0ST9I\n5UTlhSDqZC39NPZA5XrF3y2kdLBAXV1d76ampl4dvBoWjwACCCCAAAJZBOI2kJq1jHuVi5W1\nFf8ekq8guXyiDFGeVp5UKAgg0PkCm2mVfn82Kum+5N+gejeQ/Kj+ixQ3ktoq62oCL9PvfRpI\nbWnlYfzo0aO3bGho4JblPFiyCAQQQAABBNorELeB5OUPV25WfIL1uPKcEpb31ONG0t/DCroI\nINAlAjtqrW9mWfM2Gjc9y/joKF8Z3lD5IFpJf8cJJJPJipaWlkTHrYElI4AAAggggEBbArk0\nkPzJ9J7KasqXaRb8huq2UA5SXk8znioEEOh6gRptgn+j7PNgU5ZVd2/le4o/6HhKmam49FTW\nVnz1Kd1VKVVTEEAAAQQQQACB0hKI+5CG6F5P04B/LLa74pOqZZSwzFOPv6OU7RPscFq6CCDQ\n+QK3a5XDgtWuqe4U5QrlR8pNim/D20hx8W17DyireyCHsrym9ZWn6N+GHGZnUgQQQAABBBBA\noOsEcrmC5K3cQTlZ2UlZWXHxwxs+VeqVPyu3KhQEEOgagTO02vD7geEWPKGe6BMow/qjgh43\nlL5VfMXIDabDlF8r7Smna6YLFP80gB/i8gvlToWCAAIIIIAAAggUhUAuDaRDtUd/U55X/KOx\nnym+FccnVSspWyrXKQcoP1YoCCDQ+QJ+H/oKb7RMjQ5E+v3+XUXx75rdrfjqcD+lvWWIZrxI\nCb9D49v3/IHJi0qmbdAoCgIIIIAAAgggUDgCuTSQ3Cg6U/FTrTIVP/XqBcW36PhWHQoCCHSu\nwIFaXdxbXP+iabdXrlKuVF5R7lL8Xv9GybX4u0z+fpOvHoXFt90OVfzhCSWGQCIRti9jTMwk\nCCCAAAIIIJB3gbjfQeqrNfdR/Hso2crbGjlB2TPbRIxDAIGCEPhKW+ErvgOUE5WPFd8ed4fS\nnuJHgbekzOi/MTwiPAUl0+DQoUOnDBs2zD+dQEEAAQQQQACBLhKI20Dyf9j1yg/b2M4VNN5f\n7P6ojekYjQACXS9wlDbhN4pvf7ta8Q89/0nZXYn7t0GTLiij1ecrSHODGl+F8m179wfDdNoQ\nGDx48LTa2trwCYNtTM1oBBBAAAEEEOgIgVxusbtRG3C74u8hPaj4xMdfBu+phN9BOkb9TYrH\nUxBAoLAFGrV5vvWtXnlA8ZWknZWJSuqVIFW1Weo1xXbK75X1FX9f0bflzlEoCCCAAAIIIIBA\nUQjk0kDyrTdvKJcrw9PsnU+CxigjldkKBQEEClvgH9q8S5RzlFsUN4omKIcp7S3/1Yz+LhIF\nAQQQQAABBBAoSoFcGkjewXuD+HdO+it+PLCvGPm7Cx8oqU/PUhUFAQQ6QeDvWofTVlkxZYLT\nNeysocxQ/L2ksDymHp4YEGrQRQABBBBAAIGyEMi1gRSifKmeV4OEdXQRQKB4BT4s3k1nyxFA\nAAEEEEAAgfwJtLeBlGkLltaI3opvt/OXtSkIIIAAAjEFRo0aNWjq1KnrxZycyRBAAAEEEECg\nAwTa86SqbJvhL3jPUvbPNhHjEEAAAQQWF5g5c2avWbNmRX9HavGJqEEAAQQQQACBDhXIdwOp\nQVs7SnmrQ7eahSOAAAIIIIAAAggggAACHSCwJLfYddf2rKL4Ud/Nwba9o+5pQT8dBBBAAAEE\nEEAAAQQQQKCoBHK9grSD9u5uZbriH4H0D8L6+0Z+it2zypI8HlizUxBAAAEEEEAAAQQQQACB\nrhPI5QrSodpM/0isf/zxMuUzZaYS/aFY/+jkAcqPFQoCCCCAQFqBpB5ok5iXdhSVCCCAAAII\nINClArk0kNwoOlO5OMsWr6txLygbKZOzTMcoBBBAoEwFkr5yf19FRfInaiT5CjwFAQQQQAAB\nBApIIO4tdn21zX2U69vY9rc1foKyZxvTMRoBBBAoV4FfaMf3UfyB0yKlurr6iwEDBkR/rHeR\n8QwggAACCCCAQMcLxG0gfaJNqVd+2MYmraDxmyn+bhIFAQQQQGARgaT/Rl4QVOmBNsl+0dHD\nhw9/7fzzz58araMfAQQQQAABBDpXIJdb7G7Upt2u+HtIDyrTFD/BLvodpGM03KR4PAUBBBBA\nYFGBszXoq/Euyyi+ZfkgD1AQQAABBBBAoDAEcmkg+VPPN5TLleFpNn+O6sYoI5XZCgUBBBBA\nYIFA0t/R/OWCwfk9B+oq0mB9F8m3JlMQQAABBBBAoAAEcmkgeXPvDbK8uv2VNRVfMfpY+UD5\nWqEggAACCCwucKmqui1eXXGFGklbqJHUkmYcVQgggAACCCDQyQK5NpDCzftSPa8GCevoIoAA\nAgikFUjuruq90o6qqPiB6v3ghrYegpNhdqoRQAABBBBAIJ8C7W0g5XMbWBYCCCBQwgJJ/531\nzyRkKxfqKtKdY8eeVdPY2OinhlIQQAABBBBAoIsEaCB1ETyrRQCBshHwg2zSfW8zFaD7pEmT\n+tXX16+cOoJhBBBAAAEEEOg8ARpInWfNmhBAoCwFEn5ozVPxdn1IvMmYCgEEEEAAAQQ6TCDu\n7yB12AawYAQQQAABBBBAAAEEEECgUATa20DqrR3okWYnllbdsoq7FAQQQAABBBBAAAEEEECg\nqATa20Bq1F7ekGZPd1adbyf5cZpxVCGAAAIIIIAAAggggAACBS3Q3u8g/Ul79d80e/a+6vxb\nH2+nGUcVAggggAACCCCAAAIIIFDQAu1tIJ2ZYa/cMDo1wziqEUAAAQSyCFRWVs5T+MHYLEaM\nQgABBBBAoKMF2ttASmjDkhk2bnnVz1G+yzCeagQQQKBMBJLHaUcfr6hIvLP4DifXU932SpPy\noKb5asSIERObm5v71NbWLj45NQgggAACCCDQKQK5fAfJD2a4VpmhfK78TVlViRY3uGYp+0cr\n6UcAAQTKTyB5kvb5GmXdxfc9OUJ1ryvHK39QPtNnTgdXVVXN7du371wNUxBAAAEEEECgiwRy\naSD5l+B/ptwTZD91X1M2VigIIIAAAq0CyV5q7Fyi3svTgyQ3VL2/q6nbkRNbqLu2Mlq54Ntv\nE746T0EAAQQQQACBLhSIe4tdN23jzxXfLnJjsL1nqKvbQir+pWyrTFUoCCCAQAkLJLtr5wYr\nvj3uW0UPq0lMVDdantPAmsqvlHSNpP9VveZJ+GE3Kol5alBdoJ7J06b16LvWWt+oN7m7/vmP\n4iv3uyjTFd+qN1vjvO6dlJc1/KK6FAQQQAABBBDIo0DcK0jVWqcbU24QheUL9QxVPlYeVlZU\nKAgggECJCiRrtGOTlHuVAxU3ap5Xg8VX16PlNg34tjpfbU9XtlGlGjZJNX7cEEoeomH9dlzi\nmjXXbP46mOFOdX3r3avKLxWv8zFN6w+q/ATR4cozGs60Do2mIIAAAggggEB7BOI2kD7Vwv1Q\nBn+SGS1NGthLWUa5T+mpUBBAAIFSFDhLO9VH0QdGiZ3U7auMUU7Un8fI377ERRrvKz6Zij9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NxqI1a9b0yi7N9H78omODVSy9rKOvJn8+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\nECBAgACB6RP4/wGpDH+M84kZkwAAAABJRU5ErkJggg==",
      "text/plain": [
       "Plot with title “Representación simultanea de carreras y edades”"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 420,
       "width": 420
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot(acs,cframe=1.1,\n",
    "     main=\"Representación simultanea de carreras y edades\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Coordenadas y ayudas para la representación de las edades"
     ]
    },
    {
     "data": {
      "text/html": [
       "<table class=\"dataframe\">\n",
       "<caption>A data.frame: 4 × 7</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>Comp1</th><th scope=col>Comp2</th><th scope=col>Ca.Axis1</th><th scope=col>Ca.Axis2</th><th scope=col>cos2.Axis1</th><th scope=col>cos2.Axis2</th><th scope=col>conInercia</th></tr>\n",
       "\t<tr><th></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></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>a16m</th><td>-0.01</td><td>-0.07</td><td> 0.05</td><td> 5.36</td><td> -0.20</td><td>-13.42</td><td>12.61</td></tr>\n",
       "\t<tr><th scope=row>a17</th><td>-0.19</td><td> 0.11</td><td>34.27</td><td>19.56</td><td>-70.78</td><td> 24.34</td><td>25.38</td></tr>\n",
       "\t<tr><th scope=row>a18</th><td>-0.02</td><td>-0.36</td><td> 0.08</td><td>66.94</td><td> -0.16</td><td>-86.48</td><td>24.44</td></tr>\n",
       "\t<tr><th scope=row>a19M</th><td> 0.34</td><td> 0.09</td><td>65.61</td><td> 8.15</td><td> 91.55</td><td>  6.85</td><td>37.57</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 4 × 7\n",
       "\\begin{tabular}{r|lllllll}\n",
       "  & Comp1 & Comp2 & Ca.Axis1 & Ca.Axis2 & cos2.Axis1 & cos2.Axis2 & conInercia\\\\\n",
       "  & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
       "\\hline\n",
       "\ta16m & -0.01 & -0.07 &  0.05 &  5.36 &  -0.20 & -13.42 & 12.61\\\\\n",
       "\ta17 & -0.19 &  0.11 & 34.27 & 19.56 & -70.78 &  24.34 & 25.38\\\\\n",
       "\ta18 & -0.02 & -0.36 &  0.08 & 66.94 &  -0.16 & -86.48 & 24.44\\\\\n",
       "\ta19M &  0.34 &  0.09 & 65.61 &  8.15 &  91.55 &   6.85 & 37.57\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 4 × 7\n",
       "\n",
       "| <!--/--> | Comp1 &lt;dbl&gt; | Comp2 &lt;dbl&gt; | Ca.Axis1 &lt;dbl&gt; | Ca.Axis2 &lt;dbl&gt; | cos2.Axis1 &lt;dbl&gt; | cos2.Axis2 &lt;dbl&gt; | conInercia &lt;dbl&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| a16m | -0.01 | -0.07 |  0.05 |  5.36 |  -0.20 | -13.42 | 12.61 |\n",
       "| a17 | -0.19 |  0.11 | 34.27 | 19.56 | -70.78 |  24.34 | 25.38 |\n",
       "| a18 | -0.02 | -0.36 |  0.08 | 66.94 |  -0.16 | -86.48 | 24.44 |\n",
       "| a19M |  0.34 |  0.09 | 65.61 |  8.15 |  91.55 |   6.85 | 37.57 |\n",
       "\n"
      ],
      "text/plain": [
       "     Comp1 Comp2 Ca.Axis1 Ca.Axis2 cos2.Axis1 cos2.Axis2 conInercia\n",
       "a16m -0.01 -0.07  0.05     5.36     -0.20     -13.42     12.61     \n",
       "a17  -0.19  0.11 34.27    19.56    -70.78      24.34     25.38     \n",
       "a18  -0.02 -0.36  0.08    66.94     -0.16     -86.48     24.44     \n",
       "a19M  0.34  0.09 65.61     8.15     91.55       6.85     37.57     "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Promedio de contribución para las edades 25%"
     ]
    }
   ],
   "source": [
    "# edades\n",
    "cat(\"\\n\\nCoordenadas y ayudas para la representación de las edades\")\n",
    "round(cbind(acs$co,Ca=ayuacs$col.abs,cos2=ayuacs$col.rel,conInercia=ayuacs$col.contrib),2)\n",
    "cat(\"\\nPromedio de contribución para las edades 25%\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Las contribuciones absolutas *Ca* suman 100% en cada eje, vale la pena poner atención en las categorías que son superiors al promedio 100/4 = 25%: en el primer eje *a17* y *a19M*, en el segundo eje *a18*.\n",
    "\n",
    "Los cosenos cuadrados son indicadores de la calidad de la proyección, la suma por ejes es 100%, los siempre positivos, pero la salida de *inertia.dudi{ade4}* les agrega el signo de la coordenada. Los cosenos cuadrados en el primer plano son la suma de los cosenos cuadrados sobre los ejes 1 y 2. Solo *a16m* n tiene buena calidad de representación en el primer plano.\n",
    "\n",
    "La última columna es la contribución a la inercia en el espacio total, $\\Re^3$ en este ejemplo."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xNlyAmgie1FC"
   },
   "source": [
    "# **Filas y columnas suplementarias**\n",
    "\n",
    "- Se proyectan e interpretan utilizando las fórmulas de transición.\n",
    "- Su interpretación debe hacerse después de la de los elementos activos.\n",
    "- AYUDAS\n",
    "    -  Distancia al origen\n",
    "    -  Coseno cuadrado\n",
    "    -  Valor test\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[Volver al inicio](#Contenido)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "FIN"
   ]
  }
 ],
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