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# Referencias {-} |
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--- | ||
title: "Fundamentos de Estadística con Remuestreo" | ||
author: "Teresa Ortiz, Felipe González, Alfredo Garbuno" | ||
site: bookdown::bookdown_site | ||
documentclass: book | ||
bibliography: | ||
- bibs/book.bib | ||
- bibs/packages.bib | ||
biblio-style: apalike | ||
link-citations: yes | ||
github-repo: "tereom/fundamentos-2024" | ||
description: Curso de Fundamentos de Estadística con Remuestreo, maestría en Ciencia | ||
de Datos, ITAM, Otoño 2024. | ||
url: "https://tereom.github.io/fundamentos-2024" | ||
--- | ||
|
||
# Información del curso {.unnumbered} | ||
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||
Notas del curso *Fundamentos de Estadística con Remuestreo*, este curso busca explicar los principios básicos de la estadística y su papel en el análisis de datos. Nuestro punto de vista es uno de fundamentos, con menos énfasis en recetas o técnicas particulares. | ||
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||
#### Ligas {.unnumbered} | ||
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||
- Notas: <https://tereom.github.io/fundamentos-2024/>\ | ||
- Repositorio con material: <https://github.com/tereom/fundamentos-2024>\ | ||
- Correo: [teresa.ortiz.mancera\@gmail.com](mailto:[email protected])\ | ||
- Zoom clase (miércoles 4:00-7:00 pm): <https://itam.zoom.us/j/92745909276>\ | ||
- Zoom sesiones de dudas (viernes 3:00-3:45 pm): <https://itam.zoom.us/j/92518922348>\ | ||
- Canvas: <https://itam.instructure.com/courses/13328>\ | ||
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</br> | ||
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||
<a rel="license" href="http://creativecommons.org/licenses/by/4.0/"><img src="https://i.creativecommons.org/l/by/4.0/88x31.png" alt="Licencia Creative Commons" style="border-width:0"/></a><br />Este trabajo está bajo una <a rel="license" href="http://creativecommons.org/licenses/by/4.0/">Licencia Creative Commons Atribución 4.0 Internacional</a>. | ||
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# Temario {-} | ||
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## Plan semanal {-} | ||
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#### Datos y análisis exploratorio {.unnumbered} | ||
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||
Referencias: [@cleveland94], [@Chihara] | ||
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1. Visualización[^index-1] | ||
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2. Análisis exploratorio | ||
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3. Tipos de datos o estudios | ||
- Muestras diseñadas y muestras naturales | ||
- Experimentos y datos observacionales | ||
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[^index-1]: Material disponible en apéndice. | ||
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#### Introducción a Pruebas de Hipótesis {.unnumbered} | ||
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Referencias: [@Chihara] | ||
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4. Introducción a pruebas de hipótesis. Pruebas de permutaciones | ||
5. Muestras pareadas y otros ejemplos | ||
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#### Estimación y distribución de muestreo {.unnumbered} | ||
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||
Referencias: [@Chihara], [@Hesterberg] | ||
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6. Estimadores y su distribución de muestreo | ||
7. Repaso de probabilidad y Teorema del límite central | ||
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#### Introducción a estimación por intervalos {.unnumbered} | ||
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||
Referencias: [@Chihara], [@Efron], [@Hesterberg] | ||
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8. El método plugin y el boostrap | ||
9. Bootstrap e Intervalos de confianza. Ejemplos. | ||
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#### Estimación {.unnumbered} | ||
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||
Referencias: [@Chihara], [@Wasserman] | ||
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10. Estimación por máxima verosimilitud | ||
11. Ejemplos de estimación por máxima verosimilitud y Bootstrap paramétrico | ||
12. Propiedades de estimadores de máxima verosimilitud | ||
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||
#### Más de pruebas de hipótesis {.unnumbered} | ||
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||
Referencias: [@Chihara], [@Wasserman] | ||
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||
13. Pruebas de hipótesis para medias y proporciones: una y dos poblaciones. | ||
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||
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||
#### Introducción a inferencia bayesiana {.unnumbered} | ||
|
||
Referencias: [@Kruschke] | ||
|
||
14. Introducción a inferencia bayesiana | ||
15. Ejemplos de distribuciones conjugadas | ||
16. Introducción a métodos computacionales básicos: Muestreadores Metrópolis y Gibbs | ||
17. | ||
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||
|
||
## Evaluación {-} | ||
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||
Se evaluará mediante tareas semanales y dos exámenes: | ||
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* Tareas semanales (20%) | ||
* Examen parcial en clase y a casa (40%) | ||
* Examen final a casa (40%) | ||
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||
|
||
## Referencias | ||
|
||
<div id="refs"></div> |
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/* Styles for section anchors */ | ||
a.anchor-section::before {content: '#';font-size: 80%;} |
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/* Styles for section anchors */ | ||
a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;} | ||
.hasAnchor:hover a.anchor-section {visibility: visible;} | ||
ul > li > .anchor-section {display: none;} |
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document.addEventListener('DOMContentLoaded', function () { | ||
// If section divs is used, we need to put the anchor in the child header | ||
const headers = document.querySelectorAll("div.hasAnchor.section[class*='level'] > :first-child") | ||
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headers.forEach(function (x) { | ||
// Add to the header node | ||
if (!x.classList.contains('hasAnchor')) x.classList.add('hasAnchor') | ||
// Remove from the section or div created by Pandoc | ||
x.parentElement.classList.remove('hasAnchor') | ||
}) | ||
}) |
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.book .book-header h1 { | ||
padding-left: 20px; | ||
padding-right: 20px; | ||
} | ||
.book .book-header.fixed { | ||
position: fixed; | ||
right: 0; | ||
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left: 0; | ||
border-bottom: 1px solid rgba(0,0,0,.07); | ||
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span.search-highlight { | ||
background-color: #ffff88; | ||
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@media (min-width: 600px) { | ||
.book.with-summary .book-header.fixed { | ||
left: 300px; | ||
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@media (max-width: 1240px) { | ||
.book .book-body.fixed { | ||
top: 50px; | ||
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.book .book-body.fixed .body-inner { | ||
top: auto; | ||
} | ||
} | ||
@media (max-width: 600px) { | ||
.book.with-summary .book-header.fixed { | ||
left: calc(100% - 60px); | ||
min-width: 300px; | ||
} | ||
.book.with-summary .book-body { | ||
transform: none; | ||
left: calc(100% - 60px); | ||
min-width: 300px; | ||
} | ||
.book .book-body.fixed { | ||
top: 0; | ||
} | ||
} | ||
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.book .book-body.fixed .body-inner { | ||
top: 50px; | ||
} | ||
.book .book-body .page-wrapper .page-inner section.normal sub, .book .book-body .page-wrapper .page-inner section.normal sup { | ||
font-size: 85%; | ||
} | ||
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||
@media print { | ||
.book .book-summary, .book .book-body .book-header, .fa { | ||
display: none !important; | ||
} | ||
.book .book-body.fixed { | ||
left: 0px; | ||
} | ||
.book .book-body,.book .book-body .body-inner, .book.with-summary { | ||
overflow: visible !important; | ||
} | ||
} | ||
.kable_wrapper { | ||
border-spacing: 20px 0; | ||
border-collapse: separate; | ||
border: none; | ||
margin: auto; | ||
} | ||
.kable_wrapper > tbody > tr > td { | ||
vertical-align: top; | ||
} | ||
.book .book-body .page-wrapper .page-inner section.normal table tr.header { | ||
border-top-width: 2px; | ||
} | ||
.book .book-body .page-wrapper .page-inner section.normal table tr:last-child td { | ||
border-bottom-width: 2px; | ||
} | ||
.book .book-body .page-wrapper .page-inner section.normal table td, .book .book-body .page-wrapper .page-inner section.normal table th { | ||
border-left: none; | ||
border-right: none; | ||
} | ||
.book .book-body .page-wrapper .page-inner section.normal table.kable_wrapper > tbody > tr, .book .book-body .page-wrapper .page-inner section.normal table.kable_wrapper > tbody > tr > td { | ||
border-top: none; | ||
} | ||
.book .book-body .page-wrapper .page-inner section.normal table.kable_wrapper > tbody > tr:last-child > td { | ||
border-bottom: none; | ||
} | ||
|
||
div.theorem, div.lemma, div.corollary, div.proposition, div.conjecture { | ||
font-style: italic; | ||
} | ||
span.theorem, span.lemma, span.corollary, span.proposition, span.conjecture { | ||
font-style: normal; | ||
} | ||
div.proof>*:last-child:after { | ||
content: "\25a2"; | ||
float: right; | ||
} | ||
.header-section-number { | ||
padding-right: .5em; | ||
} | ||
#header .multi-author { | ||
margin: 0.5em 0 -0.5em 0; | ||
} | ||
#header .date { | ||
margin-top: 1.5em; | ||
} |
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div.sourceCode { | ||
position: relative; | ||
} | ||
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.copy-to-clipboard-button { | ||
position: absolute; | ||
right: 0; | ||
top: 0; | ||
visibility: hidden; | ||
} | ||
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.copy-to-clipboard-button:focus { | ||
outline: 0; | ||
} | ||
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div.sourceCode:hover > .copy-to-clipboard-button { | ||
visibility: visible; | ||
} |
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