Разница между страницами «Математические модели политэкономии» и «Linguistic Data: Quantitative Analysis and Visualisation: computational linguistics»

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'''Дорогие третьекурсники!'''
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* Instructors: Ilya Schurov and Olga Lyashevskaya
  
На этой странице будут появляться различные материалы и объявления, связанные с курсом '''«Математические модели политэкономии»''', читаемого для студентов 3-го курса ОП Политологии в '''2019/2020''' учебном году.
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== Materials ==
Для специализациии «Политический анализ» настоящая дисциплина является обязательной.
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{| class="wikitable"
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|-
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! Data !! Topics !! Links
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|-
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| Jan 18 || Introduction. Quantitative linguistic research and data types. R basics || [https://docs.google.com/presentation/d/1VUIUa3Db5n4dsD_HeA3e-mz55zK8uPrko3yu207pKUk/edit?usp=sharing Intro Slides] [https://github.com/LingData2019/LingData/tree/master/seminars/2019-01-12 Lab 01: intro to R]
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|-
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| Jan 25 ||  ||
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|}
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== Software ==
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During this course we will use R as a programming language and RStudio as a GUI.
  
* Авторы курса: К.И. Сонин, Д.А. Дагаев, Л.Н. Сысоева
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How to install R and RStudio?
* Лекции читает: Сысоева Любовь Николаевна (lsysoeva@hse.ru)
 
* Семинары ведет: Сысоева Любовь Николаевна
 
* Ассистент: Паршина Анастасия (a.a.parshina@ya.ru)
 
  
== Материалы ==
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1. Download [https://cran.r-project.org/ R] (you can choose another mirror here if you wish) and install it on your computer. Make sure you did it before installing RStudio.
  
=== Электронная ведомость ===
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2. Download [https://rstudio.com/products/rstudio/ RStudio] (you need RStudio Desktop Open Source License) and install it on your computer. It is recommended to create a shortcut for RStudio during installation.
https://docs.google.com/spreadsheets/d/1WgYfzY7tYBf5enav7-_DwMEQU5N5MhwC2fVtdZymcuk/edit?usp=sharing
 
  
=== Лекции ===
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It is possible avoid installing anything on your PC, using [https://rstudio.cloud rstudio.cloud] (an online version of RStudio).
{|class='wikitable'
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!дата лекции
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For successful submission of assignments you should be able to create and save R code files (.R) and RMarkdown files (.Rmd).
!тема лекции
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!литература
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|-
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== Homeworks ==
|17.01
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* Homework 1 (deadline: January 25, 12:00), Chapters 1, 2, 3, and 5 of the [https://www.datacamp.com/courses/free-introduction-to-r DataCamp] course "Introduction to R". Please fill in this [https://docs.google.com/forms/d/e/1FAIpQLSdjgKBM5JSo6D6ajhrWWfFG1ktcKgDfbdK_jQ_ZbW9GwNLzpQ/viewform form]. 
|[https://docviewer.yandex.ru/view/0/?*=513gH0X4nkqZPwLUPPZhvGFnAdt7InVybCI6InlhLWRpc2stcHVibGljOi8vZUNPZGxuNUlGR1U1Nlc3czcrbzFaUmtNbzU5Y1NSZlVTMFNBZFJ1U2J4NGI4S3l5bjhiNEFBUlo5M0JKQ1Iza3EvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiTGVjdHVyZV8xLnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMCIsInRzIjoxNTc5MzQ3MjE3MjQ0LCJ5dSI6IjQxMjgwODk0MTE1NzkzNDcwNTMifQ%3D%3D Стратегическое финансирование избирательных компаний]
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* Homework 2 (deadline: February 1, 12:00), Chapters 4 and 6 of the [https://www.datacamp.com/courses/free-introduction-to-r DataCamp] course "Introduction to R". 
|S. Gehlbach. Formal Models of Domestic Politics. Paragraph 3.1.
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After completing the course please provide either the [https://support.datacamp.com/hc/en-us/articles/360001548814-How-can-I-share-my-certificate-Statement-of-Accomplishment- Statement of Accomplishment] or a screenshot of your learning progress via [link TBA]. 
|}
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 +
 
 +
== Final project ==
 +
Projects description TBA 
 +
Projects pre-registration: link to submit your file TBA 
 +
Final versions of project papers: link to sumbit your files TBA 
 +
 
 +
 
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== References ==
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* Gries, Stefan (2013). Statistics for Linguistics with R : A Practical Introduction (Vol. 2nd revised edition). Berlin: De Gruyter Mouton. [http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=604318 HSE library link]
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* Levshina, Natalia (2015). How to Do Linguistics with R : Data Exploration and Statistical Analysis. Amsterdam: John Benjamins Publishing Company. [http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=nlebk&AN=1093048 HSE library link]
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* Baayen, Harald (2008). Analyzing Linguistic Data: A practical introduction to statistics. Cambridge UP. [http://www.sfs.uni-tuebingen.de/~hbaayen/publications/baayenCUPstats.pdf pdf]
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* Gries, Stefan (2017). Quantitative Corpus Linguistics with R : A Practical Introduction (Vol. Second edition). Milton Park, Abingdon, Oxon: Routledge. eBook
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* Empirical Bayes
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* Harney, H. L. (2016). Bayesian Inference : Data Evaluation and Decisions (Vol. 2nd ed). Springer. eBook 
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* McElreath, R. (2016). Statistical Rethinking : A Bayesian Course with Examples in R and Stan. eBook
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* ggplot2
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* Hadley, W. (2016). Ggplot2 : Elegant Graphics for Data Analysis. Springer. eBook
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* R markdown [https://rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf Rmd Cheat Sheet
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== Course Info ==
  
=== Семинары и домашние задания ===
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This page contains the materials of the course "Linguistic Data: Quantitative Analysis and Visualisation", taught at the HSE Master's program "Computational Linguistics" in 2019-2020 academic year. Modules: 3-4.
{|class='wikitable'
 
!дата семинара
 
!задания на семинар
 
!дедлайн сдачи ДЗ
 
!домашнее задание
 
|-
 
|17.01
 
|[https://docviewer.yandex.ru/view/0/?*=ZsUr%2BkXE%2B98etL0r0cDTcXM%2FUR17InVybCI6InlhLWRpc2stcHVibGljOi8veDRZWGhHeGVqSzRrRCtCa1l0WkRGT1dPS3hmVXpMdE9Kbk1rQjhrblZOT0pIaDJ0M1NHT1F4Z3cxR0FtcVhvRnEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoic2VtMS5wZGYiLCJub2lmcmFtZSI6ZmFsc2UsInVpZCI6IjAiLCJ0cyI6MTU3OTM0NzA3ODc3OSwieXUiOiI0MTI4MDg5NDExNTc5MzQ3MDUzIn0%3D Семинар №1]
 
|24.01
 
|[https://docviewer.yandex.ru/view/0/?*=E2Wnp1S2VF7%2FJ4i5LcjGTpnZHo97InVybCI6InlhLWRpc2stcHVibGljOi8vMGdVY2dFS3MxdjlyNjd4VFNKRm12dDhGaHNibC91azlqODQ0KzdrWkxjWXNsNllXclZqbko2RW83V21yZldrSXEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiaHcxLnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMCIsInRzIjoxNTc5MzQ3MDk1Mjk1LCJ5dSI6IjQxMjgwODk0MTE1NzkzNDcwNTMifQ%3D%3D ДЗ №1]
 
|}
 

Версия 23:54, 18 января 2020

  • Instructors: Ilya Schurov and Olga Lyashevskaya

Materials

Data Topics Links
Jan 18 Introduction. Quantitative linguistic research and data types. R basics Intro Slides Lab 01: intro to R
Jan 25


Software

During this course we will use R as a programming language and RStudio as a GUI.

How to install R and RStudio?

1. Download R (you can choose another mirror here if you wish) and install it on your computer. Make sure you did it before installing RStudio.

2. Download RStudio (you need RStudio Desktop Open Source License) and install it on your computer. It is recommended to create a shortcut for RStudio during installation.

It is possible avoid installing anything on your PC, using rstudio.cloud (an online version of RStudio).

For successful submission of assignments you should be able to create and save R code files (.R) and RMarkdown files (.Rmd).


Homeworks

  • Homework 1 (deadline: January 25, 12:00), Chapters 1, 2, 3, and 5 of the DataCamp course "Introduction to R". Please fill in this form.
  • Homework 2 (deadline: February 1, 12:00), Chapters 4 and 6 of the DataCamp course "Introduction to R".

After completing the course please provide either the Statement of Accomplishment or a screenshot of your learning progress via [link TBA].


Final project

Projects description TBA Projects pre-registration: link to submit your file TBA Final versions of project papers: link to sumbit your files TBA


References

  • Gries, Stefan (2013). Statistics for Linguistics with R : A Practical Introduction (Vol. 2nd revised edition). Berlin: De Gruyter Mouton. HSE library link
  • Levshina, Natalia (2015). How to Do Linguistics with R : Data Exploration and Statistical Analysis. Amsterdam: John Benjamins Publishing Company. HSE library link
  • Baayen, Harald (2008). Analyzing Linguistic Data: A practical introduction to statistics. Cambridge UP. pdf
  • Gries, Stefan (2017). Quantitative Corpus Linguistics with R : A Practical Introduction (Vol. Second edition). Milton Park, Abingdon, Oxon: Routledge. eBook
  • Empirical Bayes
  • Harney, H. L. (2016). Bayesian Inference : Data Evaluation and Decisions (Vol. 2nd ed). Springer. eBook
  • McElreath, R. (2016). Statistical Rethinking : A Bayesian Course with Examples in R and Stan. eBook
  • ggplot2
  • Hadley, W. (2016). Ggplot2 : Elegant Graphics for Data Analysis. Springer. eBook
  • R markdown [https://rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf Rmd Cheat Sheet

Course Info

This page contains the materials of the course "Linguistic Data: Quantitative Analysis and Visualisation", taught at the HSE Master's program "Computational Linguistics" in 2019-2020 academic year. Modules: 3-4.