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

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* Instructors: Ilya Schurov and Olga Lyashevskaya
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'''Дорогие третьекурсники!'''
  
== Materials ==
+
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.
{| class="wikitable"
+
Для специализациии «Политический анализ» настоящая дисциплина является обязательной.
 +
 
 +
* Авторы курса: К.И. Сонин, Д.А. Дагаев, Л.Н. Сысоева
 +
* Лекции читает: Сысоева Любовь Николаевна (lsysoeva@hse.ru)
 +
* Семинары ведет: Сысоева Любовь Николаевна
 +
* Ассистент: Паршина Анастасия (a.a.parshina@ya.ru)
 +
 
 +
== Материалы ==
 +
 
 +
=== Электронная ведомость ===
 +
https://docs.google.com/spreadsheets/d/1BZ4EQ1ZCpDEzOI-GwDDW-RLdp6_Sfw6qh6jpuUGZetY/edit?usp=sharing
 +
 
 +
=== Лекции ===
 +
{|class='wikitable'
 +
!дата лекции
 +
!тема лекции
 +
!литература
 
|-
 
|-
! Data !! Topics !! Links
+
|17.01
 +
|[https://docviewer.yandex.ru/view/0/?*=513gH0X4nkqZPwLUPPZhvGFnAdt7InVybCI6InlhLWRpc2stcHVibGljOi8vZUNPZGxuNUlGR1U1Nlc3czcrbzFaUmtNbzU5Y1NSZlVTMFNBZFJ1U2J4NGI4S3l5bjhiNEFBUlo5M0JKQ1Iza3EvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiTGVjdHVyZV8xLnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMCIsInRzIjoxNTc5MzQ3MjE3MjQ0LCJ5dSI6IjQxMjgwODk0MTE1NzkzNDcwNTMifQ%3D%3D Стратегическое финансирование избирательных компаний]
 +
|S. Gehlbach. Formal Models of Domestic Politics. Paragraph 3.1.
 
|-
 
|-
| 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/LingData2020/tree/master/seminars/2020-01-18 Lab 01: intro to R]
+
|24.01
 +
|[https://docviewer.yandex.ru/view/22496587/?*=5%2F22%2BJzxT1bTO5Ogqbz8DQuIgl17InVybCI6InlhLWRpc2stcHVibGljOi8vMzZLK3N4ZzM3bzJHNC9kM2EvaWNxK2NzWW9pRWtJWVl1eWdNY1Vld0pxakpTT0cwM3dFN3BBS2gzRkZkSTZPN3EvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiTGVjdHVyZV8yLnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMjI0OTY1ODciLCJ0cyI6MTU3OTg3MzM2ODc4MSwieXUiOiIzOTAwNDcxNjExNTc2MjQwMDA2In0%3D Двухмерная модель Даунса]
 +
|J. Duggan. Formal Models in Political Science. Lecture notes. Lectures 6,7.
 +
S. Gehlbach. Formal Models in Political Science. Paragraph 1.1: The Hotelling-Downs model.
 
|-
 
|-
| Jan 25 || Hypothesis testing. Binomial test. R: dataframes, tydyverse || [https://github.com/LingData2019/LingData2020/tree/master/seminars/2020-01-25 Lab 02] [https://datacamp-community-prod.s3.amazonaws.com/e63a8f6b-2aa3-4006-89e0-badc294b179c tidy verse cheat sheet]
+
|24.01
 +
|[https://docviewer.yandex.ru/view/22496587/?*=Pq8HHP2gq9j9w%2BYISPVwbs%2F8%2F397InVybCI6InlhLWRpc2stcHVibGljOi8vR1VBbGtEZ0pxUVZDTjJuTnlQeElTMm1QWDZScGpXSXlNcHZ5bi85dnFhK3RXTXRXOGE4bTRrVGNMWHByRytXQXEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiTGVjdHVyZV8zLnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMjI0OTY1ODciLCJ0cyI6MTU4MDQ4NzY5OTQ0MywieXUiOiIzOTAwNDcxNjExNTc2MjQwMDA2In0%3D Модель Осборна-Сливински самовыдвижения кандидатов на выборах]
 +
|S. Gehlbach. Formal Models in Political Science. Paragraph 1.4.3.
 +
M.J. Osborne, A. Slivinski. A Model of Political Competition with Citizen Candidates. Quarterly
 +
Journal of Economics, vol.111, pp. 65-96 (1993).
 
|-
 
|-
| Feb 1 || Central limit theorem. Variance. Student's t-test. R: simulating data, boxplots, density plots, binomial test, t-test ||
+
|14.02
[https://github.com/LingData2019/LingData2020/tree/master/seminars/2020-02-01 Lab 03: ]
+
|[https://docviewer.yandex.ru/view/22496587/?*=Oy%2B6wgzxIihuxd0UDQ4geylh2O97InVybCI6InlhLWRpc2stcHVibGljOi8vSFFhYWFZaCtUcDl2MHFhUHNsTm1qM1o3NXFpZnNEMTVnU0JqV0hLeTgrM0xmalRpOVhtT3lKeHRGa3NIMGYwcHEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiTGVjdHVyZV80LnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMjI0OTY1ODciLCJ0cyI6MTU4MTY5MDk5Mzk3MiwieXUiOiIzOTAwNDcxNjExNTc2MjQwMDA2In0%3D Модель политической подотчетности Барро-Фереджона]
[https://raw.githubusercontent.com/LingData2019/LingData2020/master/seminars/2020-02-01/Lab3-ttest-binom-matrices.Rmd Rmd] [https://htmlpreview.github.io/?https://github.com/LingData2019/LingData2020/blob/master/seminars/2020-02-01/Lab3-ttest-binom-matrices.html html]
+
|S. Gehlbach. Formal Models in Political Science. Paragraph 6.1.
|-
+
|}
| Feb 8 || Two-sample T-test. ANOVA. Confidence intervals. Non-parametric tests ||
+
 
|-
+
=== Семинары и домашние задания ===
| || Tests for categorial data. Chi-squared test. Fisher exact test. Effect size. ||
+
{|class='wikitable'
|-
+
!дата семинара
|  || Correlations. Linear regression ||
+
!задания на семинар
|-
+
!дедлайн сдачи ДЗ
|  || Multivariate linear regression. Dummy variables ||
+
!домашнее задание
 
|-
 
|-
| || Dimensionality reduction. PCA. MDS. t-SNE ||
+
|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]
 
|-
 
|-
| || CA, MCA. Clusterization ||  
+
|24.01
 +
|[https://docviewer.yandex.ru/view/22496587/?*=6yqYB7IXnzfr5qB8fab5q0zIS0p7InVybCI6InlhLWRpc2stcHVibGljOi8vNnE0L3NkWmZWR0tLUkNyNDdwVWZJWjk3anpXZzcxZTlHYnJoUVNjRURnRHpvMkhFalJ2azdTVDhMV0VHMTBqVXEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoic2VtMi5wZGYiLCJub2lmcmFtZSI6ZmFsc2UsInVpZCI6IjIyNDk2NTg3IiwidHMiOjE1Nzk4NzM0ODQ5OTQsInl1IjoiMzkwMDQ3MTYxMTU3NjI0MDAwNiJ9 Семинар №2]
 +
|31.01
 +
|[https://docviewer.yandex.ru/view/22496587/?*=tZv9sQu4nzZKRRIHMYYjs7%2FQHxh7InVybCI6InlhLWRpc2stcHVibGljOi8vQXBSTm1YRytrNHRaaHFHQ3I1bllhVzY4U3NUQ0xuMGFMeHNSQ2dFVG0zUWlZVFZBNmlQMHZTdFJrVWdUNWxGbnEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiaHcyLnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMjI0OTY1ODciLCJ0cyI6MTU3OTg3MzU0OTcxMiwieXUiOiIzOTAwNDcxNjExNTc2MjQwMDA2In0%3D ДЗ №2]
 
|-
 
|-
| || Logistic regression. Model selection ||  
+
|31.01
 +
|[https://docviewer.yandex.ru/view/22496587/?*=1R1V0ibBRhI7yMKpdgCPrwr3kKx7InVybCI6InlhLWRpc2stcHVibGljOi8vaGI5Z0JnNVdEamtJc0VHbi9OM3BZT1F5cHJzalJnSStBRDVWQ28wcEowOHJqR2Y1VVorY01BVDUwbjV3V2F6eHEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoic2VtMy5wZGYiLCJub2lmcmFtZSI6ZmFsc2UsInVpZCI6IjIyNDk2NTg3IiwidHMiOjE1ODA0ODc4OTg0OTksInl1IjoiMzkwMDQ3MTYxMTU3NjI0MDAwNiJ9 Семинар №3]
 +
|7.02
 +
|[https://docviewer.yandex.ru/view/22496587/?*=Q7oMZ0LknBuGzoJmMI3YMBExsmx7InVybCI6InlhLWRpc2stcHVibGljOi8vWWVQN0MrMUZ6LzB4UnBaU282UHROWGtsUXVObldiaXFmUkR4a0xtZ3hoK0oyYTd6ZnNsUTBGS00yQ0xYNFkyenEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoiaHczLnBkZiIsIm5vaWZyYW1lIjpmYWxzZSwidWlkIjoiMjI0OTY1ODciLCJ0cyI6MTU4MDQ4Nzg1MzMzOSwieXUiOiIzOTAwNDcxNjExNTc2MjQwMDA2In0%3D ДЗ №3]
 
|-
 
|-
| || Fixed and random effects. Linear mixed-effects models ||
+
|07.02
|-
+
|[https://docviewer.yandex.ru/view/22496587/?*=w62ZLX0quEz1wD%2Fly%2B0aD9Aj6iV7InVybCI6InlhLWRpc2stcHVibGljOi8vMjVnYTdhV1RDbGFFZC9RVnNyZFA3cUFxM0RrMnR4TEVZdTVqeU5lSE1BMy8rZERTakcrYTkxZWJIdlEzRU5DVHEvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoicG92dG9yZW5pZV9pemJpcmF0X2tvbXAucGRmIiwibm9pZnJhbWUiOmZhbHNlLCJ1aWQiOiIyMjQ5NjU4NyIsInRzIjoxNTgxMDE2Nzk5NTMzLCJ5dSI6IjM5MDA0NzE2MTE1NzYyNDAwMDYifQ%3D%3D Семинар №4]
|  || Bootstrap. Decision trees. Decision forests ||
+
|
|-
+
|
|  || Bayesian statistics ||  
 
|-
 
|  || Bayesian statistics II ||  
 
 
|-
 
|-
 +
|14.02
 +
|[https://docviewer.yandex.ru/view/22496587/?*=Ol9EVceRyA%2FEtZjRewfcJnXoN6F7InVybCI6InlhLWRpc2stcHVibGljOi8vV2tzZGE3VGMvb1NhWG1SVUh6WEkxZUNkNVNqNVplQTN6bzQ4QjUrWHR4OTErWGREOUZDcmREUk93YTltclNhc3EvSjZicG1SeU9Kb25UM1ZvWG5EYWc9PSIsInRpdGxlIjoic2VtNC5wZGYiLCJub2lmcmFtZSI6ZmFsc2UsInVpZCI6IjIyNDk2NTg3IiwidHMiOjE1ODE2OTExOTY4MDMsInl1IjoiMzkwMDQ3MTYxMTU3NjI0MDAwNiJ9 Семинар №5]
 +
|21.02
 +
|[ ДЗ №4]
 
|}
 
|}
 
== 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 [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.
 
 
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.
 
 
It is possible avoid installing anything on your PC, using [https://rstudio.cloud 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: February 16, 23:59), 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]. 
 
* Homework 2 (deadline: February 23, 23:59), Chapters 4 and 6 of the [https://www.datacamp.com/courses/free-introduction-to-r DataCamp] course "Introduction to R". 
 
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]. 
 
Deadlines for Homework 1 and 2 are cancelled due to unavailability of the free version of the datacamp online course. Stay tuned!
 
* Homework 3 (deadline: February 9, 12:00), Hypothesis testing, binomial test, t-test. [https://github.com/LingData2019/LingData2020/blob/master/hw/hw-pdf/LingData-HW3-comp.pdf HW3 pdf] [https://htmlpreview.github.io/?https://github.com/LingData2019/LingData2020/blob/master/hw/LingData-HW3-comp.html html] [https://github.com/LingData2019/LingData2020/blob/master/hw/LingData-HW3-comp.Rmd Rmd template]
 
 
== Final project ==
 
* Projects description [https://github.com/LingData2019/LingData2020/blob/master/projects.pdf link] 
 
* 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. [http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=604318 HSE library link]
 
* 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]
 
* Baayen, Harald (2008). Analyzing Linguistic Data: A practical introduction to statistics. Cambridge UP. [http://www.sfs.uni-tuebingen.de/~hbaayen/publications/baayenCUPstats.pdf 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.
 

Версия 17:40, 14 февраля 2020

Дорогие третьекурсники!

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. Для специализациии «Политический анализ» настоящая дисциплина является обязательной.

  • Авторы курса: К.И. Сонин, Д.А. Дагаев, Л.Н. Сысоева
  • Лекции читает: Сысоева Любовь Николаевна (lsysoeva@hse.ru)
  • Семинары ведет: Сысоева Любовь Николаевна
  • Ассистент: Паршина Анастасия (a.a.parshina@ya.ru)

Материалы

Электронная ведомость

https://docs.google.com/spreadsheets/d/1BZ4EQ1ZCpDEzOI-GwDDW-RLdp6_Sfw6qh6jpuUGZetY/edit?usp=sharing

Лекции

дата лекции тема лекции литература
17.01 Стратегическое финансирование избирательных компаний S. Gehlbach. Formal Models of Domestic Politics. Paragraph 3.1.
24.01 Двухмерная модель Даунса J. Duggan. Formal Models in Political Science. Lecture notes. Lectures 6,7.

S. Gehlbach. Formal Models in Political Science. Paragraph 1.1: The Hotelling-Downs model.

24.01 Модель Осборна-Сливински самовыдвижения кандидатов на выборах S. Gehlbach. Formal Models in Political Science. Paragraph 1.4.3.

M.J. Osborne, A. Slivinski. A Model of Political Competition with Citizen Candidates. Quarterly Journal of Economics, vol.111, pp. 65-96 (1993).

14.02 Модель политической подотчетности Барро-Фереджона S. Gehlbach. Formal Models in Political Science. Paragraph 6.1.

Семинары и домашние задания

дата семинара задания на семинар дедлайн сдачи ДЗ домашнее задание
17.01 Семинар №1 24.01 ДЗ №1
24.01 Семинар №2 31.01 ДЗ №2
31.01 Семинар №3 7.02 ДЗ №3
07.02 Семинар №4
14.02 Семинар №5 21.02 [ ДЗ №4]