Linguistic Data: Quantitative Analysis and Visualisation for theoretical linguists — различия между версиями

Материалы по математике, 2018-19 учебный год
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(Homeworks)
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(не показаны 102 промежуточные версии 4 участников)
Строка 32: Строка 32:
 
! Date !! Topic of the lecture !! Seminar !! Optional
 
! Date !! Topic of the lecture !! Seminar !! Optional
 
|-
 
|-
| 12.01 || Something about data: population vs sample, descriptive statistics || [http://math-info.hse.ru/f/2018-19/ling-data/seminar1.pdf problems1] [http://rpubs.com/AllaT/ldat-rbasics r-basics]|| RMarkdown: official [https://rmarkdown.rstudio.com/ page], [https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf cheatsheet]
+
| 12.01 || Something about data: population vs sample
 +
Descriptive statistics  
 +
|| [http://math-info.hse.ru/f/2018-19/ling-data/seminar1.pdf problems1] [http://rpubs.com/AllaT/ldat-rbasics R-basics]
 +
|| RMarkdown: official [https://rmarkdown.rstudio.com/ page],  
 +
[https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf cheatsheet]
 
|-
 
|-
| 19.01 || Population and samples. Working with data in R || [http://math-info.hse.ru/f/2018-19/ling-data/seminar2.pdf problems2] [http://rpubs.com/AllaT/ldat-samples samples] [http://math-info.hse.ru/f/2018-19/ling-data/artists-sizes.txt artists.txt]  
+
| 19.01 || Population and samples. Working with data in R  
[http://rpubs.com/AllaT/ldat-rvectors r-vectors] [http://rpubs.com/AllaT/ldat-dataframes r-dataframes] [http://math-info.hse.ru/f/2018-19/ling-data/Chi.kuk.2007.csv orientation.csv]  
+
|| [http://math-info.hse.ru/f/2018-19/ling-data/seminar2.pdf problems2] [http://rpubs.com/AllaT/ldat-samples R-samples] [http://math-info.hse.ru/f/2018-19/ling-data/artists-sizes.txt artists.txt]  
|| [http://rpubs.com/AllaT/ldat-rplots_1 More] on basic graphs in R
+
[http://rpubs.com/AllaT/ldat-rvectors R-vectors] [http://rpubs.com/AllaT/ldat-dataframes R-dataframes] [http://math-info.hse.ru/f/2018-19/ling-data/Chi.kuk.2007.csv orientation.csv]  
 +
|| [http://rpubs.com/AllaT/ldat-rplots_1 more] on basic graphs in R
 
|-
 
|-
| 26.01 || Statistical hypotheses testing || [http://rpubs.com/AllaT/ldat-rbinom binom-test] [https://raw.githubusercontent.com/LingData2019/LingData/master/data/poetry_last_in_lines.csv poetry.csv] ||
+
| 26.01 || Statistical hypotheses testing || [http://rpubs.com/AllaT/ldat-rbinom Binomial-test] [https://raw.githubusercontent.com/LingData2019/LingData/master/data/poetry_last_in_lines.csv poetry.csv] ||
 
|-
 
|-
| 02.02 || Student's t-test. Central limit theorem: recall || [http://math-info.hse.ru/f/2018-19/ling-data/icelandic.csv icelandic.csv]  
+
| 02.02 || Student's t-test. Central limit theorem
|| [http://math-info.hse.ru/f/2018-19/ling-data/dissertation.pdf paper] (Coretta, 2017)
+
|| [http://rpubs.com/AllaT/ldat-ttest T-test] [http://math-info.hse.ru/f/2018-19/ling-data/icelandic.csv icelandic.csv]  
 +
|| [http://math-info.hse.ru/f/2018-19/ling-data/dissertation.pdf asp-paper] (Coretta, 2017)
 +
|-
 +
| 09.02 || Confidence Intervals  ||  [http://rpubs.com/AllaT/ldat-conf_ints Conf-intervals] [https://raw.githubusercontent.com/LingData2019/LingData/master/data/poetry_last_in_lines.csv poetry.csv] [http://math-info.hse.ru/f/2018-19/ling-data/icelandic.csv icelandic.csv]
 +
|| an interactive [https://rpsychologist.com/d3/CI/ visualization] of CI by K.Magnusson
 +
[https://www.cscu.cornell.edu/news/statnews/stnews73.pdf more] on overlapping CI's (by A.Knezevic)
 +
|-
 +
| 16.02 || Data manipulation with tidyverse. Visualisation with ggplot2
 +
|| [https://lingdata2019.github.io/LingData/Lec_6_tidyverse.html class materials]
 +
 
 +
||
 +
|-
 +
| 02.03 || Chi-squared and Fisher's exact tests
 +
|| [http://rpubs.com/AllaT/ling-chisq Chi-squared-test] [https://raw.githubusercontent.com/LingData2019/LingData/master/data/elision.csv elision.csv] [http://math-info.hse.ru/f/2018-19/pep/socling.csv socling.csv]
 +
||
 +
|-
 +
|16.03 || Correlation coefficients and simple linear regression
 +
|| [http://rpubs.com/AllaT/ling-corr Corr-regression][https://raw.githubusercontent.com/LingData2019/LingData/master/data/education.csv education.csv][https://raw.githubusercontent.com/LingData2019/LingData/master/data/chekhov.csv chekhov.csv]
 +
|| [http://guessthecorrelation.com/ guess correlation game]
 +
|-
 +
|23.03 || Multiple comparisons. ANOVA || [http://rpubs.com/AllaT/lingdat-anova-mc Anova] [http://math-info.hse.ru/f/2018-19/ling-data/icelandic.csv icelandic.csv]
 +
|| [http://www.sthda.com/english/wiki/visualize-correlation-matrix-using-correlogram correlograms] [http://tylervigen.com/page?page=1 spurious correlations]
 +
|-
 +
|06.04 || Multiple linear regression
 +
|| [http://rpubs.com/AllaT/lingdat-multreg Multiple-regression] [http://math-info.hse.ru/f/2018-19/ling-data/english.csv english.csv]
 +
|| [https://cran.r-project.org/web/packages/jtools/vignettes/summ.html more] on visualising coefficients, [https://www.princeton.edu/~otorres/Regression101R.pdf more] tests
 +
|-
 +
|13.04 || Logistic regression || [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-04-06/Lab10-practice.Rmd Lab10] [Lab10-solutions]
 +
|| [https://cran.r-project.org/web/packages/jtools/vignettes/summ.html more] on visualising coefficients
 +
|-
 +
|27.04 || More on model diagnostics. Mixed-effects models || [http://rpubs.com/AllaT/lingdat-me Mixed-effects] [https://raw.githubusercontent.com/LingData2019/LingData/master/data/duryagin_ReductionRussian.txt ReductionRussian.txt]
 +
|| [http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#model-specification LME in R]
 +
|-
 +
|18.05 || Decision trees and random forest. || [https://github.com/LingData2019/LingData/blob/master/seminars/2019-04-27/Lab12_class.Rmd Lab 12. Trees and forests] [https://github.com/LingData2019/LingData/blob/master/seminars/2019-04-27/Lab12.Rmd Code] ||
 +
|-
 +
| 25.05 || PCA
 +
|| [https://lingdata2019.github.io/LingData/Lec_14_PCA.html class materials]
 +
 
 +
||
 +
|-
 +
|01.06 || Clustering || [http://bit.ly/2YXd8sH swadesh.csv] ||
 +
|-
 +
|08.06 || NeighborNet. Simulation statistics || [http://math-info.hse.ru/f/2018-19/ling-data/prefixes.txt prefixes.txt] [http://math-info.hse.ru/f/2018-19/ling-data/08-06.R R code] [http://math-info.hse.ru/f/2017-18/py-prog/scores2.csv scores2.csv]||
 
|}
 
|}
  
 
=== R seminars in pdf ===
 
=== R seminars in pdf ===
  
12 January: [http://math-info.hse.ru/f/2018-19/ling-data/Rbasics_TEO-pdf.pdf r-basics], 19 January: [http://math-info.hse.ru/f/2018-19/ling-data/r-more-vectors-pdf.pdf r-vectors], [http://math-info.hse.ru/f/2018-19/ling-data/r-dataframes-pdf.pdf r-dataframes], [http://math-info.hse.ru/f/2018-19/ling-data/r-samples-pdf.pdf r-samples], 26 January: [http://math-info.hse.ru/f/2018-19/ling-data/binom-test-pdf.pdf binom-test]
+
12 January: [http://math-info.hse.ru/f/2018-19/ling-data/Rbasics_TEO-pdf.pdf R-basics], 19 January: [http://math-info.hse.ru/f/2018-19/ling-data/r-more-vectors-pdf.pdf R-vectors], [http://math-info.hse.ru/f/2018-19/ling-data/r-dataframes-pdf.pdf R-dataframes], [http://math-info.hse.ru/f/2018-19/ling-data/r-samples-pdf.pdf R-samples], 26 January: [http://math-info.hse.ru/f/2018-19/ling-data/binom-test-pdf.pdf Binomial-test]
 +
 
 +
2 February: [http://math-info.hse.ru/f/2018-19/ling-data/t-test.pdf T-test], 9 February: [http://math-info.hse.ru/f/2018-19/ling-data/conf-ints.pdf Conf-intervals]
 +
 
 +
02 March: [http://math-info.hse.ru/f/2018-19/ling-data/chisq-test.pdf Chi-squared-test], 16 March: [http://math-info.hse.ru/f/2018-19/ling-data/CorrLab.pdf Corr-regression], 23 March: [http://math-info.hse.ru/f/2018-19/ling-data/anova-theo.pdf Anova]
 +
 
 +
6 April: [http://math-info.hse.ru/f/2018-19/ling-data/mult-reg-pdf.pdf Multiple-regression], 27 April: [http://math-info.hse.ru/f/2018-19/ling-data/mixed-effects.pdf Mixed-effects]
  
 
=== R seminars in .R and .Rmd ===
 
=== R seminars in .R and .Rmd ===
  
12 January: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/12-01/r-basics.R r-basics.R],  [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/12-01/Rbasics-TEO.Rmd r-basics.Rmd], 19 January: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/19-01/teo/r-more-vectors.R r-vectors.R],   
+
12 January: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-12/r-basics.R R-basics.R],  [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-12/r-basics.Rmd R-basics.Rmd], 19 January: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-19/teo/r-more-vectors.R R-vectors.R],   
[https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/19-01/teo/r-more-vectors.Rmd r-vectors.Rmd]  
+
[https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-19/teo/r-more-vectors.Rmd R-vectors.Rmd]  
[https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/19-01/teo/r-dataframes.R r-dataframes.R], [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/19-01/teo/r-dataframes.Rmd r-dataframes.Rmd],  
+
[https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-19/teo/r-dataframes.R R-dataframes.R], [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-19/teo/r-dataframes.Rmd R-dataframes.Rmd],  
[https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/19-01/teo/r-samples.Rmd r-samples.Rmd],
+
[https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-19/teo/r-samples.Rmd R-samples.Rmd],
26 January: [https://github.com/LingData2019/LingData/blob/master/seminars/26-01/26-01.Rmd binom-test]
+
26 January: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-01-26/26-01.Rmd Binomial-test.Rmd]
 +
 
 +
2 February: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-02-02/t-test.R T-test.R], [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-02-02/02-02.Rmd T-test.Rmd], 9 February: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-02-09/09-02.Rmd Conf-intervals.Rmd]
 +
[https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-02-09/conf-ints.R Conf-intervals.R]
 +
 
 +
2 March: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-03-02/chisq-02-03.Rmd Chi-squared-test.Rmd], [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-03-02/chisq-test.R Chi-squared-test.R],
 +
16 March: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-03-16/corr-regression.R Corr-regression.R], [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-03-16/corr-regression.Rmd Corr-regression.Rmd],
 +
23 March: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-03-23/anova.R Anova.R], [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-03-23/anova.Rmd Anova.Rmd]
 +
 
 +
6 April: [Multiple-regression.R], [Multiple-regression.Rmd], 27 April: [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-04-27/mixed-effects.R Mixed-models.R], [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-04-27/mixed-effects.Rmd Mixed-models.Rmd]
  
 
== Homeworks ==
 
== Homeworks ==
Строка 60: Строка 122:
 
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW1.pdf Homework 1] (deadline: 27 January, 23:59), [https://goo.gl/forms/TBx0wLPofFUfZFrI3 link] to submit
 
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW1.pdf Homework 1] (deadline: 27 January, 23:59), [https://goo.gl/forms/TBx0wLPofFUfZFrI3 link] to submit
 
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW2.pdf Homework 2] (deadline: 03 February, 23:59)
 
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW2.pdf Homework 2] (deadline: 03 February, 23:59)
* [https://raw.githubusercontent.com/LingData2019/LingData/master/hw/LingData-HW3.Rmd Homework 3] (deadline: __ February, 23:59), [ link] to submit the .Rmd file
+
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW3.pdf Homework 3] (deadline: 10 February, 23:59), [https://raw.githubusercontent.com/LingData2019/LingData/master/hw/LingData-HW3.Rmd Rmd-file] to fill in, [https://www.dropbox.com/request/1e7CcztPAO3WklIsN0fU link] to submit your ''.Rmd'' file
 +
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW4-teo.pdf Homework 4] (deadline: 19 February, 23:59), [https://raw.githubusercontent.com/LingData2019/LingData/master/hw/LingData-HW4-teo.Rmd Rmd-file] to fill in, [https://www.dropbox.com/request/LbUBzdF19dcwX9nnMXpk link] to submit your ''.Rmd'' file
 +
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW5.pdf Homework 5] (deadline: 3 March, 23:59), [https://raw.githubusercontent.com/LingData2019/LingData/master/hw/rmd-templates/HW5-template.Rmd Rmd-file] to fill in, [https://www.dropbox.com/request/BY9JbVrYFDwXkRVBS2ci link] to submit your ''.Rmd'' file
 +
* [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW6.pdf Homework 6] (deadline: 15 May, 23:59), [https://raw.githubusercontent.com/LingData2019/LingData/master/hw/rmd-templates/HW6-template.Rmd Rmd-file] to fill in, [https://www.dropbox.com/request/rBTOCpEsNXy6hkzO2f26 link] to submit your ''.Rmd'' file
 +
 
 +
== Final project ==
 +
* [http://math-info.hse.ru/f/2018-19/ling-data/projects.pdf Projects description]
 +
* Project topics: [https://docs.google.com/spreadsheets/d/1QxLq2JTO9p7xJFo-KP3XyrRbexYwxQhNqTElDAGJEls/edit?usp=sharing link] to the table to fill in
 +
* Projects pre-registration (deadline: 28 April, 23:59): [https://www.dropbox.com/request/I6XC3W9GkiAB3aQisxJq link] to submit your file
 +
* Final versions of projects:  [https://www.dropbox.com/request/Ds4JI7vs9rAhLAG3tI6o link] to sumbit your files

Текущая версия на 20:57, 19 июня 2019

Course info

Dear students,

Here will be published the materials of the course "Linguistic Data: Quantitative Analysis and Visualisation", taught at the Master programme "Linguistic Theory and Language Description" in 2018-2019 academic year.

  • Instructors: Olga Lyashevskaya, George Moroz, Alla Tambovtseva and Ilya Schurov.
  • Modules: 3-4

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 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 online version of RStudio.

How to use RStudio?

Read the instruction here.

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

Materials

Date Topic of the lecture Seminar Optional
12.01 Something about data: population vs sample

Descriptive statistics

problems1 R-basics RMarkdown: official page,

cheatsheet

19.01 Population and samples. Working with data in R problems2 R-samples artists.txt

R-vectors R-dataframes orientation.csv

more on basic graphs in R
26.01 Statistical hypotheses testing Binomial-test poetry.csv
02.02 Student's t-test. Central limit theorem T-test icelandic.csv asp-paper (Coretta, 2017)
09.02 Confidence Intervals Conf-intervals poetry.csv icelandic.csv an interactive visualization of CI by K.Magnusson

more on overlapping CI's (by A.Knezevic)

16.02 Data manipulation with tidyverse. Visualisation with ggplot2 class materials
02.03 Chi-squared and Fisher's exact tests Chi-squared-test elision.csv socling.csv
16.03 Correlation coefficients and simple linear regression Corr-regressioneducation.csvchekhov.csv guess correlation game
23.03 Multiple comparisons. ANOVA Anova icelandic.csv correlograms spurious correlations
06.04 Multiple linear regression Multiple-regression english.csv more on visualising coefficients, more tests
13.04 Logistic regression Lab10 [Lab10-solutions] more on visualising coefficients
27.04 More on model diagnostics. Mixed-effects models Mixed-effects ReductionRussian.txt LME in R
18.05 Decision trees and random forest. Lab 12. Trees and forests Code
25.05 PCA class materials
01.06 Clustering swadesh.csv
08.06 NeighborNet. Simulation statistics prefixes.txt R code scores2.csv

R seminars in pdf

12 January: R-basics, 19 January: R-vectors, R-dataframes, R-samples, 26 January: Binomial-test

2 February: T-test, 9 February: Conf-intervals

02 March: Chi-squared-test, 16 March: Corr-regression, 23 March: Anova

6 April: Multiple-regression, 27 April: Mixed-effects

R seminars in .R and .Rmd

12 January: R-basics.R, R-basics.Rmd, 19 January: R-vectors.R, R-vectors.Rmd R-dataframes.R, R-dataframes.Rmd, R-samples.Rmd, 26 January: Binomial-test.Rmd

2 February: T-test.R, T-test.Rmd, 9 February: Conf-intervals.Rmd Conf-intervals.R

2 March: Chi-squared-test.Rmd, Chi-squared-test.R, 16 March: Corr-regression.R, Corr-regression.Rmd, 23 March: Anova.R, Anova.Rmd

6 April: [Multiple-regression.R], [Multiple-regression.Rmd], 27 April: Mixed-models.R, Mixed-models.Rmd

Homeworks

Final project

  • Projects description
  • Project topics: link to the table to fill in
  • Projects pre-registration (deadline: 28 April, 23:59): link to submit your file
  • Final versions of projects: link to sumbit your files