Linguistic Data: Quantitative Analysis and Visualisation for theoretical linguists: различия между версиями
(Новая страница: «==Course info== Dear students, Here will be published the materials of the course '''"Linguistic Data: Quantitative Analysis and Visualisation"''', taught at t...») |
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==Course info== | ==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 | |
− | |||
− | * Modules: 3-4 | ||
==Software== | ==Software== | ||
+ | During this course we will use R as a programming language and RStudio as a GUI. | ||
− | + | '''How to install R and RStudio?''' | |
− | |||
− | '''How to install R and RStudio?''' | ||
− | 1. Download [https://ftp.acc.umu.se/mirror/CRAN/ R] (you can choose another mirror here if you wish) and install it on your computer. Make sure you did it before installing RStudio. | + | 1. Download [https://ftp.acc.umu.se/mirror/CRAN/ 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://www.rstudio.com/products/rstudio/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. | + | 2. Download [https://www.rstudio.com/products/rstudio/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 [https://rstudio.cloud/ RStudio]. | + | It is possible avoid installing anything on your PC, using online version of [https://rstudio.cloud/ RStudio]. |
− | '''How to use RStudio?''' | + | '''How to use RStudio?''' |
− | Read the instruction [http://math-info.hse.ru/f/2018-19/pep/rstudio-instruction-en.pdf here]. | + | Read the instruction [http://math-info.hse.ru/f/2018-19/pep/rstudio-instruction-en.pdf here]. |
− | For successful submission of assignments you should be able to create and save R code files (.R) | + | For successful submission of assignments you should be able to create and save R code files (.R) and RMarkdown files (.Rmd). |
==Materials== | ==Materials== | ||
Строка 36: | Строка 34: | ||
|- | |- | ||
| 12.01 | | 12.01 | ||
− | | Something about data: population vs sample | + | | Something about data: population vs sample<br>Descriptive statistics <br><br> |
− | | [http://math-info.hse.ru/f/2018-19/ling-data/seminar1.pdf problems1] [http://rpubs.com/AllaT/ldat-rbasics | + | | [http://math-info.hse.ru/f/2018-19/ling-data/seminar1.pdf problems1] [http://rpubs.com/AllaT/ldat-rbasics R-basics]<br> |
− | | RMarkdown: official [https://rmarkdown.rstudio.com/ page], [https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf cheatsheet] | + | | RMarkdown: official [https://rmarkdown.rstudio.com/ page],<br>[https://www.rstudio.com/wp-content/uploads/2015/02/rmarkdown-cheatsheet.pdf cheatsheet]<br><br> |
− | |||
|- | |- | ||
| 19.01 | | 19.01 | ||
− | | Population and samples. Working with data in R | + | | Population and samples. Working with data in R<br> |
− | | [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 | + | | [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]<br>[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] <br><br> |
− | [http://rpubs.com/AllaT/ldat-rvectors | + | | [http://rpubs.com/AllaT/ldat-rplots_1 more] on basic graphs in R<br> |
− | |||
− | |||
− | | [more] on graphs | ||
− | |||
|- | |- | ||
| 26.01 | | 26.01 | ||
| Statistical hypotheses testing | | Statistical hypotheses testing | ||
− | | [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/ | + | | [http://rpubs.com/AllaT/ldat-rbinom Binomial-test] [https://raw.githubusercontent.com/LingData2019/LingData/master/data/poetry_last_in_lines.csv poetry.csv] |
+ | | <br> | ||
+ | |- | ||
+ | | 02.02 | ||
+ | | Student's t-test. Central limit theorem<br> | ||
+ | | [http://rpubs.com/AllaT/ldat-ttest T-test] [http://math-info.hse.ru/f/2018-19/ling-data/icelandic.csv icelandic.csv]<br> | ||
+ | | [http://math-info.hse.ru/f/2018-19/ling-data/dissertation.pdf asp-paper] (Coretta, 2017)<br> | ||
+ | |- | ||
+ | | 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]<br> | ||
+ | | an interactive [https://rpsychologist.com/d3/CI/ visualization] of CI by K.Magnusson<br>[https://www.cscu.cornell.edu/news/statnews/stnews73.pdf more] on overlapping CI's (by A.Knezevic)<br><br> | ||
+ | |- | ||
+ | | 16.02 | ||
+ | | Data manipulation with tidyverse. Visualisation with ggplot2<br> | ||
+ | | [https://lingdata2019.github.io/LingData/Lec_6_tidyverse.html class materials]<br> | ||
+ | | <br> | ||
+ | |- | ||
+ | | 02.03 | ||
+ | | Chi-squared and Fisher's exact tests<br> | ||
+ | | [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]<br> | ||
+ | | <br> | ||
+ | |- | ||
+ | | 16.03 | ||
+ | | Correlation coefficients and simple linear regression<br> | ||
+ | | [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]<br> | ||
+ | | [http://guessthecorrelation.com/ guess correlation game]<br> | ||
+ | |- | ||
+ | | 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]<br> | ||
+ | | [http://www.sthda.com/english/wiki/visualize-correlation-matrix-using-correlogram correlograms] [http://tylervigen.com/page?page=1 spurious correlations]<br> | ||
+ | |- | ||
+ | | 06.04 | ||
+ | | Multiple linear regression<br> | ||
+ | | [http://rpubs.com/AllaT/lingdat-multreg Multiple-regression] [http://math-info.hse.ru/f/2018-19/ling-data/english.csv english.csv]<br> | ||
+ | | [https://cran.r-project.org/web/packages/jtools/vignettes/summ.html more] on visualising coefficients, [https://www.princeton.edu/~otorres/Regression101R.pdf more] tests<br> | ||
+ | |- | ||
+ | | 13.04 | ||
+ | | Logistic regression | ||
+ | | [https://raw.githubusercontent.com/LingData2019/LingData/master/seminars/2019-04-06/Lab10-practice.Rmd Lab10] [Lab10-solutions]<br> | ||
+ | | [https://cran.r-project.org/web/packages/jtools/vignettes/summ.html more] on visualising coefficients<br> | ||
+ | |- | ||
+ | | 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]<br> | ||
+ | | [http://bbolker.github.io/mixedmodels-misc/glmmFAQ.html#model-specification LME in R]<br> | ||
+ | |- | ||
+ | | 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] | ||
+ | | <br> | ||
+ | |- | ||
+ | | 25.05 | ||
+ | | PCA<br> | ||
+ | | [https://lingdata2019.github.io/LingData/Lec_14_PCA.html class materials]<br> | ||
+ | | <br> | ||
+ | |- | ||
+ | | 01.06 | ||
+ | | Clustering | ||
+ | | [https://raw.githubusercontent.com/agricolamz/2018-MAG_R_course/master/data/baltic.csv swadesh.csv] | ||
+ | | <br> | ||
+ | |- | ||
+ | | 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] | ||
+ | | <br> | ||
+ | |} | ||
+ | ===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 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 | + | 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/2019-01-19/teo/r-more-vectors.Rmd R-vectors.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/2019-01-19/teo/r-samples.Rmd R-samples.Rmd], | ||
+ | 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== | ||
− | * [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW1.pdf Homework 1] (deadline: 27 January, 23:59) | + | * [http://math-info.hse.ru/f/2018-19/ling-data/LingData-HW1.pdf Homework 1] (deadline: 27 January, 23:59), [https://docs.google.com/forms/d/e/1FAIpQLSehhy-j0Y2LIIfen6kqlz2Za5QUYvcZQ_7m3L5PAUrQbMDXwA/viewform 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) | ||
+ | |||
+ | * [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 04:11, 7 февраля 2020
Содержание
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
- Homework 1 (deadline: 27 January, 23:59), link to submit
- Homework 2 (deadline: 03 February, 23:59)
- Homework 3 (deadline: 10 February, 23:59), Rmd-file to fill in, link to submit your .Rmd file
- Homework 4 (deadline: 19 February, 23:59), Rmd-file to fill in, link to submit your .Rmd file
- Homework 5 (deadline: 3 March, 23:59), Rmd-file to fill in, link to submit your .Rmd file
- Homework 6 (deadline: 15 May, 23:59), Rmd-file to fill in, link to submit your .Rmd file
Final project
- 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