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| − | + | * Instructors: Ilya Schurov and Olga Lyashevskaya | |
| − | + | == Materials == | |
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| − | + | ! Data !! Topics !! Links | |
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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/LingData2020/tree/master/seminars/2020-01-18 Lab 01: intro to R] |
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| − | | | + | | Jan 25 || Hypothesis testing. Binomial test. R: dataframes, tydyverse || [https://github.com/LingData2019/LingData2020/tree/master/seminars/2020-01-25 Lab 02] |
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| − | | | + | | Feb 2 || Central limit theorem. Variance. Student's t-test. R: simulating data, boxplots, density plots, binomial test, t-test || |
| − | | | + | [https://github.com/LingData2019/LingData2020/tree/master/seminars/2020-02-01 Lab 03: ] |
| − | + | [https://raw.githubusercontent.com/LingData2019/LingData2020/master/seminars/2020-02-01/Lab3-ttest-binom-matrices.Rmd Rmd] | |
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| − | + | == Software == | |
| − | + | During this course we will use R as a programming language and RStudio as a GUI. | |
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| − | + | How to install R and RStudio? | |
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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. | |
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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. | |
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| − | + | It is possible avoid installing anything on your PC, using [https://rstudio.cloud rstudio.cloud] (an online version of RStudio). | |
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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). | |
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| − | + | == Homeworks == | |
| − | + | * 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]. | |
| − | + | * 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". | |
| − | + | 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 8, 12:00), Hypothesis testing, binomial test, t-test. | |
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| − | + | == 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 | |
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| − | + | == 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] | |
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| − | + | * 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 | |
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| − | == | + | == Course Info == |
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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. | |
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Версия 12:26, 1 февраля 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 | Hypothesis testing. Binomial test. R: dataframes, tydyverse | Lab 02 |
| Feb 2 | Central limit theorem. Variance. Student's t-test. R: simulating data, boxplots, density plots, binomial test, t-test |
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]. 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 8, 12:00), Hypothesis testing, binomial test, t-test.
Final project
Projects description 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. 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.
