Linguistic Data: Quantitative Analysis and Visualisation: linguistic theory
- Instructors: Ilya Schurov and Ivan Pozdnyakov
Содержание
Materials
Data | Topics | Links | video |
---|---|---|---|
Jan 11 | Introduction. Quantitative linguistic research and data types. R basic | notebook | lecture, practice |
Jan 18 | Measures of statistical dispersion. Variance and standard deviation. | script | lecture, practice |
Jan 25 | Statistical hypothesis testing. Binomial test. | lecture, practice | |
Feb 1 | Estimate of mean. Central limit theorem | video | |
Feb 8 | One sample t-test | seminar Rmd preview | video |
Feb 15 | Review | Rmd, preview | video |
Feb 27 | Two-sample t-test. One-sided and two-sided alternatives | video | |
March 15 | Chi-squared test | video | |
April 5 | Multiple comparisons problem. ANOVA (Analysis of Variances) | video | |
April 12 | Confidence intervals. Correlation | video | |
April 19 | Bivariate regression | video | |
April 26 | Multivariate regression and causal questions | video | |
May 15 | Categorical variables in regression models | ||
May 17 | Interactions | ||
May 24 | Logistic regression | ||
May 29 | Mixed effects models |
Homeworks
Academic ethics policy: you have to do your homeworks by yourself. In case of academic cheating (e.g. if you copy someone else's work, etc.), your work will receive grade 0 and the program supervisor will be notified. If you feel that you are stuck with the homeowork, ask for instructor's advices and hints.
Late penalties: in case of late submission, your grade will be multiplied by exp(-t / 86400), where t is the number of seconds since the due date. For example, if you delay the submission by one day, your grade will be multiplied by exp(-1)=0.3678794412.
Extensions: you can ask for up to two extensions of homework due dates during the course. Each extension is one week. Extensions due to valid excuses (i.e. illness) do not count.
Homework #1
Complete the following chapters in DataCamp Introduction to R course:
Due date: 2021-01-31 23:00 MSK. Late penalties are applied to each chapter independently.
Homework #2
- Homework file
- Please, put your solutions in the related Rmd file.
- Then upload it here
Due date: 2021-02-14 23:00 MSK.
Homework #3
- Homework file
- Please, put your solutions in the related Rmd file.
- Then upload it here
Due date: 2021-03-16 23:00 MSK
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).
Final project
- Final projects description
- Project proposals: please, upload here.
Online course
We will use some parts of DataCamp online course Introduction to R. (Will be made available free for the students.)
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. link