LOT Winter School 2019

RM1 - Statistics for Linguists in R

Susanne Brouwer

Contact





Title of the course: Statistics for Linguists in R
Teacher: Susanne Brouwer

Contact
Address: Radboud University Nijmegen Dutch Language and Culture department Erasmusplein 1, 6525 HT, Nijmegen
Email address: s.brouwer@let.ru.nl
website teacher: https://smbrouwer.wordpress.com/

Course info Level: RM1 (First year Research Master Linguistics)

Course description:
This course offers an overview of several statistical concepts and techniques. Students taking this course will learn to perform basic and more advanced statistical tests on empirical data, gathered by means of linguistic experiments or surveys.

Topics discussed in this course are: Descriptive statistics (e.g. measurement level; frequencies; mean, median, mode, standard deviation and variance; plotting) and inferential statistics (e.g. Central Limit Theorem; hypothesis testing; testing assumptions; p-value; independent and paired-samples t-tests, ANOVA, correlation, mixed-effects regression modeling).

The software used in this course is R, which is freely available. You should bring your laptop to class with the most recent version of R (https://cran.r-project.org/bin/windows/base/) and RStudio (https://www.rstudio.com/products/rstudio/download/) installed. Each class starts with a lecture and ends with a lab session (except the first class).

Day-to-day program
Monday: Introduction to Statistics 
Tuesday: Introduction to R and exploring your data 
Wednesday: Basic statistical tests I 
Thursday: Basic statistical tests II 
Friday: Introduction to mixed effects regression modeling

Reading list (not obligatory)
Baayen, R. H. (2008). Analyzing linguistic data: A practical introduction to statistics using R. Cambridge University Press. http://www.sfs.uni-tuebingen.de/~hbaayen/publicati...
Levshina, N. (2015). How to do linguistics with R: Data exploration and statistical analysis. John Benjamins Publishing Company. https://benjamins.com/catalog/z.195

Course readings (obligatory):

Lecture 1: Levshina (2015): Chapter 1 
Lecture 2: Levshina (2015): Chapters 2, 3, and 4 
Lecture 3: Levshina (2015): Chapters 5 (t-test), 8 (ANOVA) 
Lecture 4: Levshina (2015): Chapters 6 and 7 
Lecture 5: Baayen (2008): Chapter 7

Assignments
Assignments become available during the lectures