The course is connected to the following study programs

Recommended prerequisites

Students must have completed a Master´s degree in a relevant discipline.

Course contents

The aim of this course is to provide students with basic knowledge of statistical analysis and a specific software package R. The course introduces students to using R statistical analyses in linguistics. The course will deal with all aspects of using this software ¿ from getting your data into R Studio, perform different statistical analyses like chi-square, t-tests, correlation, regression, to graphing and plotting to understand and interpret data. The course will furthermore provide an introduction to mixed models and multiple regression. The first day of the course is intended as an introduction to statistical methods for students with little or no background in this area.

Day 1: 12-17.00 Introduction to statistical analysis

This first day is intended as additional preparation for those with little or no experience using statistical analysis.

Day 2: 9.30-17.00 Introduction to R

Getting your data into R Studio. Manipulating data (data wrangling). Data exploration and tidying.

Day 3: 9.30-17.00 Basic statistics in R Studio

This will be tailored to the kind of analyses that people are interested in e.g., chi-square, t-tests, correlation, regression. Graphing and plotting in R.

Day 4: 9.30-17.00
More advanced analyses

Graphing and plotting in R to understand your data. ANOVA in R / multiple regression / introduction to mixed models and/or Independent practice and assessment assignment

Learning outcomes

After completing the course, the students will have basic knowledge of R as an integrated suite of software facilities for data manipulation, calculation and graphical display. Furthermore, the students will have acquired practical skills in using this tool for doing statistical analyses in linguistics, as the course is specifically targeted on hands-on experience in the use of this tool for specific purposes on the student´s own linguistic data sets.

Examination requirements

  • Complete the required preparation (online courses, approx. 4-6 hours)

  • Participate in all lectures and practical sessions

Offered as Single Standing Module

Yes. Subject to availability or capacity.

Assessment methods and criteria

Complete the assessed course assignment

Last updated from FS (Common Student System) July 1, 2024 1:39:42 AM