Academic year
2022/2023 Syllabus of previous years
Official course title
Course code
LM5490 (AF:381861 AR:208342)
On campus classes
ECTS credits
Class 1
Degree level
Master's Degree Programme (DM270)
Educational sector code
2nd Semester
Course year
Go to Moodle page
As part of the "LANGUAGE AND COGNITION", "THEORETICAL LINGUISTICS" and of the "LINGUISTICS FOR DEAFNESS AND LANGUAGE DISORDERS" curricula of the Master's Degree in Language Sciences, this course provides an introduction to the basic techniques for the collection, visualization and analysis of linguistic and psycholinguistic data.

The main goals of this course are:

- to familiarize with the basic methodological tools for the visualization,exploration and statistical analysis of linguistic data
- to strengthen the student's ability to reflect on the properties of language
- to stimulate critical thinking and the ability to think out of the box

1. Knowledge and understanding
- familiarity with the basic terminology and understanding of the relevant scientific literature
- knowledge of the mathematical foundations of the fundamental statistical measures
- familiarity with the best practices for the creation and manipulation of datasets of linguistic data
- familiarity with the best approaches to the visualization and analysis of linguistic data
- familiarity with the statistical analysis softwares JASP and jamovi

2. Applying knowledge and understanding
- ability to set up a quantitative study
- knowledge of the features and limitations of the most widely used statistical measure, so as to be able to pick the most appropriate solution for a given linguistic research issue
- ability to propose insightful ideas

3. Making judgements
- awareness of the technical and deontological issues connected to the statistical analysis of experimental data
- critically evaluate quantitative analyses in a range of linguistic sub-fields
- ability to compare competing hypotheses

4. Communication skills
- ability to interact with the other students and the instructor during lab sessions
- mastering of statistical terms and concepts

5. Learning skills
- ability to learn advanced statistical techniques
- ability to learn to use other statistical softwares (e.g. SPSS) or software environments (e.g. R, Python, Matlab)
Basic mathematics skills

Basic computer skills
- introduction to statistics
- introduction to research design
- graphical representation of data
- descriptive statistics
- probability and distributions
- hypothesis testing
- comparing two means
- correlation and linear regression
- analysis of variance
Course Textbooks:

- Loerts, H., W. Lowie & B. Seton (2020) Essential statistics for applied linguistics: Using R or JASP. Red Globe Press.
- Navarro, D.J., D.R. Foxcroft & T.J. Faulkenberry (2019). Learning Statistics with JASP:
A Tutorial for Psychology Students and Other Beginners. Freely available online at:

Supplementary reading material published on the university e-learning platform
A 120 minutes long written exam composed of 3 practical exercises and 18 closed-ended questions:
- the practical exercises focus on the dataset manipulation and statistical analysis techniques discussed in class
- the closed-ended questions assess the acquisition of the fundamental concepts of experimental design and statistical analysis discussed in class

More in detail:
Knowledge and comprehension: assessed through closed-ended questions
Applying knowledge and comprehension: assessed through closed-ended questions and practical exercises
Making judgements: assessed through specific multiple choice questions and practical exercises
Communicative skills: assessed through practical exercises
Lifelong learning: assessed through practical exercises
Lecture-style presentations and lab sessions. Students are required to bring a laptop to every course meeting.
Definitive programme.
Last update of the programme: 06/07/2022