STATISTICS FOR LANGUAGE SCIENCES 1

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 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 statistical analysis softwares

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

Basic mathematical 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

Course Textbooks:

Spiegelhalter, D. (2019). The art of statistics: Learning from data. Penguin UK.

Supplementary reading material published on the university e-learning platform

There are two methods of assessment for the course, at the student's choice.

The first method involves participating in and developing a group project, agreed upon with the instructor and also developed in class during the course. The exam will consist of presenting the results of the project, a summary of which (report) must be submitted 24 hours before the discussion. The exam will be passed if the project results are deemed sufficient, and the quality of the presentation will also affect the grade.

The second method involves an oral discussion on the recommended texts and the materials available on the platform. The student must demonstrate an understanding of the main concepts of the subject and the ability to argue the operational consequences of their application. Those interested may (optionally) present a critical analysis of a research study (article, report, or other) previously agreed upon with the instructor during the oral exam.

Lecture-style presentations and lab sessions. Students are required to bring a laptop to every course meeting.

Italian

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