STATISTICS FOR LANGUAGE SCIENCES

The course "Statistics for language sciences" is one of the integrated activities of the Second Degree in Linguistics and contributes to the development of in-depth knowledge of quantitative methods and their application in the field of Linguistics, as well as to the strengthening of the ability to analyse linguistic data in a methodologically correct way, with reference to the objectives and the theoretical reference framework.

The student will be introduced to the basic elements of statistics, seen as a tool for describing and understanding reality expressed in number form. The relation between the information enclosed in the numbers and the words deployed to explain it and make it comprehensible will be explored. The student will be accompanied all the way from the definition of the need for knowledge, data collection, and analysis to the reading and understanding of information expressed in statistical form.
The course, therefore, aims to provide the student with the tools that will allow them to move autonomously when managing basic statistics, whether having to understand and use these in a correct manner when they are provided by others or having to produce them autonomously when conducting their own empirical research.

Knowledge and understanding
The student will acquire in-depth knowledge concerning the main concepts and foundations of statistics, research methods and data collection, statistical indicators and measures, and, more generally, the tools to understand the numerical synthesis of reality. At the same time, s/he will become familiar with, and increase their ability to understand, how to formulate research questions and to carefully define the phenomenon under investigation to be able to use the quantitative statistical instruments that are available appropriately.

Applying knowledge and comprehension
The student will be able to: reflect on, and take decisions about, the main methodological issues relative to statistical data; know the main sources and modes of data search; read and understand statistical data extracting from it correct information and avoiding errors of interpretation; translate the areas of interest and the knowledge objectives into research questions and hypotheses; translate simple concepts into simple indicators and complex concepts into sets of indicators; plan the different stages of the collection of statistical data; identify the different modes of data collection in the light of objectives; design a simple questionnaire; carry out descriptive quantitative analysis; use the main inferential statistical instruments; write up a report that illustrates the results.

Making judgements
The student will show s/he can elaborate complex information through the scientific approaches of the discipline; s/he will be able to discuss and reflect on the statistical methodology and on its results; s/he will be able to make autonomous and informed judgments and evaluations about the validity and feasibility of research proposals and research results (instruments, modes of analysis, indicators produced).

Communication skills
The student will master the basic specialistic lexis of statistics in order to communicate clearly with specialists and non-specialists and to discuss methods and results of analyses with clarity and precision.

Learning skills
The student will be able to demonstrate that they have acquired learning abilities and strategies that enable them to continue and/or independently deepen the main topics of the discipline.

Lifelong learning
The student will acquire the learning skills and strategies that will allow them to continue to further their knowledge and competence and/or to further explore the main thematic areas of the discipline on their own.

The course is designed for students with basic mathematical knowledge and competencies acquired in high school.

The course aims to provide the students with some basic statistical tools. The main topics that will be treated are: methodology of data search and collection, experimental design, descriptive and inferential statistics, with a particular focus on frequency distribution, central tendency, variability, estimation, and hypothesis testing.

- Agresti, A., Franklin, C., 2016, Statistica: l'arte e la scienza d'imparare dai dati. Ediz. mylab. Online expansion, Pearson
- Spiegelhalter, D. (2019). The art of statistics: Learning from data. Penguin UK.
The lecturer will use her own material and will guide the students in searching the web for useful materials.

The exam consists of a multiple-choice test, some exercises, and some open questions.
The exam will last about 90 minutes.
- Part one: ten (10) multiple choice questions;
- Part two: two (2) practical exercises, e.g., a statistical calculation;
- Part tree: two (2) open questions.

The multiple choice questions and the exercises allow for the assessment of the acquisition of the basic concepts; the open questions assess critical thought, critical analysis, and scientific writing.

More in detail:
Knowledge and comprehension: assessed through multiple-choice questions
Applying knowledge and comprehension: assessed through multiple choice questions and practical exercises
Making judgments: assessed through specific multiple-choice questions
Communicative skills: assessed through the open questions
Lifelong learning: assessed through the open questions
The open questions assess critical thought as well as the mastery of the content.

In addition, there will be an ongoing activity (thematic quizzes) for attending students and a project work for non-attending students that will help to acquire a bonus of up to 3 points in the exam. Details will be provided on Moodle and during the course.

written

The lecturer has a duty to ensure that the rules regarding the authenticity and originality of exam tests and papers are respected. Therefore, if there is suspicion of irregular conduct, an additional assessment may be conducted, which could differ from the original exam description.

Regarding the grading scale (criteria for assigning grades):
A. Scores in the 18-22 range will be assigned in the presence of:
Sufficient knowledge and understanding of the course program;
Limited ability to apply knowledge and formulate independent judgments;
Sufficient ability to communicate using the appropriate technical language of the subject.
B. Scores in the 23-26 range will be assigned in the presence of:
Fair knowledge and understanding of the course program;
Fair ability to apply knowledge and formulate independent judgments;
Fair ability to communicate using the appropriate technical language of the subject.
C. Scores in the 27-30 range will be assigned in the presence of:
Good to excellent knowledge and understanding of the course program;
Good to excellent ability to apply knowledge and formulate independent judgments;
Good to excellent ability to communicate using the appropriate technical language of the subject.
D. Honors will be awarded in the presence of outstanding knowledge and applied understanding of the program, excellent judgment skills, and exceptional communication abilities.

Traditional. The students will be required to participate actively in the discussion and carry out the exercises.