STATISTICS FOR LANGUAGE SCIENCES

This is an integrative course of the second-level degree course in Language Sciences. It contributes to the development of in-depth knowledge of quantitative methods and their application in the field of Language Sciences, as well as to the strengthening of the ability to analyse language data in a methodologically correct manner with reference to the objectives and the theoretical framework of reference.

- General outcome
The student will be introduced to the basic elements of statistics, as a tool for describing and understanding reality expressed in number form. The relation between the
information enclosed in numbers and the words employed to explain it and make it comprehensible will be explored. The student will guided on the path going from the basic
definitions and concepts behind the need for knowledge, through data collection and analysis, to the reading and understanding of information expressed in statistical form.
The course, therefore, aims to provide the tools allowing the student to proceed autonomously in the use of statistics, both to understand and correctly interpret results provided by
others and to produce new results when conducting 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 in general, the tools to understand the numerical synthesis of reality. At the same time, the ability to understand better ways to formulate research questions and to carefully
define the phenomenon under investigation so as to be able to use the quantitative statistical instruments that are available appropriately will be developed.

- 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 statistical data collection; 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 to properly present the results.

- Making judgements
The student will develop the ability to elaborate complex information through the scientific approaches of the discipline; to discuss and reflect on the statistical methodology and on its
results; to make autonomous and informed judgements and evaluations about the validity and feasibility of research proposals and research results (instruments, modes of analysis,
and produced indicators).

- Communication skills
The student will master the basic specialized 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.

- Lifelong learning
The student will acquire the learning skills and strategies that will allow them to further the knowledge and competence or to further explore the main thematic areas of the discipline
autonomously.

None.
The course is designed for students with the standard mathematical and statistical knowledge and competencies acquired at the high school level.

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, tests and linear regression.

- Main text:
Agresti, A., Franklin, C. A., Klingenberg, B. (2017) Statistics : The art of science of learning from data. Pearson, 4th ed.

- Additional material:
Additional suggested reading and materials made available on the Moodle platform.

The exam consists of a multiple choice test, some exercises and some open questions.
The exam will last 120 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 judgements: 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.

Students may accumulate up to 8 extra points, to be added to the final exam mark, through the development of 2 projects to be developed in pairs, and via Moodle quizzes taking place every two weeks on pre-established dates. Any extra points earned will remain valid for all 4 exams of the academic year, but are lost and no longer valid for future exams if the student renounces a passing grade.

Traditional. The students will be required to participate actively in the discussion and solution of exercises.

English

written