Face-to-face , first term, 30 hours of theory and 15 hours of exercises.

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The course is taught in French.

The course and practical exercises aim to lead students to acquire skills in preparing and managing data, essential skills for any statistical analysis.

The students will be capable of thinking through the organisation and the manipulation of a set of data through the use of computers. This skill will be essential to students insofar as they will either need to carry out statistical work themselves or delegate it in an intelligent manner. The emphasis is placed - during the course, the practical exercises and the assessment - on the students' development of an analytical capacity, far more than it is on their acquiring a technical-linguistic skill. Student will be able to organise data based on their knowledge of theoretical concepts relating to the databases and to the existence constraints of the variables, to their strong command of the concept of missing data, etc. Students will be able to manipulate data by calling upon their skills in analytical and programming concepts, adapted to the specific framework of statistical processing software. Thus, they will be able to combine several data files, to create discrete data starting from continuous data, to count the number of occurrences of a phenomenon within a set of data, to create new data (indices) by combining various information, etc. They will be able to carry out preliminary sample rectification operations, to select a sub-sample, etc

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After a brief introduction, the course covers, through the concepts related to the analysis and the construction of databases, the concepts of individuals, attributes, data, variables, values, etc. The introduction to analyses and programming follows, along with the concept of algorithms, of the analysis of a problem, of the step-by-step description of its solution, of the formalisation of this process. Within this framework, the concepts of function and procedure are also covered.
The largest part of the course is an introduction to analyses and programming in a programming environment typical of the social sciences: a statistics software - in this case, SPSS. After a description of its syntax, the following fields are successively discussed:
- Transformation and assignment statements,
- Conditional structure,
- Repetitive structure,
- Procedures,
- Selection, sorting and weighting of individuals,
- Data files and their reading/writing,
- Variables and their documentation.

The course begins with a theoretical lecture, goes on to clarify examples and concludes with a lesson centred primarily on collective problem solving.

Practical exercises put the students in problem-solving situations. A problem statement is distributed at the beginning of the class session; the assistant is available to help students during their efforts to solve the problem. It is exclusively up to the students to take any initiative and to conduct their work.

There is no collective discussion or explanation of the (rather, of a) solution within the framework of the practical exercise class sessions. Such a discussion or lecture will perhaps take place at the end of the term should there be sufficient time to do so: in that case, each student will benefit from the experiments, attempts, failures, errors and solutions experienced by the entire class.

The structure of the course is reviewed during the class sessions by means of transparencies on which the lectures are based.

Formative assessment:
During the course and the practical exercise sessions, exercises are proposed to the students who can thus evaluate their own progress.

Certificate-based assessment:
Formal assessment takes place during a 4-hour written examination, which consists of a theoretical part counting for 25% of the grade and a practical part counting for the remaining 75%.

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The course notes written by the lecturer contain a structured and concise presentation of the subject matter, a syntactic summary and sample examination questions. Included in the notes are a questionnaire and the data dictionary. Lastly, a data file is used as support material for the practical exercises.