Types of activities

The course is structured around directed, supervised, and autonomous activities where students will be able to acquire the course content with the in-person support of the instructor at various levels.

- Managed activities: include theoretical sessions and the development of practical exercises, led by the instructor.

- Supervised activities: in-person supervision of practical sessions, where students will independently, but under supervision, develop various exercises.

- Autonomous activities: study of theoretical content and resolution of practical exercises.

Innovative teaching methodologies

Participatory and interactive dynamics are used during sessions to reinforce the content as it is taught. Throughout the course, students participate in the collaborative construction of a database based on contextual variables, which is later used to apply statistical analysis techniques covered in class.

This subject does not incorporate single assessment.

Assessed activities:

- An objective knowledge test conducted through two written exams. Weighting factor: 50% of the final grade. Each exam represents 25% of the final grade.

- Partial LAB exercises (submission of more comprehensive practical dossiers reinforcing the course content). Weighting factor: 30% of the final grade.

- Regular LAB exercises (submission of practical work developed in the classroom). Weighting factor: 10% of the final grade.

- Participation and attendance. Both items will be measured through different activities, such as interactive activities like Kahoot. Weighting factor: 10% of the final grade.

Evaluation criteria:

- The final grade of the course will be the weighted average of all activities subject to evaluation.

- The final grade of the written test will be the average of the two partial exams.

- It is necessary to obtain a minimum of 4 in the objective test and an average course grade of 5 to pass the course.

- Activities not submitted or completed on the specified date will be marked as \"Not presented\" and graded with a zero.

- Students who have only completed 1/3 of the evaluable activities will be graded as \"Not evaluable.\"

- The instructor reserves the right to include oral assessments, either general or specific, in order to verify the authorship and understanding of the contents of any assessable activity. These assessments will not alter the weighting of the corresponding activities, but they may affect the final grade if serious inconsistencies are detected.

- If a student commits any form of academic misconduct (such as plagiarism or the use of unauthorized tools in any assessment activity, including written examinations and practical assignments) that may affect the assessment outcome, that assessment will be awarded a grade of zero. If the misconduct is considered sufficiently serious, the student may instead receive a grade of zero for the entire course, irrespective of any disciplinary proceedings that may also be initiated..

Review procedure:

All evaluated activities will be subject to grade review. Students will be informed via the Moodle classroom of the corresponding date in each case.

Resit eximanation:

The resit eximanation will be done through a written test.

The grade of one of the partial practical exercises can be recovered, only if it has been submitted.

Regular practical exercises cannot be recovered, as they are considered exercises that track the course progress.

Use of Artificial Intelligence:

For this course, the use of artificial intelligence (AI) technologies is permitted exclusively as support for working with material covered in class or for solving statistical formulations in practical exercises. Under no circumstances may these tools be used to interpret results or analyze patterns derived from data. Students must clearly identify which parts were generated using AI tools, specify the tools used, and include a critical reflection on how these influenced the process and final outcome of the activity. Lack of transparency regarding the use of AI in an assessed activity will be considered academic dishonesty and may result in partial or total loss of the grade for the activity, or more serious penalties in severe cases.

Gender criteria: Data analysis and problem-solving will take into account, where applicable, social and gender differences. Students are encouraged to use non-sexist language. The UAB guidelines (see "Ten tips for non-sexist language use") can be helpful.