A detailed schedule of sessions will be published on the virtual campus before the start date of the course.

Two types of activities will be held in the classroom:

• Theoretical sessions for the class group. The concepts and content of the course will be presented using PowerPoint presentations. The final 10 minutes of each session will be reserved for a test on the specific content of the session. This test will serve as an attendance check and also to assess student adherence to the course.
• Practical sessions in computerized classrooms. Students will work with the free software RStudio, which is installed in all social science computerized classrooms (students are encouraged to also have the software installed on their laptops). Students will be provided with a dossier for each session through the virtual campus to facilitate follow-up. As with the theoretical sessions, the final 10 minutes of each session will be reserved for a test on the specific content of the session. This test will serve as an attendance check, but also to assess student progress in the course.

Outside the classroom

• Two types of exercises must be completed weekly: one for the theoretical session and one for the practical session. These exercises must be submitted via the virtual campus before the next session:
• Theoretical session. This will consist of problems involving applied statistics in criminology. The exercises will be completed at the beginning of the next session.
• Practical session. Work exercises with RStudio software to help students gain self-reliance in its use. The solutions to these exercises will be posted on the virtual campus for self-correction.
• Creation of a poster applying the course concepts to criminological research. Its completion will be supervised during tutorial hours. In order to closely monitor the work, lecturers of the course may make these tutorials mandatory.

1. Continuous assessment activities

A) Classroom problems and practice with the analysis programme (5%):

• At the end of each theory session and each practical session, a set of exercises and problems will be posed and must be handed in before the next session.
• No practice will be accepted beyond the deadlines, except in cases of force majeure. The practices not submitted are not recoverable and have a value equal to 0.
• The practical exercises will not be directly assessed, but the solutions will be posted on the virtual campus with detailed explanations to facilitate self-correction.

B) Follow-up of theoretical and practical sessions (10%):

• In each session, a short test will be given with questions on the contents developed during the class or on reading materials defined for the session.
• This activity cannot be made up, so that unexcused absences will have a mark of 0. If the absence has been justified, the activity will not be taken into account in the calculation of the average.

C) Practical test on data processing with the analysis software (30%):

• This practical test will assess the skills acquired in data processing and the manipulation of variables and files using the software.
• In order to pass the course, a minimum mark of 4 is required. Otherwise, it will be necessary to take the final exam.

D) Theoretical-practical test on concepts specific to univariate descriptive statistics (30%):

• This theoretical and practical test will combine questions on the main concepts of univariate descriptive statistics with their application in problem-solving and the use of statistical software.
• In order to pass the course, a minimum mark of 4 is required. Otherwise, it will be necessary to take the final exam.

E) Analysis work (25%):

• A paper will contain: (1) aspects of univariate inference and (2) treatment of variables and bivariate analysis.
• Guidelines for the development of the work will be set out at the beginning of this part of the course.
• The work will be carried out in groups. The number of members of the groups will be specified at a later stage.
• In order to pass the course, a minimum mark of 4 is required. Otherwise, it will be necessary to take the final exam.
• A paper that contains serious formatting problems (e.g. spelling mistakes or poor bibliographical citations) will receive a mark of 3, regardless of its content.

2. Conditions for taking part in the assessment

• In accordance with the criteria of the Degree, attendance is compulsory at 100% unless there is an excused absence. Justified absences are considered to be those due to force majeure. Absence due to academic reasons must be accepted in advance by the teaching staff. It is necessary to meet a minimum of 80% attendance to be able to pass the evaluation.
• Punctuality in class is required. Delays of more than 5 minutes not justified by force majeure will count as a failure to attend.

3. Final test within the framework of continuous assessment

Students who take part in at least 80% of the activities (sections A and Bof the continuous assessment), but who get less than a 4 in any of the three continuous assessment activities (C, D or E) must take a final exam with the content of the whole course.

Students who take part in less than 80% of the activities (sections A and B of continuous assessment) are not entitled to this final exam.

4. Non-evaluable rating

Students will be assessed as long as they have completed a set of activities whose weight is equivalent to a minimum of 2/3 of the total grade of the subject. If the value of the activities carried out does not reach this threshold, the teacher of the subject can consider the student as not evaluable.

5. Fraudulent conduct

If any form of copying or plagiarism is detected in any of the assessment activities, the activity will be marked 0 and the right to re-assessment will be lost. Human or technological help in writing the results of a work will

be considered plagiarism.

Cell phones will be used to evaluate the monitoring of the theory and practice sessions (section B). If it is detected that a person answers the questionnaires without being present in the classroom, he/she will have a mark of 0 in the overall evaluation of the follow-up of the sessions.

6. Behaviour during the course

The UAB is home to a diverse and inclusive environment for students, teaching staff and the university community as a whole. In this class a zero-tolerance policy will be applied towards any attitude of discrimination or harassment based on age, ancestry, functional diversity, gender identity, national origin, religious belief or sexual orientation, as well as towards any attitude that generates a hostile environment for any of the aforementioned reasons. Such attitudes will be reported in accordance with the university's harassment prevention policy.

7. Single assessment

Students who, within the deadlines established by the faculty, take advantage of a single assessment, do not have the obligation to carry out the exercises set out in the classroom, or to deliver the RStudio practices, or to keep a daily monitoring of the course.

In this case, the evaluation will be based on a final exam on the date established by the faculty. This exam will assess the ability to work with the appropriate software, the knowledge of univariate and bivariate descriptive statistics, as well as the basic fundamentals of statistical sampling.

Students who do not pass the test will be will have the right to a re-evaluation. In both exams a grade of 5 is necessary to pass the subject.

For this course, the use of Artificial Intelligence (AI) technologies is permitted exclusively for support tasks, such as bibliographic or information searches and text proofreading. Students must clearly identify which parts of their work were generated using this technology, specify the tools used, and include a critical reflection on how these tools influenced both the process and the final outcome of the assignment. Failure to disclose the use of AI in this assessed activity will be considered a breach of academic integrity and may result in a partial or total reduction of the assignment grade, or more severe disciplinary sanctions in serious cases.