Degree | Type | Year |
---|---|---|
Psychology | OB | 2 |
You can view this information at the end of this document.
To take advantage of the course "Data Analysis" it is necessary to have satisfactorily completed the subject “Research Methods, Designs and Techniques" ("MEDITI").
"Data Analysis" is the second methodological subject of the Psychology syllabus and belongs to the subject "Research Methods and Psychometrics". It is taught in the first semester of the second year and represents the natural continuation of the subject "Research Methods, Designs and Techniques", imparted in the first year of the degree. The course collects some methodological competences transferred in the subject "Statistics" and incorporates and develops new ones, with an aim for the students to broaden their skills base, an aspect that will allow them to complete the ensuing methodological subjects.
The general formative objectives of the course are:
At the end of the course the student must be able to:
Title | Hours | ECTS | Learning Outcomes |
---|---|---|---|
Type: Directed | |||
Practical classes | 18 | 0.72 | 4, 3, 1, 2 |
Theoretical classes | 27 | 1.08 | 4, 3, 1, 2 |
Type: Supervised | |||
Review of problems | 10 | 0.4 | 4, 3, 1, 2 |
Tutorials | 13 | 0.52 | 4, 3, 1, 2 |
Type: Autonomous | |||
Cooperative learning | 33 | 1.32 | 4, 3, 1, 2 |
Reading scripts | 45 | 1.8 | 4, 3, 1, 2 |
The course "Data Analysis" implies the completion of 6 ECTS credits that represent a total of 150 hours for the student. Of this total, 45 hours will be dedicated to directed formative activities based on theoretical lectures and practical classes consisting in problem solving activities. A total of 18 hours will be dedicated to the revision of problems in seminar rooms and personal tutorials with the teachers. Different autonomous activities will be organized, including 72 hours of student dedication based on the reading of documents recommended by the professors and cooperative learning (group resolution of cases and problem-situations). The remaining 9 hours comprising the course will be dedicated to evaluation activities.
In summary: (1) teaching methodology: lectures, supervised practices, problem-based learning, and case exposition/discussion, and (2) training activities: case studies and technical-scientific lectures.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Title | Weighting | Hours | ECTS | Learning Outcomes |
---|---|---|---|---|
Distinction-grade | Qualitative assessment | 0 | 0 | 4, 3, 1, 2 |
EV1 Instrumental assessment units 1 to 4 (group authorship) | 5% | 0 | 0 | 4, 3, 1, 2 |
EV2 Theoretical and instrumental assessment, units 1 to 4 (individual authorship) | 45% | 2 | 0.08 | 4, 3, 1, 2 |
EV3 Instrumental assessment, units 5 to 8 (group authorship) | 5% | 0 | 0 | 4, 3, 1, 2 |
EV4 Theoretical and instrumental assessment, units 5 to 8 (individual autorship) | 45% | 2 | 0.08 | 4, 3, 1, 2 |
Continuous assessment: The marking of the students is based on a continuous assessment process that allows the evaluation of the degree to which they acquire the competences trained in the course. It is based on the performance and delivery of a series of learning evidence associated to different assessment modalities at different times along the semester. This format provides students and teachers with immediate feedback on the level of competencies acquired throughout the course and the degree of improvement in academic performance.
In order to complete the course, students must prove satisfactory performance in two compulsory tests (EV2 and EV4) of individual authorship and two instrumental or practical evaluation tests (EV1 and EV3) of group authorship.
The EV2 and EV4 tests are carried out in person at the place and date set by the Faculty in the first and second evaluation period respectively. These tests evaluate, by means of multiple-choice tests consisting of 40-45 questions, all the contents of the subject considering both the theoretical and instrumental aspects. EV2 evaluates topics 1 to 4 of the syllabus and EV4 evaluates the remaining topics (5 to 8).
The instrumental or practical evidence, EV1 and EV3, will be carried out approximately one or two weeks before EV2 and EV4, respectively. EV1 and EV3 consist of the exposition and subsequent resolution of a problem-situation that each work team, the members of which will be chosen by the teachers at the beginning of the course within each group of practices, will have been working on during the course. In this sense, EV1 will evaluate the practical aspects of topics 1 to 4 and EV3 those corresponding to topics 5 to 8. In order to be able to present each of these evidence, the work team will need to have delivered the list of exercises-problems called "complementary problems" solved, available in the practice material of the subject.
To determine the final grade of the course (FG) the weighted contributions of the respective learning evidence will be considered, so that EV1 contributes 5% to the final grade of the course, EV2 45%, EV3 5%, and EV4 45%. Therefore: FG=EV1(0.10)+EV2(0.35)+EV3(0.10)+EV4(0.45). The students who have completed the learning evidence with a weight equal to or higher than 4 points (40%) cannot be recorded as "non-assessable". Therefore, in order to pass the course following the continuous assessment, the following criteria must be met:
The students with a final grade higher or equal to 5 points will not be allowed to take the reparatory exam in order to increase the final grade obtained during the continuous assessment. The decision to re-sit one or both evidences (EV2 and/or EV4) is up to the student. The reparatory exam(s) of EV2 and EV4 will have the same format and contents as the original tests. The grade(s) obtained in the reparatory exam(s) will replace the grade(s) obtained initially in the previous evaluations carried out during the course (EV2 and/or EV4).
The students who have obtained a final grade equal to or higher than 9 points will be eligible for the qualification "With high Honors". These students will have to take a complementary evaluation test, in person and in oral format. This test will be carried out at the same time as the reparatory exam. The conditions, characteristics and dynamics of the test to opt for the qualification of "With high Honors" will be specified to the people involved days before the test.
Single evaluation: the students who consider it appropriate may opt for the single evaluation modality. This type of evaluation implies that on a single evaluation date all the evidence/learning activities will be carried out, with the same considerations, weightings and requirement level as those corresponding to the continuous assessment. The students enrolled in this type of assessment can attend classes and some of the sessions may even be compulsory. The single evaluation test will take place on the same date as the EV4 evaluation and, if necessary, the students may opt for a reparatory exam on the date set by the Faculty and the same recovery process as that of the continuous assessment will be applied. The duration of the single evaluation test is estimated between five and six hours. It should be noted that EV1 and EV3 are not recoverable.
Therefore, and in summary:
Synthesis test: this subject does not include a synthesis test as an assessment method.
You can consult the following links:
After each assessment activity, teachers will provide feedback on the performance observed in the corresponding learning test. The following table indicates the type of feedback and the approximate week in which it will be given.
Return type |
EV and type |
Week |
Written |
EV3 i EV4 |
End of week S15 (EV3) and end of week 19 (EV4) |
In the classroom |
EV1 i EV2 |
Weeks S8 and S10 respectively |
The delivery of the translation of the in-person assessment tests will be carried out if the requirements established in article 263 are met and the request is made electronically in week 4 (E-Form) (more information onthe Faculty website).
In this subject, the use of Artificial Intelligence (AI) technologies is allowed as an integral part of the development of the work, provided that the result reflects a significant contribution by the student to the analysis and personal reflection. The student must clearly identify which parts have been generated with this technology, specify the tools used and include a critical reflection on how these have influenced the process and the result of the activity. Thelack of transparency in the use of AI will be considered a lack of academic honesty and may lead to a penalty in the grade of the activity, or greater sanctions in serious cases. In short, it is about using AI technologies responsibly and keeping clear at all times that, if used correctly, it is a very good tool.
Reference manuals:
Pardo, A., Ruiz, M.A., i San Martín, R. (2009). Análisis de datos (I) en ciencias sociales y de la salud. (2ª ed.). Madrid: Editorial Síntesis.
Further reading:
Cumming, G., i Calin-Jageman, R. (2024). Introduction to the new statistics: estimation, open science, and beyond (2ª ed.). New York: Routledge-Taylor & Francis.
Ellis, P.D. (2010). The essential guide to effect sizes. Cambridge: Cambridge University Press.
Kline, R.B. (2013). Beyond Significance Testing: Statistics Reform in the Behavioral Sciences. Washington, DC: American Psychological Association.
Kline, R.B. (2020). Becoming a behavioral science researcher (2ª ed.). London: The Guilford Press.
Pardo, A., Ruiz, M.A., i San Martín, R. (2010). Análisis de datos (II) en ciencias sociales y de la salud. (2ª ed.). Madrid: Editorial Síntesis.
Peña, D. (2001). Fundamentos de estadística. Madrid: Alianza Editorial.
Solanas, A., Salafranca, Ll., Fauquet, J., i Nuñez, M.I. (2005). Estadística Descriptiva en Ciencias del Comportamiento. Madrid: Thomson.
The basic program used in the course is the statistical program STATA (V18). This program is the basic tool with which the various studies/problems posed by the course will be carried out. Complementarily, the student will have the possibility to study/deepen in two statistical programs of free distribution. These programs are the JASP system (https://jasp- stats.org/) and the JAMOVI program (https://www.jamovi.org/).
Please note that this information is provisional until 30 November 2025. You can check it through this link. To consult the language you will need to enter the CODE of the subject.
Name | Group | Language | Semester | Turn |
---|---|---|---|---|
(PAUL) Classroom practices | 11 | Catalan/Spanish | first semester | morning-mixed |
(PAUL) Classroom practices | 12 | Catalan | first semester | morning-mixed |
(PAUL) Classroom practices | 21 | Spanish | first semester | morning-mixed |
(PAUL) Classroom practices | 22 | Spanish | first semester | morning-mixed |
(PAUL) Classroom practices | 31 | Catalan/Spanish | first semester | morning-mixed |
(PAUL) Classroom practices | 32 | Catalan/Spanish | first semester | morning-mixed |
(PAUL) Classroom practices | 41 | Catalan | first semester | morning-mixed |
(PAUL) Classroom practices | 42 | Catalan | first semester | morning-mixed |
(PAUL) Classroom practices | 51 | Catalan | first semester | morning-mixed |
(PAUL) Classroom practices | 52 | Catalan/Spanish | first semester | morning-mixed |
(TE) Theory | 1 | Catalan/Spanish | first semester | morning-mixed |
(TE) Theory | 2 | Catalan/Spanish | first semester | morning-mixed |
(TE) Theory | 3 | Catalan | first semester | morning-mixed |
(TE) Theory | 4 | Catalan | first semester | morning-mixed |
(TE) Theory | 5 | Catalan/Spanish | first semester | morning-mixed |