| Session | Start date and time | End date and time | Aula | Location |
|---|---|---|---|---|
| 1 | 01/07/2025 09:00 | 01/07/2025 14:00 | Aula PB SFPIE | Lifelong Learning and Educational Innovation Service (SFPIE) |
| 2 | 03/07/2025 09:00 | 03/07/2025 14:00 | Aula PB SFPIE | Lifelong Learning and Educational Innovation Service (SFPIE) |
| 3 | 08/07/2025 09:00 | 08/07/2025 14:00 | Aula PB SFPIE | Lifelong Learning and Educational Innovation Service (SFPIE) |
| 4 | 10/07/2025 09:00 | 10/07/2025 14:00 | Aula PB SFPIE | Lifelong Learning and Educational Innovation Service (SFPIE) |
| 5 | 15/07/2025 09:00 | 15/07/2025 14:00 | Aula PB SFPIE | Lifelong Learning and Educational Innovation Service (SFPIE) |
- Campos Climent, Vanessa
- PDI-Titular d'Universitat
- Coordinador/a de Programa de Doctorat
- Director/a Titulacio Master Oficial
- Ejarque Catala, Ana Teresa
- PDI-Ajudant Doctor/A
- Secretari/a de Departament
Open science is becoming a global trend. Open science is a wide concept, usually linked to open-access publishing or open data among other related topics. However, it should not be restricted to these aspects. Thus, one of the challenges to be faced by universities and other research bodies is to pivot from using research software (quantitative and qualitative) subject to licenses to relying on free but reliable software to simplify researchers' tasks in terms of data treatment. Besides, some free software alternatives involve working with commands. This fact prevents its use in the case of some research areas because these alternatives are perceived as not being user-friendly.
For these reasons, the present course proposes focusing on JASP-free software as an alternative that allows one to complete the analysis included in other licensed programs without working with commands.
Specific learning objectives:
- Introducing researchers to JASP interface.
- Facilitate researchers' transition from other licensed quantitative software to JASP.
- Show researchers how to perform the commonly accepted statistical procedures in JASP.
Show researchers how to interpret JASP results reports
1. Getting familiar with JASP interface.
2. Descriptive statistics in JASP.
3. Inferential statistics in JASP:
3.1 Pre-tests in JASP.
3.2 Parametric tests in JASP.
3.3 Non-parametric test in JASP.
4. Correlation analysis in JASP.
5. Multi-item measurement scales validation in JASP:
5.1 Exploratory factor analysis (EFA)
5.2 Confirmatory factor analysis (CFA)
6. Regression analysis in JASP:
6.1 Pre-test and variables’ transformation.
6.2 Simple and multiple regression.
6.3 Stepwise regression.
6.4 Moderating effects.
6.5 Curvilinear effects.
6.6 Logistic regression.
7. Introduction to structural equations in JASP.
7.1 Mediating effects.
By the end of the course, students are expected to be able to:
1. Get familiar with the use of JASP free software as an alternative to other licensed software (SPSS, AMOS, EQS…) to perform quantitative data analysis without the use of commands.
2. Develop research capabilities that allow them to give an accurate response in terms of quantitative data analysis using free software.
3. Apply the commonly accepted statistical techniques in JASP.
4. Interpret and report the analysis outcomes produced in JASP.
During the last session of the course, the attendants will be asked to complete a practical exercise. This exercise will consist of applying some statistical procedures in JASP and briefly reporting the results. This exercise will be an individual delivery.
Following the SFPIE rules in relation to attendance (85%)
