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Curso en Data Analytics for Inclusion & Diversity

Presentación

Presentación

We are immersed in the information society with a wide availability of data from different fields, making it necessary to have tools that help us to understand and use the information extracted from them in our daily lives. For instance, organisations usually collect demographic data from their employees, customers, or members to know the composition of their workforce or community. They often compare their inclusion and diversity data with industry or regional benchmarks to assess their performance relative to their peers, which helps to identify areas for improvement.
In particular, statistical analysis of inclusion and diversity data is a crucial practice for organisations and institutions aiming to promote equity, fairness, and representation. This analysis involves collecting, processing, and interpreting data on different aspects of diversity, such as gender, race, ethnicity, age, disability, and more. Statistical analysis can help identify the main causes of diversity and inclusion challenges, and
factors such as biased hiring practices, lack of diversity in leadership, or discriminatory policies can be uncovered through data analysis. The ultimate goal of diversity and inclusion data analysis is to generate actionable insights that inform policies and strategies.
In summary, statistical analysis of inclusion and diversity data can greatly assist organisations in identifying disparities, setting targets and taking meaningful action to foster a more inclusive and equitable environment. It is an ongoing process that requires commitment, transparency, and ethical considerations to drive positive change.
The course "Data Analytics for Inclusion & Diversity" aims to offer a specific formative program to Bachelor and Master students in the use of Statistical techniques to the analysis of diversity and inclusion data.

Further information-download files below
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Fichero Tamaño Acciones
BIP DAID Flyer.pdf 1.49 MB
Additional Information Onsite Week.pdf 0.96 MB
2 fichero(s) en total

- To identify appropriate statistical techniques and apply them to available data

- To become familiar with the statistical software R

- To perform a basic statistical analysis of a data set and interpret the results appropriately

- To demonstrate an effective ability to communicate the results of a statistical analysis both in writing and orally

- To evaluate critically the assumptions, limitations and implications of statistical analyses

- To develop intercultural skills and learn to work in multidisciplinary teams

- To create a greater awareness of inclusion and diversity and integrate them in the learning experience

The approach of the course is eminently practical with the support of statistical software tools, so we hope that the course will be enjoyable and useful for everyone.
The only academic prerequisites are elementary knowledge of mathematics and basic user computing.
Therefore, the ideal profile of participants to make the most of the opportunities offered by this course is that of students of any degree, with a critical spirit, capable of
appreciating the importance of Statistics in the current context and interested in learning about statistical data processing.

Total number of 15-20 students: 5-7 students from each partner university plus a yet to be determined number from the University of Jaén.
Students will be selected by each partner university from among those who show the greatest involvement and best performance in their degree and who have applied to participate in this BIP.

Preinscripción y matrícula

Fecha de Inicio: 01 de marzo de 2024 a las 00:00

Fecha Fin: 30 de abril de 2024 a las 23:59

Para realizar la preinscripción online pulse el siguiente botón:

Acceso preinscripción

Para realizar la preinscripción se recomienda utilizar el navegador Chrome desde un ordenador. Si recibe un mensaje de error, envía un correo, incluyendo la captura de pantalla y datos personales (nombre y DNI), a continua@ujaen.es.

LOS/LAS ESTUDIANTES CUYA SOLICITUD DE PREINSCRIPCIÓN HAYA SIDO ACEPTADA PODRÁN REALIZAR LA MATRÍCULA.

Fecha de inicio de matrícula: 02 de mayo de 2024 a las 00:00

Fecha de fin de matrícula: 24 de mayo de 2024 a las 23:59

Periodo de matrícula cerrado.

Información Matrícula:

  • ORDINARIA: 0,00 €
  • Plazos propuestos e importes: 1 plazo de 0,00 €.

Para realizar la matrícula se recomienda utilizar el navegador Chrome desde un ordenador. Si recibe un mensaje de error, envía un correo, incluyendo la captura de pantalla y dados personales (nombre y DNI), a continua@ujaen.es.

Importante: Seguro de accidentes: Todos los participantes deben estar cubiertos por un seguro de accidentes (EXCEPTO CURSOS ONLINE)

  • Seguro escolar. Obligatorio para todos los menores de 28 años, cobrándose en Estudios oficiales, una sola vez por curso académico.
  • Seguro accidentes UJA. Obligatorio para todos aquellos alumnos que no tengan abonado el seguro escolar en el curso académico activo, siendo ambos incompatibles, debiendo abonarse una sola vez por curso académico. Afecta a todos los alumnos de estudios oficiales y no oficiales (Grado, Máster, Tercer Ciclo, Enseñanzas Propias y Cursos Cortos)
  • Enlace de informe al alumnado: https://www.ujaen.es/estudios/acceso-y-matricula/matricula/seguros-para-el-alumnado-de-la-uja

El alumnado matriculado en esta actividad puede participar en la Convocatoria de Becas de Formación Permanente 1er. cuatrimestre del curso 2023/24. La Resolución se publicará en el Centro de Formación Permanente y Formación Complementaria - Perfil de Estudiantes en Becas y Ayudas

Información académica

Aquí encontrarás los detalles fundamentales y todos los enlaces necesarios para conocer la organización de tu máster propio.

The contents of this course are structured in 5 modules that include exploratory, descriptive and inference techniques:

Chapter 1: Introduction to statistical data analysis and first steps with R software
Chapter 2: Exploratory analysis of inclusion and diversity data using graphical and analytical methods
Chapter 3: Categorical data analytics for inclusion and diversity
Chapter 4: Inference techniques applied to inclusion and diversity data
Chapter 5: Modelling the relationship between inclusion and diversity characteristics

With the support of the statistical software R, flipped classroom methodology and case studies, the course content will be more interactive and the experience that participants already have can be shared. In addition, the collaborative work between students from different backgrounds and the cultural activities programmed will allow participants to take part in an international exchange.
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The BIP will take the form of project work, in transnational teams, based on the statistical analysis of inclusion and diversity data.
The programme framework consists of:

Face-to-face teaching (June 3-7, 2024), at the University of Jaén, that will include

- Lecture time (20 hours)

- Cultural and social activities.

Online activities (June 10-14, 2024), that will include

- Asynchronous activities (Viewing of videos and reading of scientific texts, )

- Student’s work (proposed activities, preparation of a poster)

- 4 hours of webinars (student presentations, discussion, conclusions)

- Guest lectures.

Assessment:

Online poster, infographic or slide presentation (10-15 minutes): Students will present the results of a statistical analysis carried out using one of the techniques covered in the lectures. (Relative weight 30 %).

Attendance, student work, and participation: This includes attendance, active participation in class activities, and completion of assigned work. (Relative weight: 70 %).

  • Trabajos

Fecha de Inicio: 03 de junio de 2024

Fecha de Fin: 14 de junio de 2024

Calendario Académico: 3-7 June and 10-14 June, 2024

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Normativas Relevantes para tus Estudios

Normativa de Enseñanzas Propias de Formación Permanente de la Universidad de Jaén