Bachelor's degree in Statistics

Introduction

Orientatively, in the previous degree, Catalan 62.1%, Spanish 37.9%

10.110 (July 2025, start of process, via official entrance examinations/vocational training)

Objectives and competences

Objectives

The core objective aim is to train generalist statistics professionals with the skills to carry out specific tasks in the data analysis and decision-making process, with special emphasis on:

• data collection and processing;
• modelling, identifying and developing the appropriate model in each case;
• analysis, computational manipulation of models and critical analysis;
• decision-making, understanding the nature of problems and interpreting the solutions provided by the corresponding models.

Students are provided with the essential skills to successfully join the job market: analysis and synthesis, problem-solving, reasoning, spoken and written communication, team-work, organization, decision-making, capacity for independent learning, etc.

Competences

General competences

• Commitment to ethical practice (critical and self-critical capabilities/capacity to demonstrate attitudes consistent with accepted notions of ethical practice).
• Capacity for learning and responsibility (capacity for analysis and synthesis, to adopt a global approach, and to apply knowledge in practice / capacity to make decisions and to adapt to new situations).
• Ability to work as part of a team (capacity to work with others and contribute to a common project / capacity to work in cross-disciplinary and multicultural teams).
• Creative and entrepreneurial skills (capacity to conceive, design and manage projects / capacity to research and integrate new knowledge and approaches).
• Communication skills (capacity to understand and produce spoken and written Catalan, Spanish and a third language including the comprehension and use of specialized language / capacity to search for, use and assimilate information).
• Social commitment and concern for sustainability

.Specific competences

• Capacity to identify information analysis requirements in different settings and institutions and detect potential sources of inconsistency and uncertainty.
• Capacity to select the most suitable method for a statistical study, evaluate possible alternatives, and integrate cost and resource analyses if necessary.
• Capacity to use statistical methods as the basis for decision-making in different professional and organizational contexts.
• Capacity to identify, formulate and solve decision-making problems in organizational settings, using operations research models and integrating the results of statistical analyses where necessary.
• Capacity to apply statistical techniques and operations research to improve quality and productivity in different settings (technological, industrial, etc).
• Capacity to apply logical reasoning and mathematical instruments to a specific context.
• Capacity to use specific mathematical procedures commonly applied in statistics and operations research.
• Capacity to use, interpret, document and adapt statistical analysis and database management tools, adjusting models and solving specific problems.
• Capacity to order, present and summarize the information obtained from a series of data using objective criteria.
• Capacity to identify the properties of different estimation methods and determine their advantages and disadvantages in specific contexts.
• Capacity to apply different hypothesis testing procedures to answer questions on a specific context.
• Capacity to identify the principal models of operations research, and understanding of their properties and areas of application.
• Capacity to apply the correct optimization methods to different operations research models.
• Capacity to use different programming languages to implement database management algorithms and systems.
• Capacity to conceive, model, analyse, validate and interpret real-life situations and problems, adapting theoretical models to the specific requirements of different areas of application.

Access and admission

Applicant profile and access requirements

Recommended applicant profile

• Students with an interest in data analysis techniques and how these techniques are applied to decision-making in different areas: business intelligence, machine learning, bioscience, economics, finance, engineering, etc.
• Disposition to use mathematics and computer science from the first stages of training as a statistician.
• Knowledge of mathematics at upper secondary school level. Ability to analyse and interpret numerical results.

Access requirements and conditions

Admission for students with studies completed outside Spain.

Applicants holding higher educational qualifications from a university outside Spain should consult the page Admission with foreign qualifications to find out about specific admission requirements.
 

Pre-enrolment

Students that have studied abroad and who wish to study at the University of Barcelona may be admitted to EHEA bachelor's degree courses. Procedures for gaining admission will depend on the qualifications held by each applicant.

For further information about admission, consult the page Admission with foreign qualifications.
 

Enrolment

As a general rule, at the UB you will be required to enrol online via the Students Portal. To find out the date and time you have been assigned, check the specific information for your course. Remember that you can lose your place if you do not enrol on the day you have been assigned.

• Academic information
  • Documents required for enrolment
  • Procedure to formalize enrolment
  • After enrolment
  • Grants and financial aid

Welcome

Support and guidance

• Pre-enrolment information and events
• Welcome portal
• Student Support Service (SAE)
• Open days
• Informative sessions

Course curriculum

Subjects and course plans

Distribution of credits

List of subjects

Previous years

Teaching staff

Placements

Placements are supervised by tutors and subject to assessment.They are therefore included in the academic record.  There is also an option to complete non-curricular placements of up to 500 hours, which can be extended to 900 hours. For both curricular and non-curricular placements, an educational cooperation agreement is signed between the UB and the company, institution or other organization at which the placement will be carried out.

• Institutional information
  • Regulations on external placements
  • FeinaUB

Career opportunities

What can you work on ?

• Business intelligence: data, business and strategic consultancy agencies. Companies which use the analysis of their clients' data to prepare strategic plans for improvement, to increase sales, performance and turnover and to improve product quality, business organization, etc.
• Machine learning: technology companies that design statistical algorithms to improve decision-making based on previous data analysis and to provide new inputs in every step of the process. Computational statistics
• Economy and finance: central services of financial entities, banking, risk assessment, stock market, portfolio management, financial analysis, market research, pricing policies, insurance.
• Biosciences: research using biomedical data in hospitals or research centres, public health, pharmaceutical industry, clinical trials, animal health, environment, life sciences, bioinformatics, agriculture, etc.
• Public administration: official statistics institutes, demographic projections, social trends, job market, optimum allocation of resources, etc.
• Industry and services: experiment design, quality control, process and product improvement, logistics, production planning, optimum management of resources, etc.
• Teaching and research: university teaching and research, secondary education, etc.

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