BSc Hons Economics, Mathematics and Statistics

4 Years On Campus Bachelors Program

University College Dublin

Program Overview

The BSc (Hons) in Economics, Mathematics and Statistics at University College Dublin (UCD) is a four-year honours degree that combines economic thinking with strong mathematical and statistical skills, making it ideal for students who enjoy problem-solving and analytical thinking. The program prepares you to understand how economies function, work confidently with data, and apply quantitative methods to real-world challenges across multiple industries.

Curriculum Structure

Year 1 – Building Core Foundations
In the first year, students develop a solid base across all three disciplines. Core modules include Introduction to Economics, Microeconomics and Macroeconomics, alongside mathematical subjects such as Calculus I & II, Linear Algebra I, and Combinatorics & Number Theory. Students are also introduced to Practical Statistics, Statistical Modelling, and Introduction to Programming, helping them begin analysing data from the start.

Year 2 – Strengthening Concepts and Methods
Year 2 focuses on developing deeper theoretical and technical understanding. Students study Intermediate Microeconomics and Macroeconomics, advanced mathematical topics like Multivariable Calculus, Linear Algebra 2, Algebraic Structures, and Analysis, and begin formal probability theory through Introduction to Probability. Modules such as Predictive Analytics start linking theory with practical data applications.

Year 3 – Application and Specialisation
In the third year, learning becomes more applied and specialised. Key modules such as Econometrics, Complex Analysis, and Time Series train students to model economic and statistical relationships using real data. Optional modules including Stochastic Models and Financial Mathematics allow students to align their studies with career interests, while opportunities for internships or study abroad add valuable global exposure.

Year 4 – Advanced Study and Research
The final year allows students to specialise further through advanced modules like Statistical Machine Learning, Actuarial Statistics, and Optimisation in Finance. Students can also choose higher-level economics options and electives such as Game Theory or Cryptography, alongside completing a research project that demonstrates independent thinking and advanced analytical ability.

Focus Areas

Economics theory, quantitative analysis, mathematical modelling, statistics, data analytics, computational methods.

Learning Outcomes

Graduates gain strong problem-solving skills, the ability to analyse and interpret complex datasets, apply economic reasoning to real-world issues, and communicate insights clearly in professional and academic environments.

Professional Alignment (Accreditation)

The program is delivered within UCD’s established honours degree framework, offering a rigorous academic foundation that aligns well with careers in economics, finance, data analytics, actuarial science, public policy, and research.

Reputation (Employability Rankings)

University College Dublin is internationally recognised for its strength in economics and quantitative disciplines, and its graduates are well regarded by employers for their analytical skills, adaptability, and strong academic training.

Experiential Learning (Research, Projects, Internships etc.)

At University College Dublin, the BSc (Honours) Economics, Mathematics and Statistics is a highly analytical degree designed for students who want to combine economic theory with rigorous quantitative and statistical methods. From the very first year, you gain hands-on experience in data analysis, mathematical modelling, and applied economics, preparing you to tackle complex real-world problems. The programme emphasises practical engagement through tutorials, lab-style workshops, applied coursework, and research-led teaching. As you progress, you build advanced skills in econometrics, statistical modelling, and quantitative economics, culminating in opportunities to conduct independent research or specialised projects. This combination ensures that graduates leave with strong technical ability and career-ready experience in analytical roles across multiple sectors.

Here’s how experiential learning is embedded throughout the programme:

Applied Tutorials & Problem-Solving Sessions
Tutorials and workshops allow you to work through real-world economic and statistical problems, apply quantitative methods, and strengthen critical thinking and communication skills.
Econometrics & Statistical Analysis Labs
You gain practical experience using statistical software to analyse data, model economic relationships, and interpret results, giving you essential applied skills in finance, economics, and research.
Mathematics & Modelling Applications
Core mathematics modules are complemented by hands-on modelling exercises that reinforce your understanding of algorithms, optimisation, and quantitative reasoning in economic contexts.
Research-Led Teaching & Data-Driven Learning
Modules are informed by current research in economics, mathematics, and statistics, ensuring that the skills you develop are aligned with contemporary analytical and industry needs.
Group Projects & Collaborative Work
Many modules include team-based projects that require you to work collaboratively to solve applied problems, present findings, and develop professional communication skills.
Independent Study & Capstone Research Opportunities
In later years, you can undertake research-focused modules or a final-year project, allowing you to design, conduct, and report on quantitative or applied economic research independently.
Flexible Specialisation Options
You can tailor your studies in areas such as financial mathematics, actuarial science, data analytics, or advanced econometrics to align with your career interests and professional goals.
Study Abroad & Global Exposure
Students may have the opportunity to study at partner universities abroad, gaining international experience and exposure to diverse economic, statistical, and analytical approaches.
Career-Focused Skill Development
Through continuous assessment, applied projects, and analytical exercises, you develop skills in data analysis, problem-solving, quantitative modelling, and clear communication — all highly valued by employers.

Facilities & Academic Resources (Official):
Access to lecture and tutorial spaces, statistical and econometric software, computing labs, mathematics and modelling resources, extensive library collections, research supervision for independent projects, collaborative study areas, and UCD’s international exchange networks — all structured to provide practical, hands-on experience in economics, mathematics, and statistics.

Why choose Economics, Mathematics and Statistics at UCD:
This honours degree is ideal for students seeking a strong quantitative and analytical foundation, with practical experience that prepares them for careers in finance, consulting, data analytics, actuarial science, economic research, policy analysis, or postgraduate study. Graduates leave with the skills, experience, and confidence to succeed in competitive and data-driven fields.

Progression & Future Opportunities

The BSc (Hons) in Economics, Mathematics and Statistics at University College Dublin (UCD) equips you with a powerful combination of quantitative, analytical and economic reasoning skills — a mix that employers across finance, consulting, technology, public policy and data science actively seek. Graduates often move into roles such as Data/Economic Analyst, Quantitative Analyst, Risk Analyst and Business Strategy Consultant, with the ability to interpret complex data, model real‑world systems, and support strategic decision‑making in dynamic professional environments.

• University Services to Support Your Career: UCD’s Careers Service offers personalised career guidance, CV and interview preparation, targeted networking events, employer fairs, internship and placement support, and access to industry‑specific recruitment — helping you build professional confidence and connections throughout your degree.
• Employment Outcomes & Salary Prospects: Graduates with strong quantitative and analytical skills enjoy high employability in a wide range of sectors including finance, consulting, technology, data analytics and government services. These skills also support competitive starting salaries due to strong demand for professionals who can interpret data and inform strategic decisions.
• University–Industry Engagement: The programme connects you with employers from industry, consulting firms, financial institutions and public organisations through guest lectures, careers fairs and applied projects — giving you exposure to real‑world problems, employer expectations and potential professional networks before you graduate.
• Long‑Term Accreditation Value: The combination of economics with rigorous mathematical and statistical training builds highly transferable expertise valued internationally, giving you flexibility to adapt to changing job markets and pursue specialist credentials or professional qualifications in areas like analytics or finance.
• Graduation Outcomes: Graduates are prepared to analyse complex datasets, build quantitative models, interpret economic trends and support evidence‑based decision‑making across sectors such as finance, consulting, tech, government policy, risk management and business intelligence.

Typical roles graduates pursue include:
• Data/Economic Analyst – interpreting and modelling data to drive business and policy decisions.
• Quantitative/Risk Analyst – building models to assess risk, markets and investment outcomes.
• Business/Data Strategy Consultant – advising organisations on analytics‑driven strategy.
• Statistical Modelling Specialist – supporting analytics and data science initiatives.

Further Academic Progression:

After completing the BSc (Hons) in Economics, Mathematics and Statistics, you can expand your expertise and boost your career potential through postgraduate study. Many graduates pursue Master’s degrees in areas such as data science, statistics, financial mathematics, economics, actuarial science, risk analytics, machine learning or business analytics to deepen specialised knowledge. Others may choose PhD research in quantitative economics, statistics, data science or related fields, preparing for careers in academia, advanced research or high‑level analytical leadership positions. Postgraduate study also strengthens your professional profile and supports pathways into senior roles and specialist areas across sectors where data and quantitative reasoning are key.