Program Overview

Introduction to the Statistics MSc Program

The Statistics MSc program at University College London (UCL) is designed to provide students with a broad-based approach to statistics, covering modern ideas in statistics, including applied Bayesian methods, generalized linear modeling, and object-oriented statistical computing. The program offers an excellent balance between theory and application, preparing students for careers in industry, healthcare, government, commerce, or research.

Program Structure

The program is available in both full-time and part-time modes. Full-time students complete the program in one calendar year, while part-time students complete it in two calendar years. The program starts in September, and applications are accepted from October of the previous year.

Entry Requirements

To be eligible for the program, applicants must have a minimum of an upper second-class Bachelor's degree in a quantitative discipline from a UK university or an overseas qualification of an equivalent standard. Knowledge of mathematical methods and linear algebra at university level and familiarity with introductory probability and statistics are required. Relevant professional experience will also be taken into consideration.

English Language Requirements

The English language level for this course is Level 1. UCL Pre-Master's and Pre-sessional English courses are available for international students who need to improve their academic English and academic skills.

Course Overview

The program covers a range of topics, including:

• Statistical computing
• Statistical models and data analysis
• Statistical design of investigations
• Research project
• Applied Bayesian methods Optional modules include:
  • Statistical inference
  • Stochastic systems
  • Forecasting
  • Decision and risk
  • Stochastic methods in finance
  • Medical statistics
  • Bayesian methods in health economics
  • Quantitative modeling of operational risk and insurance analytics
  • Statistical machine learning
  • Computational statistics

Careers and Employability

Graduates of the Statistics MSc program typically enter professional employment across a broad range of industry sectors or pursue further academic study. Areas of employment include accountancy and financial services, banking and investment, and consultancy. The program provides skills that are highly sought after by companies and research organizations, including advanced training in methods and computational tools for data analysis.

Teaching and Learning

The primary method of communicating information and stimulating interest is through lectures, which provide students with a formal knowledge base. Understanding of lecture material is reinforced by problem classes, computer workshops, and group tutorials, as well as by self-study. Peer-assisted learning, discussion with other students, and individual discussion with staff also support the learning process.

Assessment

All summative assessment is organized at modular level during the academic year in which the module is taken. Most Statistical Science modules employ a combination of end-of-year written examination and coursework to assess subject-specific knowledge and academic skills. Statistical project work further assesses intellectual, academic, and research skills.

Fees and Funding

The tuition fees for the program are:

• UK students: ｣16,800 (full-time), ｣8,400 (part-time)
• International students: ｣42,700 (full-time), ｣21,350 (part-time) There are no program-specific costs. Students may need to pay for additional costs such as travel and living expenses.

Accreditation

The Statistics MSc program is accredited by the Royal Statistical Society. The current period of accreditation covers students who first enroll between September 2023 and September 2028.

Research Areas

The program allows students to specialize in areas such as biostatistics, applied stochastic modeling, quantitative decision making, quantitative analysis for industry, and financial mathematics. The research project is a consolidation of the MSc's taught component, and students will normally analyze and interpret data from a real, complex problem, offering the chance to produce viable solutions. Project topics can be selected from a departmental list, or students can make their own suggestions. The list usually includes some collaborative projects available with industrial partners.