Statistics MSc

Program Overview

Through compulsory and optional modules, students develop a deep understanding of traditional and modern statistical methods and gain experience in applying them to real-world problems. The program prepares graduates for careers in various sectors, including public and private organizations, and provides dedicated career support to help them succeed in their chosen field.

Program Outline

Degree Overview:

• Target Audience: This program is designed for individuals interested in pursuing a career in statistics and related fields, or those seeking to engage in postgraduate research.
• Program Objectives:
• Enhance Quantitative Skills: Build upon existing mathematical and quantitative skills through exposure to diverse statistical techniques and applications.
• Explore Statistical Methods: Gain a comprehensive understanding of both traditional and modern statistical methods, from foundational theory to cutting-edge regression models.

Outline:

• Program Structure: The MSc Statistics program is a full-time, one-year program.
• Course Schedule:
• Compulsory Modules:
• MTH3028 Statistical Inference: Theory and Practice (15 credits):
This module focuses on the theoretical foundations of statistical inference, covering topics such as hypothesis testing, confidence intervals, and statistical power.
• MTHM033 Statistical Modelling in Space and Time (15 credits): This module explores statistical models for analyzing data that varies across space and time, including spatial autocorrelation and time series analysis.
• MTHM047 Bayesian Statistics, Philosophy and Practice (15 credits): This module introduces Bayesian statistics, a powerful approach to statistical inference that incorporates prior knowledge and beliefs.
• MTHM050 Research Project in Statistics (60 credits): This module provides students with the opportunity to conduct an independent research project in a chosen area of statistics.
• MTHM503 Applications of Data Science and Statistics (15 credits): This module explores the practical applications of data science and statistics in various fields, such as business, healthcare, and finance.
• MTHM507 Communicating Data Science (15 credits): This module focuses on the effective communication of data science findings to both technical and non-technical audiences.
• Optional Modules: Students can choose 45 credits from a selection of optional modules, including:
• ECMM422 Machine Learning (15 credits):
This module covers the theory and practice of machine learning, a powerful set of techniques for building predictive models from data.
• ECMM450 Stochastic Processes (15 credits): This module explores the mathematical theory of stochastic processes, which are used to model random phenomena that evolve over time.
• MTHM002 Methods for Stochastics and Finance (15 credits): This module explores statistical methods for analyzing financial data, including risk management and portfolio optimization.
• MTHM006 Mathematical Theory of Option Pricing (15 credits): This module covers the mathematical theory of option pricing, a fundamental topic in financial mathematics.
• MTHM063 Uncertainty Quantification (15 credits): This module explores methods for quantifying and managing uncertainty in complex systems.
• MTHM611 Topics in Environmental Intelligence (15 credits): This module focuses on the application of statistical methods to environmental problems, such as climate change and pollution.
• SOCM033 Data Governance and Ethics (15 credits): This module explores the ethical and legal considerations surrounding the collection, use, and sharing of data.

Assessment:

• Assessment Methods: Modules are assessed through a combination of coursework and exams.

Teaching:

• Teaching Methods: The program utilizes a variety of teaching methods, including lectures, seminars, workshops, and practical exercises.
• Faculty: The program is taught by experts in the field of statistics, who are actively involved in research and practice.
• Research-Led Teaching: The program emphasizes research-led teaching, ensuring students are exposed to the latest ideas, research discoveries, and new technologies.

Careers:

• Career Paths: Graduates of the MSc Statistics program are highly sought after by employers in various sectors, including:
• Public Sector:
Actuarial analyst, data analyst, statistician, market researcher, operational researcher.
• Private Sector: Actuary, data scientist, financial risk analyst, investment analyst.
• Career Support: The University of Exeter provides dedicated career support through the Career Zone team, offering one-on-one guidance, industry contacts, training events, and workshops.

Other:

• Research Expertise: The University of Exeter is renowned for its research in areas such as climate modeling and statistics, control and dynamics, systems biology, astrophysical fluid flows, and number theory.
• Research Projects: The program offers a wide range of exciting and high-impact research projects for students to engage in.

UK fees per year: £12,100 full-time International fees per year: £27,500 full-time