MSc Statistics

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Course Overview

Statistics support many aspects of the modern world, from science and technology to finance and business. They allow us to overcome scientific, industrial and social problems and a Masters-level understanding of them is beneficial in many careers.

Our Royal Statistical Society (RSS) accredited Masters programme combines a blend of theoretical study with real-world application. This means that over the year, you will develop advanced statistical skills and knowledge, while having the opportunity to put what you learn into practice and gain valuable, real-world experience. As a result, after graduation, you will be ideally placed to pursue your career ambitions, and progress in your field.

Based in our purpose built facility, the Postgraduate Statistics Centre (PSC), you will have access to specialist software and equipment, such as our dedicated super computer. These facilities will support you as you engage with one of our specialist statistical pathways. The pathways you can choose from are:

  • Environmental Statistics
  • Medical Statistics
  • Pharmaceutical Statistics

As part of your programme, you will also complete our Statistics in Practice module. Providing a strong foundation for Masters-level study in statistics, you will gain key practical skills using software, including R and SAS. Your scientific writing abilities will also be enhanced as we help you to present rigorous, written mathematical arguments, and develop your understanding of scientific papers. Oral presentations will also allow you to put your public speaking skills into practice, specifically in the context of presenting summaries of papers.

Finally, over the course of three months, you will complete a Masters-level dissertation. This project will be supervised by one of our academics and may be in collaboration with an external organisation, such as: GlaxoSmithKline (GSK); AstraZeneca; Wrightington Hospital; Royal Lancaster Infirmary; Leahurst Veterinary Centre; or the Department of the Environment, for example.

Assessment

Teaching in our department is delivered through a range of methods to create the best possible learning experience. Alongside traditional lectures, you can expect to benefit from small workshop groups, which are guided by tutors who are active researchers and offer you an opportunity to put what you have learnt in lectures into practice. We also run computer lab sessions focused on developing your skills in specialist mathematical and statistical software.

Career

Statistics graduates are highly employable, having in-depth specialist knowledge and a wealth of skills. Through this degree, you will graduate with a comprehensive skill set, including data analysis and manipulation, logical thinking, problem-solving and quantitative reasoning, as well as advanced knowledge of the discipline. In addition, statistics plays a valuable role in all businesses and enterprises. As a result, statisticians are sought after in a range of industries, such as education, finance, forensics, health, market research, and transport.

The starting salary for many graduate statistical roles is highly competitive, and popular career options include:

  • Assistant Statistician
  • Data Analyst
  • Market Researcher
  • Mathematical Modeller
  • Statistical Officer
  • Teacher

In addition, studying at Masters-level will further enhance your career prospects, opening up opportunities to progress further in your career.

Alternatively, you may wish to undertake postgraduate research study at Lancaster and pursue a career in research and teaching.

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Requirements

The requirements may vary based on your selected study options.





















Modules

  • MSc Statistics Dissertation
  • Statistical Fundamentals I
  • Statistical Fundamentals II
  • Statistical Learning
  • Statistics in Practice
  • Clinical Trials
  • Computationally Intensive Methods
  • Extreme Value Theory
  • Methods for Missing Data
  • Modelling Multilevel and Longitudinal Data
  • Principles of Epidemiology
  • Survival and Event History Analysis
  • Time-Series
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    Use our magical AI system, to check your admission chances for this course.
    Offer response
    4 - 6 weeks after your application is submitted
    Backlogs accepted
    This course accepts backlogs