Train to work as a professional statistician and gain skills and experience working at the interface between statistics and finance.
Our course emphasises data analysis and will provide you with contemporary statistical ideas and methodologies that are attractive to prospective employers. The skills you gain are useful for a wide range of financial data analysis and in a range of other sectors where data analysis is required, for example sociology, health science, medical science or biology. This experience is also an ideal foundation for further academic study; many of our students choose to progress to PhD.
Our Statistics and Probability Group has a thriving research culture. Our group works with mainstream statistics to develop new methodology and apply it to real-world problems. The team produces world-class research, publishing in top journals. Our graduate students have full access to this expertise, as well as being exposed to forefront research carried out across the globe through our regular seminars and working groups.
Dusa McDuff seminar room exclusively for Masters students
This course will equip you with the necessary skills to:
You'll study a total of 180 credits:
Unique to our degree, you can choose one of two distinct pathways. Pathway A provides a thorough mathematical grounding in the theory of option pricing, while Pathway B provides a simpler introduction to the same material.
The core modules we offer will give you a strong grounding in statistical data analysis and modelling techniques, as well as much needed computational skills required by finance-based employers, such as C/C++ and R languages. Additionally, you'll choose option modules that are aligned with your own interests, resulting in a flexible programme tailored to meet your needs.
You'll take 100 credits from core modules, and 20 credits from option modules.
Core modules (both pathways):
Additional core modules (pathway A):
Additional core modules (pathway B):
Option modules (pathway A)
Choose two of the following:
Option modules (pathway B)
Choose two of the following:
Please note, modules may change to reflect the latest academic thinking and expertise of our staff.
Your Masters will culminate in a dissertation (60 credits) on a selected topic in Statistics or Computational Finance.
It will be a piece of independent work that you complete over the summer. You will have guidance from a project supervisor with weekly supervision, scheduled at a time to suit you.
Our recent students' dissertations have investigated topics including:
Every course at York is built on a distinctive set of learning outcomes. These will give you a clear understanding of what you will be able to accomplish at the end of the course and help you explain what you can offer employers. Our academics identify the knowledge, skills, and experiences you'll need upon graduation and then design the course to get you there.
|Full-time (1 year)||£12,060||£24,620|
Students on a Tier 4 Visa are not currently permitted to study part-time at York.
UK/EU or international fees? The level of fee that you will be asked to pay depends on whether you're classed as a UK/EU or international student.
Discover your funding options to help with tuition fees and living costs.
If you've successfully completed an undergraduate degree at York you could be eligible for a 10% Masters fee discount.
You can use our living costs guide to help plan your budget. It covers additional costs that are not included in your tuition fee such as expenses for accommodation and study materials.
You’ll work with world‐leading academics who’ll challenge you to think independently and excel in all that you do. Our approach to teaching will provide you with the knowledge, opportunities, and support you need to grow and succeed in a global workplace.
Our teaching is informed by the latest research, meaning you can focus on the latest ideas and models.
We use a wide range of teaching methods to suit different learning styles including:
For some modules you may also attend practical classes, computer laboratories or workshops.
Lectures are used to describe new concepts you will have to learn and problems classes put them into practice. Seminars are small, interactive sessions which allow us to focus on your individual needs. You'll be able to use our Virtual Learning Environment to supplement lectures and seminars.
While you're working on your project and your dissertation you'll have regular meetings with your academic supervisor who will offer advice and support. We will give you a supervisor with specialist knowledge of the area you're investigating.
You will be based in the Department of Mathematics in James College on Campus West. Most of your small group teaching will take place in the Department's dedicated MSc seminar room (the Dusa McDuff room), with larger classes taking place close by in James College, Derwent College and elsewhere on Campus West.
Our beautiful green campus offers a student-friendly setting in which to live and study, within easy reach of the action in the city centre. It's easy to get around campus - everything is within walking or pedalling distance, or you can always use the fast and frequent bus service.
All taught modules are assessed by a combination of closed book written exams, coursework, projects and presentations.
The closed book written exam assesses your subject-specific knowledge through both theoretical and practical questions and open-ended problems.
The coursework and projects often require the use of software, giving you an opportunity to develop your technical skills. They will test your subject knowledge and analytical, theoretical skills as well as the practical aspects of application, implementation and interpretation.
Developing and delivering digital presentations will enhance your communication skills for a range of audiences, from the general public to subject experts.
The independent study module relies on your own research, so you'll continue to develop your critical reasoning and digital literacy skills, including programming. As this module is assessed with a dissertation, your training is rounded off by consistently working on your written communication skills.
The big data analysis skills you develop on this course provide attractive employment opportunities in a growing number of industries where such skills are in high demand. The course is also a good foundation for continuing your studies at PhD level.
The destinations of recent graduates from this course include:
Our computational skills are transferable and employers recognise the value of the programming knowledge you will have developed to a high level during this course.
|Undergraduate degree||2:1 or equivalent in Mathematics or in a subject with a substantial mathematics component. We may accept a 2:2 undergraduate degree supported by relevant professional qualifications.|
If English isn't your first language you may need to provide evidence of your English language ability. We accept the following qualifications:
|IELTS||6.0, minimum 5.5 in each component|
|PTE Academic||55, minimum 51 in each component|
|C1 Advanced and C2 Proficiency||169, minimum 162 in each component|
|TOEFL||79, minimum 17 in Listening, 18 in Reading, 20 in Speaking and 17 in Writing|
|Trinity ISE III||Pass in all components|
For more information see our postgraduate English language requirements.
You may be eligible for one of our pre-sessional English language courses. These courses will provide you with the level of English needed to meet the conditions of your offer.
The length of course you need to take depends on your current IELTS scores and how much you need to improve to reach our English language requirements.
After you've accepted your offer to study at York, we'll confirm which pre-sessional course you should apply to via You@York.
You can apply and send all your documentation electronically through our online system. You don’t need to complete your application all at once: you can start it, save it and finish it later.
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