MSc w Statystyce i Prawdopodobieństwie Stosowanym

Are you considering a career as a professional statistician in the industry? This course will provide you with the necessary advanced knowledge and skills. This masters course differs from the Statistics MSc, by providing specialised training in probability models, suitable for roles in business and finance.

You'll study two compulsory modules in Fundamentals of Statistics and Stochastic Models. They provide the basis for the remaining optional modules. These include, amongst others, Mathematical Finance and Statistical Machine Learning.

You will develop advanced statistical techniques. This will enable you to test theories, learn how to interpret large and complex data, and extract relevant insights from it. The course can lead to careers in data science, healthcare and the digital economy.

In the summer you'll complete a dissertation. This will be in collaboration with staff from the school's internationally recognised Statistics and Probability Research group, or one of our industry partners, such as Capital One.

Alexas_Fotos / Pixabay

Why choose this course?

• Expand your network
  • interact with other MSc students.

• Analytical thinking
  • develop skills to think logically and critically, gain competence in statistical software.

• Unique MSc in the UK -  allows you to specialise in statistics with particular focus on applied probability (based on Find a Masters search in May 2020).

• Flexible programme  with a broad range of modules influenced by our research expertise.

• International research
  • modules taught by experts in infectious disease modelling, analysis of object data and Bayesian computation (Research Excellence Framework 2014).

Course content

The course is split between core and optional modules.

You will study the compulsory modules in Fundamentals of Statistics and Stochastic Models. This will provide you with the knowledge and skills required to complete your chosen optional modules during the rest of the year.

On completion of your optional modules, you will prepare a compulsory written research dissertation. You will be given one-to-one support from your supervisor who will offer advice and guidance during your dissertation.

During the year you will study a total of 180 credits. This will include 120 credits worth of taught modules and the 60-credit dissertation.

* Please note, you may not take both Statistical Machine Learning and Uncertainty Quantification as optional modules.

Modules

Core modules

• Fundamentals of Statistics

• Statistics Dissertation

• Stochastic Models

Optional modules

You choose three optional modules from one of the following:

• Applied Multivariate Statistics

• Computational Statistics

• Statistical Machine Learning

• Stochastic Financial Modelling

• Time Series and Forecasting

• Uncertainty Quantification

Learning and assessment

How you will learn

• Lectures

• Workshops

• Computer labs

Some modules will be taught alongside students from other courses.

How you will be assessed

• Coursework

• Dissertation

• Examinations

• Project work

You will be awarded the Master of Science Degree provided you have successfully completed the taught stage by achieving a weighted average mark of at least 50% with no more than 40 credits below 50% and no more than 20 credits below 40%.

You must achieve a mark of at least 50% in the dissertation.

Contact time and study hours

The number of formal contact hours varies depending on the optional modules you are studying. As a guide, in the Autumn and Spring semesters, you will typically spend around 14 hours per week in lectures.

You will work on your research project between June and September, usually based at the University.

Teaching is provided by academic staff within the School of Mathematical Sciences. All modules are typically delivered by Professors, Associate and Assistant Professors. Additional support in small group and practical classes may involve PhD students and post-doctoral researchers.

The majority of your lecturers and tutors will be based within the mathematics building. This means if you need to get in touch with them during office hours, they can be contacted easily as they are close by.

Entry requirements

All candidates are considered on an individual basis and we accept a broad range of qualifications. The entrance requirements below apply to 2021 entry.

Home/ UK students

EU/ International students

English language support

If you need support to meet the required level, you may be able to attend a presessional course. Our Centre for English Language Education is accredited by the British Council for the teaching of English in the UK.

For presessional English courses, you must take IELTS for UKVI to meet visa regulations.

If you successfully complete your presessional course to the required level, you can then progress to your degree course. This means that you won't need to retake IELTS or equivalent.

Alternative qualifications

We recognise that applicants have a variety of experiences and follow different pathways to postgraduate study.

We treat all applicants with alternative qualifications on an individual basis. We may also consider relevant work experience.

If you are unsure whether your qualifications or work experience are relevant, contact us.

Where you will learn

University Park Campus

University Park Campus covers 300 acres, with green spaces, wildlife, period buildings and modern facilities. It is one of the UK's most beautiful and sustainable campuses, winning a national Green Flag award every year since 2003.

Most schools and departments are based here. You will have access to libraries, shops, cafes, the Students’ Union, sports village and a health centre.

You can walk or cycle around campus. Free hopper buses connect you to our other campuses. Nottingham city centre is 15 minutes away by public bus or tram.

Dedicated MSc study room

There is a dedicated workroom for masters students, based within the School of Mathematical Sciences. It is equipped with desktop computers, this provides a quiet study space.

Careers

Careers advice

We offer individual careers support for all postgraduate students.

Expert staff can help you research career options and job vacancies, build your CV or résumé, develop your interview skills and meet employers.

More than 1,500 employers advertise graduate jobs and internships through our online vacancy service. We host regular careers fairs, including specialist fairs for different sectors.

Job prospects

Graduate destinations

Alongside their statistical knowledge and skills in probability, our graduates leave Nottingham with valuable skills in:

• Logical thinking
• Problem-solving
• Data analysis and manipulation

Statisticians are required to work in many sectors including banking, education, finance, healthcare, sport and transport.

Previous graduates work as:

• Analysis officer
• Business analyst
• Pricing model analyst

They have taken roles in organisations including Capital One, HMRC, and the Lowell Group.

Career progression

97.5% of postgraduates from the School of Mathematical Sciences secured graduate-level employment or further study within 15 months of graduation. The average annual salary for these graduates was £28,131.*

* HESA Graduate Outcomes in 2020. The Graduate Outcomes % is derived using The Guardian University Guide methodology. The average annual salary is based on graduates working full-time within the UK.

The University of Nottingham was founded on the vision and philanthropic spirit of Jesse Boot who, in 1928, donated the land that is now University Park. The vision of a university devoted to the discovery, enterprise and the advancement of the human condition, combined with his lifelong commitment to improving health and wellbeing, remains intrinsic to the culture of the University today and will continue to underpin our future purpose.

We have inspiring campuses in three countries, energising us to be a globally engaged university that is also committed to making a difference in our cities and regions

We empower and support students and staff to collaborate in learning, scholarship and discovery across all realms of knowledge, solving problems and improving lives

We are stewards of a pioneering and entrepreneurial tradition of creativity and innovation