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Statistics with Data Analytics MSc

Course code

G300PSTATDAT

Start date

September

Subject area

Mathematics

Mode of study

1 year full-time

2 years part-time

Fees

2020/21

UK / EU £10,440

International £19,280

Entry requirements

2:2

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Overview

Statistics is the study of the collection, analysis, interpretation, presentation and organisation of data. Statistical analysis and data analytics is listed as one of the highly desirable skills employers are looking for, and with data becoming an ever increasing part of modern life, the talent to extract information and value from complex data is scarce.

The new Statistics and Data Analytics MSc is designed to train the next generation of statisticians with a focus on the field of data analytics. Employers expect skills in both statistics and computing. This master’s programme will provide a unique and coherent blend of modern statistical methods together with the associated computational skills that are essential for handling large quantities of unstructured data. This programme offers training in modern statistical methodology, computational statistics and data analysis from a wide variety of fields, including financial and health sectors.

You can explore our campus and facilities for yourself by taking our virtual tour.

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Course content

The programme consists of eight compulsory modules and a statistics with data analytics dissertation. The first term provides a thorough grounding in core programming, statistical and data analysis skills. In addition to acquiring relevant statistical and computational methods, you’ll be encouraged to engage with real commercial and/or industrial problems through a series of inspiring case studies delivered by guest speakers.

On completing this course you’ll be equipped with a range of advanced statistical methods and the associated computational skills for handing large quantities of unstructured data. You’ll develop a critical awareness of the underlying needs of industry and commerce through case studies. You’ll be able to analyse real-world data and to communicate the output of sophisticated statistical models in order to inform decision making processes. You’ll have the necessary computational skills to build and analyse simple/appropriate solutions using statistical Big Data technologies.

Compulsory modules

  • Big Data Analytics
  • Computer Intensive Statistical Methods
  • Data Visualisation
  • Fundamentals of Machine Learning
  • Probability and Stochastics
  • Quantitative Data Analysis
  • Research Methods and Case Studies
  • Dissertation

Optional modules

  • Network Models
  • Time Series Modelling

This course can be studied 1 year full-time or 2 years part-time, starting in September.

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Careers and your future

By the end of this programme you’ll have acquired an advanced level of statistical knowledge and data analytical skills. This will allow you to work as an independent expert within a multidisciplinary team that designs, performs, analyses and reports about applied scientific research.

You’ll be equipped to pursue a career in data science, the financial sector or the health sector. Areas you might be interested in could include big processing companies (Accenture, Oracle Corporation), the financial sector (JP Morgan), pharmaceuticals (GSK), government agencies (the Office of National Statistics) and data science departments within universities.

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UK entry requirements

  • A UK honours degree or equivalent, internationally recognised qualification in mathematics/statistics or other numerate disciplines with adequate content in statistics.
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EU and International entry requirements

If you require a Tier 4 visa to study in the UK, you must prove knowledge of the English language so that we can issue you a Certificate of Acceptance for Study (CAS). To do this, you will need an IELTS for UKVI or Trinity SELT test pass gained from a test centre approved by UK Visas and Immigration (UKVI) and on the Secure English Language Testing (SELT) list. This must have been taken and passed within two years from the date the CAS is made.

English language requirements

  • IELTS: 6.5 (min 6 in all areas)
  • Pearson: 58 (51 in all subscores)
  • BrunELT: 65% (min 60% in all areas)
  • TOEFL: 92 (min 20 in all)

You can find out more about the qualifications we accept on our English Language Requirements page.

Should you wish to take a pre-sessional English course to improve your English prior to starting your degree course, you must sit the test at an approved SELT provider for the same reason. We offer our own BrunELT English test and have pre-sessional English language courses for students who do not meet requirements or who wish to improve their English. You can find out more information on English courses and test options through our Brunel Language Centre.

Please check our Admissions pages for more information on other factors we use to assess applicants. This information is for guidance only and each application is assessed on a case-by-case basis. Entry requirements are subject to review, and may change.

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Fees and funding

2020/21

UK / EU

£10,440 full-time

£5,220 part-time

International

£19,280 full-time

£9,640 part-time

More information on any additional course-related costs.

See our fees and funding page for full details of postgraduate scholarships available to Brunel applicants.

Fees quoted are per year and are subject to an annual increase. 

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Teaching and Learning

Mathematics at Brunel has an active and dynamic research centre and many of our lecturers are widely published and highly recognised in their fields. Their work is frequently supported by external grants and contracts with leading industry and government establishments. Lecturers are consequently at the frontiers of the subject and in active contact with modern users of mathematics. This means that you can be assured that our academics are teaching you a truly up-to-date methods and you’ll benefit from a wide range of expertise across the different areas of mathematics.

You’ll be taught using a range of teaching methods, including lectures, computer labs and discussion groups. Lectures are supplemented by computer labs and seminars/exercise classes and small group discussions. The seminars will be useful for you to carry out numerical data analysis, raise questions arising from the lectures, exercise sheets, or self-studies in an interactive environment.

Support for academic and personal growth is provided through a range of workshops covering topics such as data protection, critical thinking, presentation skills and technical writing skills.

You’ll also complete an individual student project supervised by a relevant academic on your chosen topic.

Should you need any non-academic support during your time at Brunel, the Student Support and Welfare Team are here to help.

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Assessment and feedback

The assessment of all learning outcomes is achieved by a balance of coursework and examinations. Assessments range from written reports/essays, group work, presentations through to conceptual/statistical modelling and programming exercises, according to the demands of particular modular blocks. Additionally, class tests are used to assess a range of knowledge, including a range of specific technical subjects.

Read our guide on how to avoid plagiarism in your assessments at Brunel.