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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

2024/25

UK £13,750

International £25,000

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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.

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

Year 1

Please note that all modules are subject to change.

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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 2.2 (or above) UK honours degree or equivalent, internationally recognised qualification in numerate disciplines with adequate content in statistics, including: Mathematics, Statistics, Computational Statistics, Biostastics, Medical Statistics, Social Statistics, Machine Learning, Stochastic models, Probability Statistics, Statistical Modelling, Applied Statistics or Econometrics, Economics, Actuarial Science, Mathematics for Data Science, Applied Mathematics.

Other academic profiles and students with relevant work experience will be considered on a case by case basis.'

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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 (min 5.5 in all areas)
  • Pearson: 59 (59 in all sub scores)
  • BrunELT: 58% (min 55% in all areas)
  • TOEFL: 77 (min R18, L17, S20, W17) 

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

2024/25 entry

UK

£13,750 full-time

£6,875 part-time

International

£25,000 full-time

£12,500 part-time

More information on any additional course-related costs.

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

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

Scholarships and bursaries

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Teaching and Learning

How the course will be delivered

Required equipment

How you'll learn on your course

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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.

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