MSc Statistics

Why take this course?

Statistics is an exciting subject with a rapidly increasing uptake in industry, commerce, government and academia. More and more professions, from the everyday to the exotic, depend on data and numerical reasoning. Data are not just numbers, but numbers that carry information about a specific setting and need to be interpreted within that setting. With the growth in the use of data comes a growing demand for the services of statisticians, although, as stated by the Royal Statistical Society, there is a lack of statisticians across all areas of applications in the UK and internationally. The need is especially pronounced in the finance, insurance and pharmaceutical industries. To help meet the demand for well trained statisticians, the School of Computing Sciences, in close collaboration with the School of Medicine and the School of Economics, offers a 1-year MSc in Statistics. Students will have the ability to choose specialist pathways out of medical, finance/insurance or knowledge discovery. The programme will prepare you for employment across a range of industries and for further education through a PhD in order to pursue a career in industrial or academic research.

Contact time

Students have on average 15 hours of contact time per week with teaching staff through lectures, laboratory sessions and seminars, though this may vary depending on module choices. Additionally, students should allocate at least 25 hours per week for study, coursework assignments and projects.

Teaching and Assessment

The MSc Statistics is normally a 12-month full-time intensive course but may be studied part-time over 24 months.

The course develops statistical thinking and provides training in the advanced aspects of statistical theory as well as familiarising students with applications of statistics and exposure to practical problems. Particular attention is given to statistical computing, with a core module in the first semester, and exposure to R and SAS statistical programming languages throughout the course. SAS is an industry standard both in pharmaceutical and in the financial services industry. R is a free flexible statistical environment used extensively in academia and in Research and Development.

The course is broadly divided into three parts. The first part is a set of core modules that are taught in the first semester. These include Computational Statistics, Inference, Statistical Modelling and Multivariate Analysis. The second part comprises specialised pathways in either financial statistics, medical statistics or knowledge discovery and takes place in the second semester. This allows students to build on or broaden their existing knowledge. The third part of the course is a three-month research project that is written up in the form of a dissertation. This may be based on a placement in a pharmaceutical or financial/insurance company. Part-time students follow a similar structure, except that the modules are spread over four semesters plus two summers.

Career opportunities

The School has an excellent record in both post-BSc and post-MSc placements and most of our recent graduates have found jobs.

SAS actively supports this new MSc in Statistics degree and is delighted that the University of East Anglia is expanding its portfolio of statistics courses. The University of East Anglia's reputation for research excellence means that SAS customers in the financial services and pharmaceutical industries will know where to look for their recruitment needs.

Geoffrey Taylor - SAS Academic Programme Manager

Course Organiser:Prof Elena Kulinskaya

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Entry Requirements Degree Subject: Mathematics, Statistics, Operational Research or a related subject Degree Classification: Good first degree (minimum 2.1 or equivalent). Students for whom English is a Foreign language

We welcome applications from students whose first language is not English. To ensure such students benefit from postgraduate study, we require evidence of proficiency in English. Our usual entry requirements are as follows:

IELTS: 6.5 (minimum 6.0 in all components)
TOEFL: Internet-based score of 88 (minimum 18 in listening, 21 speaking, 19 writing and 20 reading)
PTE (Pearson): 62 (minimum 55 in all components)
Test dates should be within two years of the course start date.

Other tests such as TOEIC and the Cambridge Certificate of Advanced English are also accepted by the university. Please check with the Admissions Office for further details including the scores or grades required.

INTO UEA and INTO UEA London run pre-sessional courses which can be taken prior to the start of your course. For further information and to see if you qualify please contact intopre-sessional@uea.ac.uk (INTO UEA Norwich) or pseuealondon@into.uk.com (INTO UEA London).

• 95% of research activity is classified as internationally leading, excellent or recognised in the 2008 Research Assessment Exercise.
• Teaching of the highest quality; rated “Commendable” in the most recent Teaching Quality Assessment.
• Our Masters programmes are accredited by the BCS - The Chartered Institute for IT to full Chartered IT Professional (CITP Further Learning Element) as well as leading to Chartered Engineer (CEng) status.
• The School maintains close links with industry and many of our student assignments relate to real world problems.
• The School of Computing Sciences leads the university in utilizing its internationally recognized research commercially, through SYS Consulting, its Consulting company and through Knowledge Transfer Partnerships.
• Our students also use their technical and entrepreneurial skills to play influential roles in the creation of companies such as Travel Republic, Evoke systems, Fyfo and Shoretech systems.

Come and Visit Us

Our Open Days will give you the opportunity to experience the University of East Anglia's unique campus atmosphere.

Fees and Funding Tuition Fees 2013/14

• UK/EU £5,000
• International £12,500

Funding

• International applicants applying to this course can be considered for one Faculty of Science half fees scholarship or one £2000 scholarship. The deadline is 1st April 2013.

Faculty of Science Scholarships
Students wishing to apply should submit an essay answering the following question in 1000 words: 'Statistics as the science of learning from Data (Jon Kettering, ASA President, 1997). Discuss'. Essays should be emailed to the Admissions Office. Please ensure you include your full name, the course you have applied to, and your applicant number in your email.

For more information please contact the Computing Sciences Postgraduate Admissions Office (cmp.pgt.admiss@uea.ac.uk).