MSc Statistics
Postgraduate
In Colchester
Description
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Type
Postgraduate
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Location
Colchester
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Duration
1 Year
About the course
Statistics is one of the most important fields of study in the world
The techniques we use to model and manipulate data guide the political, financial and social decisions that shape our modern society
If you are a logical person and enjoy solving problems, statistics at Essex is for you
Our Department of Mathematical Sciences embraces pure mathematics, applied mathematics and statistics, and operational research, and our course offers you the opportunity to study statistics alongside other mathematical subjects
Providing a balance of solid statistical theory and practical application, this course builds your knowledge in all areas of statistics, data analysis and probability
You also have the opportunity to specialise, taking optional modules in topics including:
Survey methodology
Operations research
Applied mathematics
Computer science
Our interdisciplinary research recognises that mathematics, including what can be very abstract mathematics, is an essential part of research in many other disciplines
Our department has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology
Our expert staff
Our Department of Mathematical Sciences is a small but influential department, so our students and staff know each other personally
You never need an appointment to see your tutors and supervisors, just knock on our office doors – we are one of the few places to have an open-door policy, and no issue is too big or small
Facilities
Location
Start date
Start date
Reviews
Subjects
- Statistics
- Mathematics
- GCSE Mathematics
- Staff
- Probability
- Financial Training
- Financial
Course programme
Postgraduate study is the chance to take your education to the next level. The combination of compulsory and optional modules means our courses help you develop extensive knowledge in your chosen discipline, whilst providing plenty of freedom to pursue your own interests. Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field, therefore to ensure your course is as relevant and up-to-date as possible your core module structure may be subject to change.
For many of our courses you’ll have a wide range of optional modules to choose from – those listed in this example structure are, in many instances, just a selection of those available. Our Programme Specification gives more detail about the structure available to our current postgraduate students, including details of all optional modules.
Year 1
Modelling Experimental Data
Statistical Methods
Stochastic Processes
Applied Statistics
Bayesian Computational Statistics
Research Methods
Dissertation
Nonlinear Programming (optional)
Financial Modelling (optional)
Research Methods in Finance: Empirical Methods in Finance (optional)
Machine Learning and Data Mining (optional)
Cloud Technologies and Systems (optional)
Time Series Econometrics (optional)
Panel Data Methods (optional)
Topics in Contemporary Social Theory (optional)
Introduction to Survey Design and Management (optional)
Applied Sampling (optional)
Teaching
Core components can be combined with optional modules, to enable you to gain either in-depth specialisation or a breadth of understanding
Learn to use LATEX to produce a document as close as possible to what professional mathematicians produce in terms of organisation, layout and type-setting
Our postgraduates are encouraged to attend conferences and seminars on a Thursday afternoon
Assessment
Courses are assessed on the results of your written examinations, together with continual assessments of your practical work and coursework
Dissertation
You will be provided with a list of dissertation titles or topics proposed by staff and it may be possible to propose a project of your own
Most dissertations are between 10,000 and 30,000 words in length. However, these are guidelines, not mandatory word counts
Close supervision by academic staff
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Additional information
MSc Statistics