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Masters Degrees (Mathematical Statistics)

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This course, commonly referred to as Part III, is a one-year taught Master's course in mathematics. Read more
This course, commonly referred to as Part III, is a one-year taught Master's course in mathematics. It is an excellent preparation for mathematical research and it is also a valuable course in mathematics and in its applications for those who want further training before taking posts in industry, teaching, or research establishments.

Students admitted from outside Cambridge to Part III study towards the Master of Advanced Study (MASt). Students continuing from the Cambridge Tripos for a fourth year, study towards the Master of Mathematics (MMath). The requirements and course structure for Part III are the same for all students irrespective of whether they are studying for the MASt or MMath degree.

There are over 200 Part III (MASt and MMath) students each year; almost all are in their fourth or fifth year of university studies. There are normally about 80 courses, covering an extensive range of pure mathematics, probability, statistics and the mathematics of operational research, applied mathematics and theoretical physics. They are designed to cover those advanced parts of the subjects that are not normally covered in a first degree course, but which are an indispensable preliminary to independent study and research. Students have a wide choice of the combination of courses that they offer, though naturally they tend to select groups of cognate courses. Normally classes are provided as back-up to lecture courses.

Visit the website: http://www.graduate.study.cam.ac.uk/courses/directory/mapmasmst

Course detail

The structure of Part III is such that students prepare between six and nine lecture courses for examination. These lecture courses may be selected from the wide range offered by both Mathematics Departments. As an alternative to one lecture course, an essay may be submitted. Examinations usually begin in late May, and are scheduled in morning and afternoon sessions, over a period of about two weeks. Two or three hours are allocated per paper, depending on the subject. Details of the courses for the current academic year are available on the Faculty of Mathematics website. Details for subsequent years are expected to be broadly similar, although not identical.

Most courses in the Part III are self-contained. Students may freely mix courses offered by the two Mathematics Departments. Courses are worth either two or three credit units depending on whether they last for 16 or 24 lectures respectively. Candidates for Part III may offer a maximum of 19 credit units for examination. In the past it has been recommended that candidates offer between 17 and 19 units. An essay (should a candidate choose to submit one) counts for 3 credit units. Part III is graded Distinction, Merit, Pass or Fail. A Merit or above is the equivalent of a First Class in other Parts of the Mathematical Tripos.

Learning Outcomes

After completing Part III, students will be expected to have:

- Studied advanced material in the mathematical sciences to a level not normally covered in a first degree;
- Further developed the capacity for independent study of mathematics and problem solving at a higher level;
- Undertaken (in most cases) an extended essay normally chosen from a list covering a wide range of topics.

Students are also expected to have acquired general transferable skills relevant to mathematics as outlined in the Faculty
Transferable Skills Statement http://www.maths.cam.ac.uk/undergrad/course/transferable_skills.pdf .

Format

Courses are delivered predominantly by either 16 or 24 hours of formal lectures, supported by additional examples classes. As an alternative to one lecture course, an essay may be submitted. There is also the possibiltiy of taking a reading course for examination. There are normally additional non-examinable courses taught each year.

Twice a year students have an individual meeting with a member of academic staff to discuss their progress in Part III. Students offering an essay as part of their degree may meet their essay supervisor up to three times during the academic year.

Assessment

Candidates may substitute an essay for one lecture course. The essay counts for 3 credit units.

Lecture courses are assessed by formal examination. Courses are worth either two or three credit units depending on whether they are 16 or 24 hours in length respectively. A 16 hour course is assessed by a 2 hour examination and a 24 hour course, a 3 hour examination. Candidates for Part III may offer a maximum of 19 credit units for examination. In the past it has been recommended that candidates offer between 17 and 19 units.

Continuing

MASt students wishing to apply for the PhD must apply via the Graduate Admissions Office for readmission by the relevant deadline. Applicants will be considered on a case by case basis and offer of a place will usually include an academic condition on their Part III result.

How to apply: http://www.graduate.study.cam.ac.uk/applying

Funding Opportunities

There are no specific funding opportunities advertised for this course. For information on more general funding opportunities, please follow the link below.

General Funding Opportunities http://www.graduate.study.cam.ac.uk/finance/funding

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International Master's in Statistics - MSc. https://www.kent.ac.uk/courses/postgraduate/163/international-masters-statistics. Read more
International Master's in Statistics - MSc: https://www.kent.ac.uk/courses/postgraduate/163/international-masters-statistics

Overview

The International Master’s in Statistics develops your practical, statistical and computing skills to prepare you for a professional career in statistics or as a solid basis for further research in the area.

The programme has been designed to provide a deep understanding of the modern statistical methods required to model and analyse data. You will benefit from a thorough grounding in the ideas underlying these methods and develop your skills in key areas such as practical data analysis and data modelling.

It has been accredited by the Royal Statistical Society (RSS) and equips aspiring professional statisticians with the skills they need for posts in industry, government, research and teaching. It also enables you to develop a range of transferable skills that are attractive to employers within the public and private sectors.

Students whose mathematical and statistical background is insufficient for direct entry on to the appropriate programme, may apply for this course. The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. This is followed by the MSc in Statistics.

International Master's in Statistics with Finance - MSc: https://www.kent.ac.uk/courses/postgraduate/164/international-masters-statistics-finance

Overview

This programme, accredited by the Royal Statistical Society (RSS), equips aspiring professional statisticians with the skills they will need for posts in industry, government, research and teaching. It is suitable preparation too for careers in other fields requiring a strong statistical background.

Students whose mathematical and statistical background is insufficient for direct entry on to the appropriate programme, may apply for this course. The first year of the programme gives you a strong background in statistics, including its mathematical aspects, equivalent to the Graduate Diploma in Statistics. This is followed by the MSc in Statistics with Finance.

About the School of Mathematics, Statistics and Actuarial Science (SMSAS)

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.

The Statistics Group is forward-thinking, with varied research, and received consistently high rankings in the last two Research Assessment Exercises.

Statistics at Kent provides:

- a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers

- teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work

- advanced and accessible computing and other facilities

- a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

Research areas

Biometry and ecological statistics
Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.

Bayesian statistics
Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.
Bioinformatics, statistical genetics and medical statistics
Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.

Nonparametric statistics
Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

Professional recognition

The taught programmes in Statistics and Statistics with Finance provide exemption from the professional examinations of the Royal Statistical Society and qualification for Graduate Statistician status.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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When you study mathematics and statistics at the University of Helsinki, some of the best mathematicians and statisticians in the world will be your instructors. Read more
When you study mathematics and statistics at the University of Helsinki, some of the best mathematicians and statisticians in the world will be your instructors. Studies in this Master’s programme will give you a solid basis for maths and statistics applications. Graduates of this Master’s programme find employment as researchers, teachers, and in demanding expert posts in the public and private sectors in Finland and abroad.

The Master’s programme in mathematics and statistics is based on top research. The teaching within the sub-programmes at the University of Helsinki follows a high standard and is highly valued, not just within Finnish academia but in global university rankings. Upon graduating from this Master’s programme, you will:
-Be an expert in the methods of mathematics or statistics.
-Have mastered the basics of another scientific discipline.
-Be able to apply scientific knowledge and methods.
-Be able to follow developments in mathematics and statistics.
-Know how to think critically, argue a point, and solve problems.
-Have excellent interaction skills and be assertive and creative.
-Understand the principles of ethical and sustainable development.
-Be well prepared to work as an expert and developer in your field.
-Be prepared for scientific postgraduate studies.

The University of Helsinki will introduce annual tuition fees to foreign-language Master’s programmes starting on August 1, 2017 or later. The fee ranges from 13 000-18 000 euros. Citizens of non-EU/EEA countries, who do not have a permanent residence status in the area, are liable to these fees. You can check this FAQ at the Studyinfo website whether or not you are required to pay tuition fees.

Programme Contents

The Master’s programme consists of courses in mathematics, applied mathematics, and statistics. The courses include group and lecture instruction, exercises, literature, and workshops. Most courses also include exams or project assignments. In addition, you can complete some courses independently, by taking literature-based exams. The instructors in this programme have received prizes for their high standard of teaching. The teaching methods used in the subjects in this Master's programme have been widely recognised in the media.

Selection of the Major

The specialisation subjects within the programme are:
-Analysis
-Mathematical physics and stocastics
-Applied analysis
-Computational science
-Mathematical logic
-Mathematical modelling
-Insurance and financial mathematics
-Algebra and topology
-Statistics
-European Master in Official Statistics, EMOS (based on the statistics education in the Faculty of Social Sciences).

You will select your specialisation subject during your first year.

Programme Structure

The Master’s programme comprises 120 credits, which you can complete in two years. The degree in mathematics includes:
-85 credits of advanced courses, including the Master’s thesis (Pro gradu, 30 credits).
-35 credits of other courses from your own or other programmes.
-Working-life orientation and career planning.
-Personal study plan.

The degree in statistics includes:
-25 credits of advanced mathematics courses.
-60 credits of advanced statistics courses, including the Master’s thesis (Pro gradu, 30 credits).
-35 credits of other courses e.g. more advanced courses in statistics, or intermediate courses in some other subject, in which you included basic courses in your BSc degree, or, module/s from other university programmes.
-Working-life orientation and career planning.
-Personal study plan.

The European Master in Official Statistics sub-programme includes:
-85 credits of advanced courses in statistics or mathematics, including the Master’s thesis (Pro gradu, 30 credits) and a traineeship.
-35 credits of other courses from your own or other programmes.
-Working-life orientation and career planning.
-Personal study plan.

Career Prospects

Graduates of the Master’s programme can find employment outside the university or continue with one of the doctoral programmes in mathematics and statistics. The Master’s programme will give you excellent capabilities for work in the public or private sector as an expert in mathematics and statistics, skills that are very sought after in the job market both in Finland and abroad. The banking, investment, and insurance fields, for instance, value mathematicians and statisticians very highly internationally. Many of our graduates work in research and development or as teachers in various educational institutions. Graduates from this programme have excellent chances to find employment corresponding to their education.

Internationalization

The international nature of the programme is implemented in many ways:
-Research within the disciplines of the degree programme is of high international standard and is highly regarded.
-Teaching staff and research collaboration within the programme are international.
-The atmosphere of the programme is international, several international students are admitted each year.
-Theses and projects may be completed within international projects.
-There are opportunities for a student exchange period in many foreign universities.

Research Focus

The research focus within the disciplines in the degree programme are e.g.
-Geometric analysis and measurement theory
-Analysis in metric spaces
-Partial differential equations
-Functional analysis
-Harmonic analysis
-Mathematical physics
-Stochastics
-Inversion problems
-Mathematical logic and set theory
-Biomathematics
-Time series analysis
-Biometry
-Econometry
-Psychometrics
-Social statistics

The programme is part of the Analyysin ja dynamiikan (Analysis and dynamics) and the Inversio-ongelmien (Inversion problems) centres of excellence.

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These programmes offers the opportunity to begin or consolidate your research career under the guidance of internationally renowned researchers and professionals in the School of Mathematics, Statistics and Actuarial Science (SMSAS). Read more
These programmes offers the opportunity to begin or consolidate your research career under the guidance of internationally renowned researchers and professionals in the School of Mathematics, Statistics and Actuarial Science (SMSAS).

Research interests are diverse and include: Bayesian statistics; bioinformatics; biometry; ecological statistics; epidemic modelling; medical statistics; nonparametric statistics and semi-parametric modelling; risk and queueing theory; shape statistics.

Visit the website https://www.kent.ac.uk/courses/postgraduate/169/statistics

About the School of Mathematics, Statistics and Actuarial Science (SMSAS):

The School has a strong reputation for world-class research and a well-established system of support and training, with a high level of contact between staff and research students. Postgraduate students develop analytical, communication and research skills. Developing computational skills and applying them to mathematical problems forms a significant part of the postgraduate training in the School. We encourage all postgraduate statistics students to take part in statistics seminars and to help in tutorial classes.

The Statistics Group is forward-thinking, with varied research, and received consistently high rankings in the last two Research Assessment Exercises.

Statistics at Kent provides:

- a programme that gives you the opportunity to develop practical, mathematical and computing skills in statistics, while working on challenging and important problems relevant to a broad range of potential employers

- teaching and supervision by staff who are research-active, with established reputations and who are accessible, supportive and genuinely interested in your work

- advanced and accessible computing and other facilities

- a congenial work atmosphere with pleasant surroundings, where you can socialise and discuss issues with a community of other students.

Course structure

The research interests of the group are in line with the mainstream of statistics, with emphasis on both theoretical and applied subjects.

There are strong connections with a number of prestigious research universities such as Texas A&M University, the University of Texas, the University of Otago, the University of Sydney and other research institutions at home and abroad.

The group regularly receives research grants. The EPSRC has awarded two major grants, which support the National Centre for Statistical Ecology (NCSE), a joint venture between several institutions. A BBSRC grant supports stochastic modelling in bioscience.

Research areas

- Biometry and ecological statistics

Specific interests are in biometry, cluster analysis, stochastic population processes, analysis of discrete data, analysis of quantal assay data, overdispersion, and we enjoy good links within the University, including the School of Biosciences and the Durrell Institute of Conservation and Ecology. A recent major joint research project involves modelling the behaviour of yeast prions and builds upon previous work in this area. We also work in collaboration with many external institutions.

- Bayesian statistics

Current work includes non-parametric Bayes, inference robustness, modelling with non-normal distributions, model uncertainty, variable selection and functional data analysis.

- Bioinformatics, statistical genetics and medical statistics

Research covers bioinformatics (eg DNA microarray data), involving collaboration with the School of Biosciences. Other interests include population genetics, clinical trials and survival analysis.

- Nonparametric statistics

Research focuses on empirical likelihood, high-dimensional data analysis, nonlinear dynamic analysis, semi-parametric modelling, survival analysis, risk insurance, functional data analysis, spatial data analysis, longitudinal data analysis, feature selection and wavelets.

Careers

Students often go into careers as professional statisticians in industry, government, research and teaching but our programmes also prepare you for careers in other fields requiring a strong statistical background. You have the opportunity to attend careers talks from professional statisticians working in industry and to attend networking meetings with employers.

Recent graduates have started careers in diverse areas such as the pharmaceutical industry, financial services and sports betting.

Find out how to apply here - https://www.kent.ac.uk/courses/postgraduate/apply/

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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. Read more
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.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Working in industries such as health, business, social care and finance, graduates are consistently in demand, working on projects such as efficacy of social policy, comparable data of cardiac rehabilitation and manipulation of raw data for academic research.

Our Masters graduates have progressed into careers in banking and finance, actuarial sciences, biological sciences, market research and statistics, management and consultancy etc.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-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)

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The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. Read more

Mission and goals

The objective of this programme of study is to prepare professionals able to deal with complex systems using sophisticated mathematical tools, yet with an engineering attitude. It harmonises a solid scientific background with a command of advanced methodologies and technologies. The programme is characterised by a continuous synergy between Applied Mathematics and Engineering disciplines- The students may choose among three specialisations:
- Computational Science and Engineering
- Applied Statistics
- Quantitative Finance

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Career opportunities

The professional opportunities offered by this course are rather ample and varied: engineering consultancy companies that deal with complex computational problems; manufacturing or civil engineering companies where analyses based on the use of advanced mathematical tools are needed; banks, insurance companies and financial institutions making use of quantitative finance for risk analysis or forecast; companies that require statistical interpretation and the processing of complex data, or the simulation of different scenarios; public and private research institutes and laboratories.

Eligible students

Students holding a Bachelor degree in Mathematical Engineering, or in a related area with a solid background in the core disciplines of the programme, i.e. Applied Mathematics, Computer Science, Applied Physics or other Engineering disciplines are eligible for application. In particular, eligible students' past studies must include courses in different areas of Engineering (among Informatics, Economics & Business Organization, Electrotechnics, Automation, Electronics, Applied Physics, Civil Engineering) for at least 25% of the overall courses, as well as courses in different areas of Mathematics (Mathematical Analysis, Linear Algebra, Geometry, Probability, Statistics, Numerical Analysis, Optimization) for at least 33% of the overall courses.
The following tracks are available:
1. Computational Science and Engineering
2. Applied Statistics
3. Quantitative Finance

Eligible students must clearly specify the track they are applying for in their motivation letter.

Presentation

See http://www.polinternational.polimi.it/uploads/media/Mathematical_Engineering.pdf
The Master of Science in Mathematical Engineering (MSME) aims to form an innovative and flexible professional profile, endowed with a wide spectrum of basic scientific notions and engineering principles, together with a deep knowledge of modern pure and applied mathematical techniques. MSME is characterized by a continuous synergy between Mathematics and Engineering methods, oriented to the modelling, analysis and solution of complex planning, control and management problems, and provides the students with the possibility to face problems from various scientific, financial and/or technological areas. The MSME graduates can find employment in Engineering companies specialized in handling complex computational problems, requiring a multidisciplinary knowledge; in companies manufacturing industrial goods for which design analysis based on the use of advanced mathematical procedures are required; in service societies, banks, insurance companies, finance or consultant agencies for the statistical interpretation and the simulation of complex situations related to the analysis of large number of data (e.g. management and optimization of services, data mining, information retrieval) or for handling financial products and risk management; in public and private institutions. The programme is taught in English.

Subjects

Three main tracks available:
1. Computational Science for Engineering
Real and functional analysis; algorithms and parallel programming; numerical and theoretical analysis for partial differential equations; fluid mechanics; computational fluid dynamics advanced programming techniques for scientific computing;

2. Statistics
Real and functional analysis; algorithms and parallel programming; stochastic dynamical models; applied statistics, model identification and data analysis; Bayesian statistics

3. Mathematical Finance
Real and functional analysis; algorithms and parallel programming; stochastic differential equations; mathematical finance; financial engineering; model identification and data analysis.

In the motivation letter the student must clearly specify the track he/she is applying for.

See the website http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

For contact information see here http://www.polinternational.polimi.it/educational-offer/laurea-magistrale-equivalent-to-master-of-science-programmes/mathematical-engineering/

Find out how to apply here http://www.polinternational.polimi.it/how-to-apply/

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Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Read more
Businesses, organisations, and individuals all strive to work as effectively as possible. Operational research uses advanced statistical and analytical methods to help improve the complex decision-making processes to deliver a product or service. Working in this field, you might be identifying future needs for a business, evaluating the time-life value of a customer, or carrying out computer simulations for airlines.

Our MSc Statistics and Operational Research will appeal if your first degree included mathematics as its major subject, and we expect you to have prior knowledge of statistics – for example significance testing or basic statistical distributions – and operational research such as linear programming.

You specialise in areas including:
-Continuous and discrete optimisation
-Time series econometrics
-Heuristic computation
-Experimental design
-Machine learning
-Linear models

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 of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00808&subgroup=2

Our expert staff

Our Department of Mathematical 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.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society, an active and social group where you can explore your interest in your subject with other students

Your future

Our MSc Statistics and Operational Research will equip you with employability skills like problem solving, analytical reasoning, data analysis, and mathematical modelling, as well as training you in independent work, presentation and writing skills.

Your exposure to current active research areas, such as decomposition algorithms on our module, Combinatorial Optimisation, prepares you for further study at doctoral level. Graduates of this course now hold key positions in government, business and academia.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Nonlinear Programming
-Combinatorial Optimisation
-Modelling Experimental Data (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)
-Applied Statistics (optional)
-Bayesian Computational Statistics
-Research Methods
-Dissertation
-Ordinary Differential Equations (optional)
-Graph Theory (optional)
-Partial Differential Equations (optional)
-Portfolio Management (optional)
-Machine Learning and Data Mining (optional)
-Evolutionary Computation and Genetic Programming (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)
-Applications of Data Analysis (optional)
-Mathematical Research Techniques Using Matlab (optional)

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Our Probability and Statistics research groups have a long-standing reputation and experience of offering this one year, high quality taught course in areas of Statistics leading to the degree of MSc. Read more
Our Probability and Statistics research groups have a long-standing reputation and experience of offering this one year, high quality taught course in areas of Statistics leading to the degree of MSc.

This course offers a thorough professional training which prepares students to embark on statistical careers in a variety of areas. There is a shortage of statisticians trained to postgraduate level in the UK and the employment prospects for such people remain good. The course also provides a very good foundation for further study at PhD level.

Our newly revised MSc programme in Statistics allows students to take one of two different MSc degrees, depending on their interests and career aspirations. There is the main programme in Statistics and an associated pathway in Financial Statistics. Each is built around a common core of five units and then students study an additional set of three specialist units to make a total of eight in all.

Main Statistics pathway

Semester one
•Linear Models and Nonparametric Regression
•Statistical Computing
•Statistical Inference
•Multivariate Statistics

Semester two
•Generalized Linear Models and Survival Analysis
•Longitudinal Data Analysis
•Markov Chain Monte Carlo (MCMC)
•Design and Analysis of Experiments

This degree is accredited by the Royal Statistical Society.

Financial Statistics pathway

This comprises a core of five course units which are common to the main course, plus three specialist course units in financial statistics.

Semester one
•Linear Models and Nonparametric Regression
•Statistical Computing
•Statistical Modelling in Finance
•Extreme Values and Financial Risk

Semester two
•Generalized Linear Models and Survival Analysis
•Longitudinal Data Analysis
•Markov Chain Monte Carlo (MCMC)
•Time Series Analysis and Financial Forecasting

This degree is accredited by the Royal Statistical Society.

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The MSc Statistics and Applied Probability is suitable for students who wish to broaden and deepen their knowledge in both statistics and applied probability. Read more

Overview

The MSc Statistics and Applied Probability is suitable for students who wish to broaden and deepen their knowledge in both statistics and applied probability.

The course offers you the opportunity to further your knowledge in both of these areas, which will be beneficial for a professional career in statistics or as a solid basis for research in statistics or applied probability.

Topics include advanced stochastic processes, queueing processes, epidemic models and reliability, as well as most of those listed for the MSc Statistics.

This course is accredited by the Royal Statistical Society

Key facts:
- This course is informed by the work being carried out in the Statistics and Probability research group.
- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.
- In the latest independent Research Assessment Exercise, the School ranked 8th in the UK in "research power" across the three subject areas within the School of Mathematical Sciences (Pure Mathematics, Applied Mathematics, Statistics and Operational Research).
- This course is accredited by the Royal Statistical Society.

Modules

Advanced Stochastic Processes

Applications of Statistics

Computational Statistics

Fundamentals of Statistics

Medical Statistics

Statistics Dissertation

Time Series and Forecasting

Topics in Biomedical Statistics

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information



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Specialised statistical methods are hugely important in dealing with particular problems of economic data. Read more
Specialised statistical methods are hugely important in dealing with particular problems of economic data. For instance, time series econometrics provides methods for analysing the dynamic processes that are often found in macroeconomics, while other techniques are required for analysing the stock market and other financial data.

Econometrics can be described as the application of statistics in an economic context so this course will interest you if your first degree included some training in both statistics and economics.

You study topics including:
-Methods of linear regression and hypothesis testing
-Bayesian statistical modelling and methods
-Actuarial modelling and time series models
-Applied statistics
-Game theory

Our Department of Mathematical Sciences has an international reputation in many areas including semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology.

You are also taught within our Department of Economics, who are rated consistently highly for student satisfaction and are Top 5 in the UK for research, with over 90% of their research rated as ‘world-leading’ or ‘internationally excellent’ (REF 2014).

This course can also be studied to a PGDip level - for more information, please view this web-page: http://www.essex.ac.uk/courses/details.aspx?mastercourse=PG00807&subgroup=2

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.

Our staff have published several well-regarded text books and are world leaders in their individual specialisms, with their papers appearing in learned journals like Communications in Algebra, Studia Logica, International Journal of Algebra and Computation, SIAM Journal in Optimization, IEEE Evolutionary Computation, Computers and Operations Research, Ecology, Journal of Mathematical Biology, and Journal of Statistical Applications in Genetics and Molecular Biology.

The academic staff in our Department of Economics are also exceptionally well-regarded; our researchers are at the forefront of their field and have even received MBEs.

Many of our researchers in economics also provide consultancy services to businesses in London and other major financial centres, helping us to develop research for today's society as well as informing our teaching for the future.

Specialist facilities

-Unique to Essex is our renowned Maths Support Centre, which offers help to students, staff and local businesses on a range of mathematical problems. Throughout term-time, we can chat through mathematical problems either on a one-to-one or small group basis
-We have our own computer labs for the exclusive use of students in the Department of Mathematical Sciences – in addition to your core maths modules, you gain computing knowledge of software including Matlab and Maple
-Extensive software for quantitative analysis is available in all computer labs across the university
-We host regular events and seminars throughout the year
-Our students run a lively Mathematics Society where you can explore your interest in your subject with other students
-Alternatively, our Economics Society is an active and social group

Your future

Our graduates are sought after by employers in banking, investment and forecasting, local government and other fields.

We also offer supervision for PhD, MPhil and MSc by Dissertation. We have an international reputation in many areas such as semi-group theory, optimisation, probability, applied statistics, bioinformatics and mathematical biology, and our staff are strongly committed to research and to the promotion of graduate activities.

We additionally work with our Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

Example structure

-Modelling Experimental Data (optional)
-Statistical Methods (optional)
-Stochastic Processes (optional)
-Applied Statistics (optional)
-Bayesian Computational Statistics (optional)
-Research Methods
-Dissertation
-Mathematics of Portfolios (optional)
-Financial Derivatives (optional)
-Partial Differential Equations (optional)
-Econometric Methods (optional)
-Economics of Financial Markets (optional)
-Game Theory and Applications (optional)
-Time Series Econometrics (optional)
-Panel Data Methods (optional)

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The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. Read more

Mathematical Biology at Dundee

The University of Dundee has a long history of mathematical biology, going back to Professor Sir D'Arcy Wentworth Thompson, Chair of Natural History, 1884-1917. In his famous book On Growth and Form (where he applied geometric principles to morphological problems) Thompson declares:

"Cell and tissue, shell and bone, leaf and flower, are so many portions of matter, and it is in obedience to the laws of physics that their particles have been moved, molded and conformed. They are no exceptions to the rule that God always geometrizes. Their problems of form are in the first instance mathematical problems, their problems of growth are essentially physical problems, and the morphologist is, ipso facto, a student of physical science."

Current mathematical biology research in Dundee continues in the spirit of D'Arcy Thompson with the application of modern applied mathematics and computational modelling to a range of biological processes involving many different but inter-connected phenomena that occur at different spatial and temporal scales. Specific areas of application are to cancer growth and treatment, ecological models, fungal growth and biofilms. The overall common theme of all the mathematical biology research may be termed"multi-scale mathematical modelling" or, from a biological perspective, "quantitative systems biology" or"quantitative integrative biology".

The Mathematical Biology Research Group currently consists of Professor Mark Chaplain, Dr. Fordyce Davidson and Dr. Paul Macklin along with post-doctoral research assistants and PhD students. Professor Ping Lin provides expertise in the area of computational numerical analysis. The group will shortly be augmented by the arrival of a new Chair in Mathematical Biology (a joint Mathematics/Life Sciences appointment).

As a result, the students will benefit directly not only from the scientific expertise of the above internationally recognized researchers, but also through a wide-range of research activities such as journal clubs and research seminars.

Aims of the programme

1. To provide a Masters-level postgraduate education in the knowledge, skills and understanding of mathematical biology.
2. To enhance analytical and critical abilities and competence in the application of mathematical modeling techniques to problems in biomedicine.

Prramme Content

This one year course involves taking four taught modules in semester 1 (September-December), followed by a further 4 taught modules in semester 2 (January-May), and undertaking a project over the Summer (May-August).

A typical selection of taught modules would be:

Dynamical Systems
Computational Modelling
Statistics & Stochastic Models
Inverse Problems
Mathematical Oncology
Mathematical Ecology & Epidemiology
Mathematical Physiology
Personal Transferable Skills

Finally, all students will undertake a Personal Research Project under the supervision of a member of staff in the Mathematical Biology Research Group.

Methods of Teaching

The programme will involve a variety of teaching formats including lectures, tutorials, seminars, journal clubs, case studies, coursework, and an individual research project.

Taught sessions will be supported by individual reading and study.

Students will be guided to prepare their research project plan and to develop skills and competence in research including project management, critical thinking and problem solving, project reporting and presentation.

Career Prospects

The Biomedical Sciences are now recognizing the need for quantitative, predictive approaches to their traditional qualitative subject areas. Healthcare and Biotechnology are still fast-growing industries in UK, Europe and Worldwide. New start-up companies and large-scale government investment are also opening up employment prospects in emerging economies such as Singapore, China and India.

Students graduating from this programme would be very well placed to take advantage of these global opportunities.

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Medical statistics is a fundamental scientific component of health research. Medical statisticians interact with biomedical researchers, epidemiologists and public health professionals and contribute to the effective translation of scientific research into patient benefits and clinical decision-making. Read more
Medical statistics is a fundamental scientific component of health research. Medical statisticians interact with biomedical researchers, epidemiologists and public health professionals and contribute to the effective translation of scientific research into patient benefits and clinical decision-making. As new biomedical problems emerge, there are exciting challenges in the application of existing tools and the development of new superior models.

Degree information

The UCL Medical Statistics degree provides students with a sound background in theoretical statistics as well as practical hands-on experience in designing, analysing and interpreting health studies, including trials and observational studies. The taught component equips students with analytical tools for health care economic evaluation, and the research project provides experience in using real clinical datasets.

Students undertake modules to the value of 180 credits.

The programme consists of a foundation course, six core modules (90 credits) two optional modules (30 credits) and the research dissertation (60 credits).

Core modules
-Foundation Course (not credit bearing)
-Statistical Inference
-Statistical Models and Data Analysis
-Medical Statistics I
-Medical Statistics II
-Statistical Computing
-Applied Bayesian Methods

Optional modules - at least one from:
-Statistics for Interpreting Genetic Data
-Bayesian Methods in Health Economics

and at least one from:
-Epidemiology
-Statistical Design of Investigations

Dissertation/report
All MSc students undertake an individual research project, culminating in a dissertation of approximately 10,000–12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. External organisations deliver technical lectures and seminars where possible. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics, for example, the presentation of statistical graphs and tables.

Careers

Medical statisticians enable the application of the best possible quantitative methods in health research and assist in the reliable translation of research findings to public and patients’ health care.

The National Institute of Health Research (NIHR) has identified Medical Statistics as one of the priority areas in their capacity building strategy and has awarded UCL two studentships annually for this MSc.

Top career destinations for this degree:
-Graduate Bio-Statistician, PRA International
-Statistical and Epidemiological Modeller, University of Oxford
-Biostatistician, Boehringer Ingelheim
-PhD Statistical Science, University College London (UCL)

Employability
There is an acute shortage of medical statisticians in the UK and employment opportunities are excellent. Recent graduates from this programme have been employed by clinical trials units, pharmaceutical industry, NHS trusts and Universities (e.g. London School of Hygiene and Tropical Medicine, UCL).

Why study this degree at UCL?

One of the strengths of UCL Statistical Science is the breadth of expertise on offer; the research interests of staff span the full range from foundations to applications, and make important original contributions to the development of statistical science.

UCL is linked with four NHS hospital trusts and hosts three biomedical research centres, four clinical trial units and an Institute of Clinical Trials and Methodology. Established links between the Department of Statistical Science, the NIHR UCLH/UCL Biomedical Research Centre and the Clinical Trial Units provide high-quality biomedical projects for Master's students and opportunities for excellent postgraduate teaching and medical research.

The programme has been accredited by the Royal Statistical Society. Graduates will automatically be granted the society's Graduate Statistician status on application.

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The MSc Statistics offers a modern advanced curriculum in statistics which will enable you to broaden and deepen your understanding of the subject and its applications. Read more

Overview

The MSc Statistics offers a modern advanced curriculum in statistics which will enable you to broaden and deepen your understanding of the subject and its applications.

The programme will provide you with specific techniques and skills suitable for a professional career in statistics or as a solid basis for research in the area.

Optional topics typically include generalised linear models, Markov Chain Monte Carlo, the bootstrap, multivariate analysis, spatial statistics, time series and forecasting, multilevel models, stochastic finance, and shape and image analysis.

This course is accredited by the Royal Statistical Society.

Key facts:

- This course is informed by the work being carried out in the Statistics and Probability research group.

- The School of Mathematical Sciences is one of the largest and strongest mathematics departments in the UK, with over 50 full-time academic staff.

- In the latest independent Research Assessment Exercise, the School ranked 8th in the UK in "research power" across the three subject areas within the School of Mathematical Sciences (Pure Mathematics, Applied Mathematics, Statistics and Operational Research).

Modules

Advanced Stochastic Processes

Applications of Statistics

Computational Statistics

Fundamentals of Statistics

Medical Statistics

Statistics Dissertation

Time Series and Forecasting

Topics in Biomedical Statistics

English language requirements for international students

IELTS: 6.0 (with no less than 5.5 in any element)

Further information



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High-level training in statistics and the modelling of random processes for applications in science, business or health care. Read more
High-level training in statistics and the modelling of random processes for applications in science, business or health care.

For many complex systems in nature and society, stochastics can be used to efficiently describe the randomness present in all these systems, thereby giving the data greater explanatory and predictive power. Examples include statistical mechanics, financial markets, mobile phone networks, and operations research problems. The Master’s specialisation in Applied Stochastics will train you to become a mathematician that can help both scientists and businessmen make better decisions, conclusions and predictions. You’ll be able to bring clarity to the accumulating information overload they receive.

The members of the Applied Stochastics group have ample experience with the pure mathematical side of stochastics. This area provides powerful techniques in functional analysis, partial differential equations, geometry of metric spaces and number theory, for example. The group also often gives advice to both their academic colleagues, and organisations outside of academia. They will therefore not only be able to teach you the theoretical basis you need to solve real world stochastics problems, but also to help you develop the communications skills and professional expertise to cooperate with people from outside of mathematics.

See the website http://www.ru.nl/masters/mathematics/stochastics

Why study Applied Stochastics at Radboud University?

- This specialisation focuses both on theoretical and applied topics. It’s your choice whether you want to specialise in pure theoretical research or perform an internship in a company setting.
- Mathematicians at Radboud University are expanding their knowledge of random graphs and networks, which can be applied in the ever-growing fields of distribution systems, mobile phone networks and social networks.
- In a unique and interesting collaboration with Radboudumc, stochastics students can help researchers at the hospital with very challenging statistical questions.
- Because the Netherlands is known for its expertise in the field of stochastics, it offers a great atmosphere to study this field. And with the existence of the Mastermath programme, you can follow the best mathematics courses in the country, regardless of the university that offers them.
- Teaching takes place in a stimulating, collegial setting with small groups. This ensures that you’ll get plenty of one-on-one time with your thesis supervisor at Radboud University .
- More than 85% of our graduates find a job or a gain a PhD position within a few months of graduating.

Career prospects

Master's programme in Mathematics

Mathematicians are needed in all industries, including the banking, technology and service industries, to name a few. A Master’s in Mathematics will show prospective employers that you have perseverance, patience and an eye for detail as well as a high level of analytical and problem-solving skills.

Job positions

The skills learned during your Master’s will help you find jobs even in areas where your specialised mathematical knowledge may initially not seem very relevant. This makes your job opportunities very broad and is the reason why many graduates of a Master’s in Mathematics find work very quickly.
Possible careers for mathematicians include:
- Researcher (at research centres or within corporations)
- Teacher (at all levels from middle school to university)
- Risk model validator
- Consultant
- ICT developer / software developer
- Policy maker
- Analyst

PhD positions

Radboud University annually has a few PhD positions for graduates of a Master’s in Mathematics. A substantial part of our students attain PhD positions, not just at Radboud University, but at universities all over the world.

Our research in this field

The research of members of the Applied Stochastics Department, focuses on combinatorics, (quantum) probability and mathematical statistics. Below, a small sample of the research our members pursue.

Eric Cator’s research has two main themes, probability and statistics.
1. In probability, he works on interacting particles systems, random polymers and last passage percolation. He has also recently begun working on epidemic models on finite graphs.
2. In statistics, he works on problems arising in mathematical statistics, for example in deconvolution problems, the CAR assumption and more recently on the local minimax property of least squares estimators.

Cator also works on more applied problems, usually in collaboration with people from outside statistics, for example on case reserving for insurance companies or airplane maintenance. He has a history of changing subjects: “I like to work on any problem that takes my fancy, so this description might be outdated very quickly!”

Hans Maassen researches quantum probability or non-commutative probability, which concerns a generalisation of probability theory that is broad enough to contain quantum mechanics. He takes part in the Geometry and Quantum Theory (GQT) research cluster of connected universities in the Netherlands. In collaboration with Burkhard Kümmerer he is also developing the theory of quantum Markov chains, their asymptotic completeness and ergodic theory, with applications to quantum optics. Their focal point is shifting towards quantum information and control theory, an area which is rapidly becoming relevant to experimental physicists.

Ross Kang conducts research in probabilistic and extremal combinatorics, with emphasis on graphs (which abstractly represent networks). He works in random graph theory (the study of stochastic models of networks) and often uses the probabilistic method. This involves applying probabilistic tools to shed light on extremes of large-scale behaviour in graphs and other combinatorial structures. He has focused a lot on graph colouring, an old and popular subject made famous by the Four Colour Theorem (erstwhile Conjecture).

See the website http://www.ru.nl/masters/mathematics/stochastics

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If numbers drive you, let Applied Statistics be your destination. Applied Statistics is a challenging field. With a Manderson degree, even when the numbers are stacked against them, our graduates are ready. Read more
If numbers drive you, let Applied Statistics be your destination. Applied Statistics is a challenging field. With a Manderson degree, even when the numbers are stacked against them, our graduates are ready.

Visit the website: http://manderson.cba.ua.edu/academics/departments/masters_program/master_of_science_in_applied_statistics

Course detail

The candidate for a graduate degree in Applied Statistics is normally expected to have completed courses in mathematics equivalent to two semesters of undergraduate calculus, and to have a working knowledge of computer programming and linear or matrix algebra.

Format and assessment

The M.S. degree in Applied Statistics requires 30 hours, half of which are track specific. There are two different tracks within this degree. These include: Statistics and Analytics. There are five required courses common to both tracks of study.

The electives may be earned in additional coursework with the approval of a faculty advisor. The program of related courses may vary from student to student and depends on the student's interests and academic background. When most of the coursework is completed, the student must pass a written comprehensive examination OR a professional exam such as the Actuarial P Exam, SAS Predictive Modeler Exam, or the ASQ Certified Quality Engineer Exam.

Required modules:

- ST 552 Applied Regression Analysis
- ST 553 Applied Multivariate Analysis
- ST 554 Mathematical Statistics I
- ST 555 Mathematical Statistics II
- ST 560 Statistical Methods

How to apply: http://graduate.ua.edu/prospects/application/

Fund your studies

Student Financial Aid provides comprehensive information and services regarding opportunities to finance the cost of education at The University of Alabama. We recognize that financial assistance is an important key to helping reach your educational and career goals. The financial aid staff is dedicated to making the financial aid process as straightforward as possible. Visit the website to find out more: http://financialaid.ua.edu/

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