Masters Degrees (Statistics)

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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About the MSc programme

The MSc Statistics (Social Statistics) aims to provide high-level training in the theory and application of modern statistical methods, with a focus on methods commonly used in the social sciences. You will gain insights into the design and analysis of social science studies, including large and complex datasets, study the latest developments in statistics, and learn how to apply advanced methods to investigate social science questions.

The programme includes two core courses which provide training in fundamental aspects of probability and statistical theory and methods, the theory and application of generalised linear models, and programming and data analysis using the R and Stata packages. These courses together provide the foundations for the optional courses on more advanced statistical modelling, computational methods and statistical computing. Options also include specialist courses from the Departments of Methodology, Economics, Geography and Social Policy. Students on the taught master’s programme will take optional courses to the value of two units, while those on the research track will substitute one unit with a dissertation.

Graduate destinations

The programme will prepare graduates for work within the public sector, market research organisations and survey research organisations, or for further study.

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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).

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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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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This Masters in Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics.

Why this programme

◾The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
◾Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
◾Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
◾You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
◾You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
◾You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
◾Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses (compulsory)
◾Bayesian statistics
◾Generalised linear models
◾Introduction to R programming
◾Probability 1
◾Regression models
◾Statistical inference 1
◾Statistics project and dissertation.

Optional courses (six chosen, but at least one course must be from Group 1)

Group 1
◾Data analysis
◾Professional skills.

Group 2
◾Biostatistics
◾Computational inference
◾Data management and analytics using SAS
◾Design of experiments
◾Environmental statistics
◾Financial statistics
◾Functional data analysis
◾Machine learning
◾Multivariate methods
◾Spatial statistics
◾Statistical genetics
◾Stochastic processes
◾Time series.

1 Any student who, in the course of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses can substitute these courses by any other optional course (including optional courses offered as part of the MRes in Advanced Statistics). The choice of substituting courses is subject to approval by the Programme Director.

Summer (May – August)
Statistics project and dissertation (60) - assessed by a dissertation.

Career prospects

Our graduates have an excellent track record of gaining employment in many sectors including finance, medical research, the pharmaceutical industry and government statistical services, while others have continued to a PhD.

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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. 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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This Masters in Environmental Statistics will provide you with knowledge and experience of the principles, theory and practical skills of statistics; previous study of statistics is not required.

Why this programme

◾The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
◾Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
◾Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
◾You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
◾You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
◾You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
◾Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Core courses (compulsory)
◾Bayesian statistics
◾Data analysis
◾Environmental statistics
◾Generalised linear models
◾Introduction to R programming
◾Principles of GIS (10)
◾Probability 1
◾Regression models
◾Spatial statistics
◾Statistical inference 1
◾Time series
◾Topographic mapping and landscape monitoring
◾Statistics project and dissertation.

Career prospects

Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.

Graduates of this programme have gone on to positions such as:
Research Officer Medical Statistics at Kenya Medical Research Institute (KEMRI) Welcome Trust.

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The Master of Science Degree in Applied Statistics brings together statistics, computer science, scientific research, and communication skills using the latest state-of -the-art technologies. It prepares students for immediate employment in a variety of high-paying industry positions or doctoral study in applied statistics or a related field.

Applied statisticians are in high demand in the current high-technology economy. Our program emphasizes a flexible curriculum that allows a wide variety of concentrations of application, including biology, mathematics, computer science, psychology, health sciences, business, pharmaceutical product development, and other self-designed multi-disciplinary concentrations. The Program also offers paid internship opportunities and flexible class offerings allowing for both full-time and part-time students.

We encourage students from diverse academic backgrounds to consider our program. Due to the interdisciplinary nature of the program, various undergraduate majors and interests are eligible for admissions.

Curriculum

After admission to the program, students will be allowed to select the thesis or nonthesis track for the M.S. in applied statistics. The thesis option replaces one of the elective classes and STA 531 with a six-credit thesis, to be initiated after the completion of STA 504 or STA 505 and STA 506.

Core modules for non-thesis option:

STA 505 Mathematical Statistics I or STA 504 Mathematical Statistics I with Calculus Review
STA 506 Mathematical Statistics II
STA 507 Introduction to Categorical Data Analysis
STA 511 Intro Stat Computing & Data Management
STA 512 Principles of Experimental Analysis
STA 513 Intermediate Linear Models
STA 514 Modern Experimental Design
STA 531 Topics In Applied Statistics

PLUS

Select two, three-credit electives from a selected area of concentration or STA 601 and one additional three-credit elective from a selected area of concentration

Core modules for thesis option:

STA 505 Mathematical Statistics I or STA 504 Mathematical Statistics I with Calculus Review
STA 506 Mathematical Statistics II
STA 507 Introduction to Categorical Data Analysis
STA 511 Intro Stat Computing & Data Management
STA 512 Principles of Experimental Analysis
STA 513 Intermediate Linear Models
STA 514 Modern Experimental Design
STA 609 Thesis I
STA 610 Thesis II

PLUS

Select one three-credit elective from a selected area of concentration or STA 601

Please see the website for more detailed information about these modules:

http://catalog.wcupa.edu/general-information/index-course-prefix-guide/course-index/graduate/sta/

Statistics Institute

The West Chester Statistics Institute (WCSI) provides statistical support, analysis, and education on a short or long term basis on specific projects for the West Chester University community and for regional business, industry, and academic institutions. WCSI is a non-profit organization, committed to providing hands-on, supervised educational opportunities for current West Chester University Applied Statistics Graduate Students. For more information please visit the website:

https://wcupa.edu/sciences-mathematics/mathematics/gradstat/statisticsInstitute.aspx

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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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This programme qualifies for the prestigious Data Lab Masters Scholarships. The award covers full tuition fee costs. For further information please see: Data Lab Masters Scholarships.

Why this programme

◾The Statistics Group at Glasgow is a large group, internationally renowned for its research excellence.
◾Our expertise spans topics including: biostatistics and statistical genetics; environmental statistics; statistical methodology; statistical modelling and the scholarship of learning and teaching in statistics.
◾Our Statistics MSc programmes benefit from close links lecturers have with industry and non-governmental organisations such as NHS and SEPA.
◾You will develop a thorough grasp of statistical methodology, before going on to apply statistical skills to solve real-life problems.
◾You will be equipped with the skills needed to begin a career as a professional statistician; previous study of statistics is not required.
◾You will be taught by world-leading experts in their fields and will participate in an extensive and varied seminar programme, are taught by internationally renowned lecturers and experience a wide variety of projects.
◾Our students graduate with a varied skill set, including core professional skills, and a portfolio of substantive applied and practical work.

Programme structure

Modes of delivery of the Masters across the Statistics programmes include lectures, laboratory classes, seminars and tutorials and allow students the opportunity to take part in lab, project and team work.

Courses include (twelve chosen)
◾Advanced Bayesian methods
◾Advanced data analysis
◾Bayesian statistics
◾Biostatistics
◾Computational inference
◾Data analysis
◾Data management and analytics using SAS
◾Design of experiments
◾Environmental statistics
◾Flexible regression
◾Financial statistics
◾Functional data analysis
◾Generalised linear models
◾Introduction to R programming
◾Linear mixed models
◾Machine learning
◾Multivariate methods
◾Principles of probability and statistics
◾Professional skills
◾Spatial statistics
◾Statistical genetics
◾Stochastic processes
◾Time series
◾Statistics project and dissertation.

Summer (May – August)
Statistics project and dissertation (60) - assessed by a dissertation

Career prospects

Our graduates have an excellent track record of gaining employment in many sectors including medical research, the pharmaceutical industry, finance and government statistical services, while others have continued to a PhD.

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About the MSc programme

The Financial Statistics stream of the MSc Statistics programme is mainly intended for students wishing to pursue careers in the finance industry or as a stepping stone towards PhD study in statistics for finance. It provides high-level training in statistics with applications in finance and econometrics. You will learn to analyse and critically interpret data, build statistical models of real situations, and use statistical software packages.

There are three compulsory courses. Statistical Inference: Principles, Methods and Computation will provide comprehensive coverage of fundamental aspects in probability and statistical methods and principles, while Time Series will provide solid training in statistical time series analysis. Modern data analytics, together with topics such as financial time series, asset pricing and portfolio choice, and some aspects of continuous-time finance will be provided in the course Financial Statistics. You will also learn to code in the R statistical computing environment.

Students on the taught master’s programme will take optional courses to the value of two units, including selected options from the Department of Finance. Those on the research track will substitute one unit with a dissertation, making the research track a 12 month programme.

Graduates of the programme are awarded Graduate Statistician (GradStat) status by the Royal Statistical Society if a specific combination of modules is taken.

Graduate destinations

The programme provides excellent opportunities for employment and further study. The programme is also conditionally accredited by the Royal Statistical Society. This means that although an accreditation is given, it will only lead to the award of ‘Graduate Statistician’ when students have taken a specific combination of modules.

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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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Our MSc in Operational Research and Applied Statistics aims to equip you with the necessary analytical skills, methods and ways of thinking to tackle and analyse complex organisational problems, help make better decisions, and to become confident statistical analysts.

This course is ideal training and experience for those looking for career opportunities in areas such as Operational Research, management science, statistics, management consultancy, business analytics, supply chain management, government operational research/statistics.

You will undertake case studies and project work which will give you the opportunity to put your skills into practice and provides valuable experience of working in the field. The dissertation project, typically undertaken with an industrial partner, will allow you to work with complex data in a creative manner and a problem-solving environment, as well as to communicate your ideas and findings effectively.

Distinctive features:

• Available on a one year full-time or three year part-time basis

• Acquire transferable operational research and statistical skills that are highly sought after in a broad range of sectors

• Learn from experts in the fields of Operational Research and Statistics

• Gain valuable work experience; we have some placement opportunities available with industrial partners in the UK and abroad

Structure

The course can be completed in one year with full-time study or in three years by part-time study.

The one-year course includes a three-month period working with a company on a real problem that they have identified. You will take 80 credits of core modules and 40 credits of optional modules in the taught component of the programme. This is followed by a 60 credit summer project.

As a part-time student you will typically need to be in the University for lectures and workshops for the equivalent of one day per week over 24 weeks each year. You will usually complete the taught component of the programme over two years with up to a further year to complete the project dissertation.

The programme will prepare you with essential techniques in Operational Research and Applied Statistics, and then allow you to select from optional courses in topics such as supply chain modelling, healthcare, and Statistics and Operational Research for Government (delivered with input from the Office for National Statistics and Welsh Assembly Government).

You will have the opportunity to put the theory into practice, through case studies and project work in the ‘real-world’. An important feature of the MSc is the project dissertation, allowing you to work with an external company.

For a list of modules for the FULL-TIME route, please see website:

http://www.cardiff.ac.uk/study/postgraduate/taught/courses/course/operational-research-and-applied-statistics-msc

For a list of the modules for the PART-TIME route, please see website:

http://www.cardiff.ac.uk/study/postgraduate/taught/courses/course/operational-research-and-applied-statistics-msc-part-time

Teaching

The methods of teaching we employ will vary from module to module, as appropriate depending on the subject matter and the method of assessment. We teach using a mixture of lectures, seminars, computer workshops and tutorials.

You will apply the skills you develop through presentations, research assignments, case studies and the summer project.

Assessment

During the course your development will primarily be monitored via tutorial sheets, with other means where appropriate.

Written examinations, often in combination with an in-course element forms overall assessment.

Career Prospects

This programme prepares you for a career in areas such as operational research, management science, statistics, risk analysis, financial modelling, actuarial risk and credit scoring, management consultancy, business analytics, supply chain management, government operational research /statistics.

Our School of Mathematics has well established and strong links with many employers of Operational Researchers and Applied Statisticians, who regularly offer projects and/or recruit our students.

If you prefer to continue on a more academic career pathway, you may choose to continue your studies with a PhD.

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This programme is an ideal opportunity to provide yourself with the analytical and statistical skill set necessary for success in industry, business or in the public sector. From day one you will find yourself working with multinational organisations on case studies to develop your abilities in applied analytics and statistics. Opportunities for summer projects in a wide range of industries are an integral part of the programme.

Full time study: This one year master programme is suitable for numerate graduates. The MSc programme lasts for twelve months.

The MSc programme in Operational Research and Statistics provides students with the ideal skill set in mathematical modelling, experimental design, statistical analysis, and numerical computation. This programme also provides soft skills such as communicating results to managers/executives. These prepare students to pursue a wide variety of career opportunities in industry, business or in the public sector.

A highlight of the programme is the three-month summer project: it may be either in Operational Research or Statistics (or the interface between the two). You will have the option to bid for an external project which is usually based at a nearby company and requires working on a real problem of practical importance to that company. You also have the option to work on an internal project which might involve data from external sources. The MSc project consists of an individual investigation and is under the supervision of a member of staff. This project enables students to integrate and consolidate skills learned on the course (and to fulfil deliverables for the sponsoring company in the case of an external project).

In summary, the learning and teaching aims of the programme are:
1. To give you knowledge of operational research techniques and applied statistical theory and methods at an advanced level;
2. To train you for careers as either an operational researcher or as a statistician.
3. To enable you to develop oral and written communication skills.
4. To give you experience of applications of operational research and statistical methods.

Introducing your course

Operational researchers and statisticians play a fundamental role in the modern world. This MSc will equip you with the necessary skills and knowledge to provide effective solutions to complex organizational challenges. This includes all key stages of solving real-world problems:

-Providing analytical understanding the problem; possibly through designing experiments, collecting and visualizing data
-Mathematically formulating the problem and finding solution approaches
-Providing statistical analysis and computation
-Presenting and communicating the results

The programme contains compulsory modules that provide the foundation in both Operational Research and Statistics, and optional modules for students to specialise in these two areas (or to have a balance portfolio of them).

The summer dissertation gives you an opportunity to develop your research skills, often in a commercial setting, and our industrial liaison team will work with you to find a project that suits your skills and ambitions.

What is Operational Research?

Operational Research is the application of scientific methods to the study of complex organisational problems. It is concerned with applying advanced analytical methods to make effective decisions in strategic planning or operational planning, and build more productive systems.

What is Statistics?

Statistics is concerned with decision-making in the face of uncertainty, and lies at the heart of the type of quantitative reasoning necessary for making important advances in the sciences, such as medicine and genetics, and for making important decisions in business and public policy.

Why do an MSc?

An MSc is generally accepted as being highly desirable for starting and developing a career in OR. The MSc is also a good preparation for research work.
http://www.southampton.ac.uk/cormsis/mscsummerproject/index.page
A highlight of the programme is the 3-month summer project. The student is usually placed with a nearby company and works on a real problem of practical importance to that company.

Environment

The Operational Research Group and the Statistics Group in Mathematics are strong committed teams of 20 lecturing staff and a number of research staff. The Groups teach a wide range of undergraduate and postgraduate courses, as well as undertaking consultancy work for outside organisations. Many of the staff are internationally known in their fields of research.
The 2013 QS subject world rankings places Statistics and Operational Research at Southampton 44th in the world and 5th in the UK.

CORMSIS Business Advisory Board

This Committee is a good indicator of the high regard in which the Southampton MSc programmes involving Operational Research are held by outside organisations. Its purpose is to ensure that the MSc programmes produce graduates with the requisite skills for the needs of industry. It also provides a focal point for liaison between the Operational Research Group and industry. You have the chance to meet the Committee several times during the year. Major companies including Shell, British Airways, BAA, BT, The AA, Dstl and HM Revenue & Customs are represented on the Committee.

Programme Structure

The full-time MSc is completed over a 12-month period. There are two semesters of taught material, which account for 60 ECTS (120 CATS), together with an MSc project (typically undertaken in the summer), which accounts for 30 ECTS (60 CATS).

The structure of the programme provides you with a foundation in both Operational Research and Statistics. It also allows you to select several optional modules from a broad range of topics in Semester 2 so that you can specialise in either Operational Research or Statistics (or to choose a balanced portfolio of options). These are complemented by careers talks, with speakers from a wide range of organisations providing an appreciation of the developments in, and use of, Operational Research and Statistics in practice, and presentations on employability skills.

While studying for your degree, you will develop key transferrable skills, such as written and oral communication, presentation skills, teamwork, the use of IT (e.g. some Optimisation, Simulation, and Statistical software), time management, and basic research skills including the use of the web and the library.

Learning & Assessment

The programme is taught through a mixture of lectures, computer workshops, case studies and project work. Assessment is made using examinations, presentations, coursework assignments and a final dissertation.

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This MSc teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantitative finance, artificial intelligence and machine vision.

Degree information

The programme aims to provide graduates with the foundational principles and the practical experience needed by employers in the area of machine learning and statistics. Graduates of this programme will have had the opportunity to develop their skills by tackling problems related to industrial needs or to leading-edge research.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research project (60 credits). Please note that not all combinations of optional modules will be available due to timetabling restrictions.

Core modules
-Supervised Learning
-Statistical Modelling and Data Analysis
-Graphical Models or Probabilistic and Unsupervised Learning
Plus one of:
-Applied Bayesian Methods
-Statistical Design of Investigations
-Statistical Computing
-Statistical Inference

Optional modules - students select 60 credits from the following list:
-Advanced Topics in Machine Learning
-Affective Computing and Human-Robot Interaction
-Applied Bayesian Methods
-Approximate Inference and Learning in Probabilistic Models
-Computational Modelling for Biomedical Imaging
-Information Retrieval and Data Mining
-Machine Vision
-Selected Topics in Statistics
-Optimisation
-Statistical Design of Investigations
-Statistical Inference
-Statistical Natural Language Programming
-Stochastic Methods in Finance
-Stochastic Methods in Finance 2
-Advanced Topics in Statistics
-Mathematical Programming and Research Methods
-Intelligent Systems in Business

Dissertation/report
All MSc students undertake an independent research project, which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning
The programme is delivered through a combination of lectures, discussions, practical sessions and project work. Student performance is assessed through unseen written examinations, coursework, practical application and the project assessment process.

Careers

There is a strong national and international demand for graduates with skills at the interface of traditional statistics and machine learning. Substantial sectors of UK industry, including leading, large companies already make extensive use of computational statistics and machine learning techniques in the course of their business activities. Globally there are a large number of very successful users of this technology, many located in the UK. Areas in which expertise in statistics and machine learning is in particular demand include; finance, banking, insurance, retail, e-commerce, pharmaceuticals, and computer security. Graduates have gone on to further study at, for example, the Universities of Cambridge, Helsinki, Chicago, as well as at UCL. The MSc is also ideal preparation for a PhD, in statistics, machine learning or a related area.

Top career destinations for this degree:
-Statistical and Algorithm Analyst, Telemetry
-Decision Scientist, Everline
-Computer Vision Researcher, Slyce
-Data Scientist, YouGov
-Research Engineer, DeepMind

Employability
Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. There is a considerable shortfall in the number of qualified graduates in this area internationally. CSML graduates have been in high demand for PhD positions across the sciences. In London there are many companies looking to understand their customers better who have hired our CSML graduates. Similarly graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector has also hired several graduates recently.

Why study this degree at UCL?

The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and UCL Statistical Science, this MSc programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance and related information areas.

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

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