M.Sc. Social Statistics

University of Glasgow

Tuition fee: Not specified
Start date: September  2015
Duration full-time: 12 months
Languages:
  • English
Location:
Disciplines:
Delivery mode: On Campus
Educational variant: Full-time

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Description

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Key facts·MSc: 12 months full-time;

·Contact:Further information: Postgraduate Admissions Team: pgadmissions@glasgow.ac.uk

Why Glasgow

·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.

·The University of Glasgows School of Mathematics and Statistics is ranked 4th in Scotland (Complete University Guide 2015).

·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.

·With a 94% overall student satisfaction in the National Student Survey 2014, the School of Mathematics and Statistics combines both teaching excellence and a supportive learning environment.

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.

Semester 1

Core courses (compulsory)

·Introduction to R

·Probability or Stochastic processes 1

·Professional skills

·Regression models

·Statistical inference or Bayesian statistics or computational inference 2.

Optional courses (one chosen)

·Biostatistics

·Multivariate methods.

Semester 2

Core courses (compulsory)

·Data analysis

·Generalised linear models.

Optional courses (four chosen)

·Advanced Bayesian methods

·Design of statistical investigations

·Environmental statistics

·Financial statistics

·Functional data analysis

·Principles of probability and statistics

·Sampling and databases

·Spatial statistics

·Statistical data mining

·Statistical genetics

·Time series.

1 Stochastic processes will normally be substituted in the curriculum of 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.

2 These option will normally be substituted in the curriculum of any student who, in the courses of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses.

Projects

·To complete the MSc degree you must undertake a project worth 60 credits. This is a project chosen by you to investigate a challenging statistical problem, where you will investigate the background to the project; identify relevant statistical methodology, formulate and implement an appropriate analysis plan, present your work orally and in a dissertation.

·The project will integrate the subject knowledge and generic skills that you will acquire during your Masters.

·We offer a wide range of projects, and each student is allocated an individual project. We take your preferences into account when we allocate the projects.

·You will also have the opportunity to propose your own project, subject to academic approval.

Contents

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.

Semester 1

Core courses (compulsory)

·Introduction to R

·Probability or Stochastic processes 1

·Professional skills

·Regression models

·Statistical inference or Bayesian statistics or computational inference 2.

Optional courses (one chosen)

·Biostatistics

·Multivariate methods.

Semester 2

Core courses (compulsory)

·Data analysis

·Generalised linear models.

Optional courses (four chosen)

·Advanced Bayesian methods

·Design of statistical investigations

·Environmental statistics

·Financial statistics

·Functional data analysis

·Principles of probability and statistics

·Sampling and databases

·Spatial statistics

·Statistical data mining

·Statistical genetics

·Time series.

1 Stochastic processes will normally be substituted in the curriculum of 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.

2 These option will normally be substituted in the curriculum of any student who, in the courses of study for his or her first degree, has already completed the equivalent of the Probability and/or Statistical inference courses.

Requirements

An upper second class Honours degree or equivalent with a substantial mathematics component (at least equivalent to Level-1 courses in mathematics and Level-2 courses in calculus and linear algebra at the University of Glasgow). Previous study of statistics is not required.

International students with academic qualifications below those required should contact our partner institution, Glasgow International College, who offer a range of foundation courses.

Further information regarding academic entry requirements:student.recruitment@glasgow.ac.uk

For applicants whose first language is not English, the University sets a minimum English Language proficiency level.

International English Language Testing System (IELTS) Academic module (not General Training):

* overall score 6.5
* no sub-test less than 6.0
* or equivalent scores in another recognised qualification (see below)

Common equivalent English language qualifications:

* ibTOEFL: 92; no sub-test less than 20
* CAE (Cambridge Certificate of Advanced English): Bminimum
* CPE (Cambridge Certificate of Proficiency in English): Cminimum
* PTE Academic (Person Test of English, Academic test): 60; no sub-test less than 59

Pre-sessional courses
The University of Glasgow accepts evidence of the required language level from the Language Centre Pre-sessional courses. We also consider other BALEAP accredited pre-sessional courses:

* Language Centre, University of Glasgow
* BALEAP guide to accredited courses

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