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  • DeadlineStudy Details:

    1 year full time, 2 years part time

Course Description

In this digital and data-rich era the demand for statistics graduates from industry, the public sector and academia is high, yet the pool of such graduates is small. The recent growth of data science has increased the awareness of the importance of statistics, with the analysis of data and interpretation of the results firmly embedded within this newly recognised field.

This programme is designed to train the next generation of statisticians with a focus on the newly recognised field of data science. The syllabus combines rigorous statistical theory with wider hands-on practical experience of applying statistical models to data. In particular the programme includes:

  • classical and Bayesian ideologies
  • computational statistics
  • regression
  • data analysis of a range of models and applications

Graduates will be in high demand. It is anticipated that the majority of students will be employed as statisticians within private and public institutions providing statistical advice/consultancy.

Entry Requirements

A UK 2:1 degree, or its international equivalent, in a numerate discipline such as mathematics, engineering, computer science, physical or biological sciences, economics or business.

Your degree must have included substantial mathematics content, including calculus (including calculus of several variables), linear algebra, probability, statistics and statistical theory. Detailed information is available from the School of Mathematics website.

You can increase your chances of a successful application by exceeding the minimum programme requirements.

Fees

Please see our website

Student Destinations

Trained statisticians are in high demand both in public and private institutions. This programme will provide graduates with the necessary statistical skills, able to handle and analyse different forms of data, interpret the results and effectively communicate the conclusions obtained.

Graduates will have a deep knowledge of the underlying statistical principles coupled with practical experience of implementing the statistical techniques using standard software across a range of application areas, ensuring they are ideally placed for a range of different job opportunities.

The degree is also excellent preparation for further study in statistics or data science. Students have gone on to study their PhDs at highly-ranked universities including Oxford and Edinburgh.

Module Details

Compulsory courses have previously included:

  • Bayesian Data Analysis
  • Bayesian Theory
  • Generalised Regression Models
  • Incomplete Data Analysis
  • Statistical Programming
  • Statistical Research Skills

Optional courses have previously included:

  • Biomedical Data Science
  • Biostatistics
  • Credit Scoring
  • Fundamentals of Operational Research
  • Fundamentals of Optimization
  • Large Scale Optimization for Data Science
  • Machine Learning in Python
  • Machine Learning and Pattern Recognition*
  • Python Programming
  • Machine Learning in Python
  • Simulation
  • Probabilistic Modelling and Reasoning*
  • Methods for Causal Inference*
  • Statistical Methodology
  • Stochastic Modelling
  • Time Series
  • Text Technologies for Data Science*

*delivered by the School of Informatics

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