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  • DeadlineStudy Details: Online across 24 or 36 months, part-time with both September and January entry points.

Course Description

Our online MSc in Applied Statistics is a conversion course, offering the opportunity to develop skills in statistics and data analysis even if you have never studied statistics before.

You’ll be supported through this programme by members of staff who work directly with industry to develop skills which are relevant to current areas of research including population health and medicine, animal and plant health, finance and business. Modules are delivered entirely online, giving students the flexibility to study at times that suit them. You’ll gain skills in:

  • problem solving
  • analysis and manipulation of complex data
  • the use of statistical software for data analysis and reporting
  • effective communication of statistics

 

Entry Requirements

Minimum second-class (2:2) Honours degree or overseas equivalent

Mathematical training to A Level or equivalent standard

Prospective students with relevant experience or appropriate professional qualifications are also welcome to apply

For Australia and Canada, normal degrees in relevant disciplines are accepted

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Fees

For fees and funding options, please visit website to find out more

Student Destinations

The online MSc in Applied Statistics will provide graduates with skills in the statistical analysis of data from a wide range of disciplines. These skills are required by many employers in sectors such as:

  • investment companies 
  • financial institutions 
  • pharmaceutical industry 
  • medical research 
  • government organisations 
  • retailers 
  • internet information providers

Module Details

Compulsory classes
Foundations of Probability & Statistics

Data Analytics in R (20 credits)

Statistical Modelling & Analysis (20 credits)

Research project (60 credits)

Elective classes
You're required to take 60 credits of elective classes.

Data dashboards with Rshiny (10 credits)

Quantitative Risk Analysis

Survey Design & Analysis (10 credits)

Financial Econometrics

Financial Stochastic Processes

Medical Statistics (20 credits)

Effective Statistical Consultancy (10 credits)

Bayesian Spatial Statistics (10 credits)

Machine Learning for Data Analytics (20 credits)

Big Data Fundamentals (10 credits)

Big Data Tools & Techniques (10 credits)

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