Unit information: Statistical Computing 2 in 2021/22

Unit name	Statistical Computing 2
Unit code	MATHM0040
Credit points	20
Level of study	M/7
Teaching block(s)	Teaching Block 2 (weeks 13 - 24)
Unit director	Dr. Fasiolo
Open unit status	Not open
Pre-requisites	Statistical Methods 1 and Statistical Computing 1
Co-requisites	None
School/department	School of Mathematics
Faculty	Faculty of Science

Description including Unit Aims

This unit introduces students to the wider ‘computerverse’, especially those parts of it pertinent to scientific and big-data computing. These include tools to extend R and to enhance its performance, other computer languages, and other computing environments. This is a rapidly-changing area, and undoubtedly some of today’s state-of-the-art methods will be tomorrow’s also-rans, and so there is emphasis on skills for self-development. Parts of this unit will be developed and delivered in conjunction with the University’s Advanced Computing Research Centre.

Intended Learning Outcomes

By the end of the unit students should be able to:

• Interface R with C/C++ to perform computationally intensive tasks, such as Monte Carlo simulations
• Use high-performance computational libraries in C++, such as the Armadillo or Eigen linear algebra libraries
• Build and document R packages that include both R and C++ code
• Write R and/or C++ that runs in parallel via the OpenMP and/or MPI programming interfaces
• Use an HPC cluster for performing computationally intensive jobs
• Perform numerical calculations, including data analysis, in a second interpreted language (typically Python)

Teaching Information

Some lab based instruction as mentioned above in details

Assessment Information

Formative: a homework each week

Summative:

• A personal portfolio of notes, code snippets, and vignettes, 30%.
• Assessed coursework, 2 at 20% each.
• A group project, 30%.

Resources

If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. MATHM0040).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.