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The University of Southampton

MATH6173 Statistical Computing

Module Overview

This module consists of lecturers and associated practical sessions. The first part will focus on basic statistical programming in R. The second part will provide an introduction to some modern computational statistical methods and their implementation in R. The module includes 18 lectures and 18 computer practical sessions for students to gain hands-on experience of statistical programming and computation.

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Students should be able to enter, import and manipulate data.
  • Students should be able to produce basic graphics.
  • Students should be able to write functions, loops and code for conditional execution.
  • Students should understand and able to implement the algorithms of the methods from the following approaches: bootstrapping, MCMC and EM algorithm.


- R syntax - Importing data - Data manipulation - Graphics - Writing functions - Loops and conditional execution - Random number generation - Markov chain Monte Carlo - Bootstrapping - EM algorithm

Learning and Teaching

Teaching and learning methods

18 computer labs + 18 lectures (this may all be delivered online)

Independent Study114
Total study time150

Resources & Reading list

James, G., Witten, D., Hastie, T. and Tibshirani, R.. An Introduction to Statistical Learning with Applications in R. 

Hastie, T., Tibshirani, R. and Friedman, J. . The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 

Grolemund, G. and Wickham, H.. R for Data Science. 



MethodPercentage contribution
Coursework 50%
Coursework 50%


MethodPercentage contribution
Coursework 50%
Coursework 50%


MethodPercentage contribution
Coursework 50%
Coursework 50%


Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Books and Stationery equipment

Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase reading texts as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at

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