MAS468 Statistical Computing in R

Note: This is an old module occurrence.

You may wish to visit the module list for information on current teaching.

Semester 1, 2019/20 10 Credits
Lecturer: Dr Kevin Walters uses MOLE Timetable Reading List
Aims Outcomes Teaching Methods Assessment Full Syllabus

The module introduces the basics of the R language, demonstrates how to use and write functions in R, introduces some programming tools, shows how R can be used for Monte Carlo techniques.

Prerequisites: MAS223 (Statistical Inference and Modelling)
No other modules have this module as a prerequisite.

Outline syllabus

  • Introduction to the R language.
  • Using R Markdown
  • Writing R functions.
  • Programming in R.
  • Monte Carlo Simulation in R.


  • To enable students to write basic R code.
  • To give practice in writing functions in R.
  • To help students to write longer programs.
  • To illustrate how R can be used to implement a range of Monte Carlo techniques
  • To give practice in applying Monte Carlo methods and interpreting results from them.
  • To give practice in creating reproducible work using R Markdown.

Learning outcomes

  • write simple functions and programs in R;
  • develop skills in writing longer, more complex R programs;
  • understand how Monte Carlo simulations can be implemented in R
  • be able to produce high quality graphics in R;
  • prepare technical documents with R Markdown.

Teaching methods

Examples classes and computer practice in the PC Laboratories; on-line discussion. Feedback on assignments.

No lectures, no tutorials, 10 practicals


Two continuously assessed assignments.

Full syllabus

N.B `computer labs' are 1.5 or 2hrs.

  • Introduction to the R language(8 hours).
  • Using R Markdown (2 hours)
  • Writing R functions (5 hours).
  • Monte Carlo Simulation in R (5 hours).
  • Programming in R (5 hours).

Reading list

Type Author(s) Title Library Blackwells Amazon
B Grolemund, G. Hands-on Programming with R Blackwells Amazon
B Grolemund, G. and Wickham, H. R for Data Science Blackwells Amazon
B Xie, Y., Allaire, J.J. and Grolemund G. R Markdown: The definiitive Guide Blackwells Amazon

(A = essential, B = recommended, C = background.)

Most books on reading lists should also be available from the Blackwells shop at Jessop West.


Mon 10:00 - 10:50 lab session   Diamond Computer Room 1 / Room 201
Mon 11:00 - 11:50 lab session   Diamond Computer Room 1 / Room 201