MAS6024 Statistical Data Science in R

Note: Information for future academic years is provisional. Timetable information and teaching staff are especially likely to change, but other details may also be altered, some courses may not run at all, and other courses may be added.

Semester 1, 2019/20 15 Credits
Lecturer: Dr Kevin Walters uses MOLE Timetable Reading List
Aims Outcomes Teaching Methods Assessment Full Syllabus

This module starts in Intro Week with some basic R. The module then introduces further aspects of the R language, demonstrates how to use and write functions in R, introduces some programming tools and shows how R can be used for Monte Carlo techniques.

There are no prerequisites for this module.
No other modules have this module as a prerequisite.


Outline syllabus

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

Office hours

Invite me to a meeting on my Google calendar whenever I am free.



Aims

  • 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
  • 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, 16 practicals

Assessment

Two pieces of course work

Full syllabus

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

  • Introduction to the R language(9 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.