School of Mathematics and Statistics (SoMaS)

MAS6024 Statistical Data Science in R

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

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.

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

Timetable