The course introduces students to programming in the statistical software environment R.

The course mostly consists of asynchronous teaching material.

Introduction to R Programming

Introduction to R Programming (Level M)

Statistics 3R: Introduction to R Programming

-/-

100% Continuous Assessment

This will typically be made up of a project (20%), one oral assessment (20%) and three homework exercises (60%).

Full details are provided in the programme handbook.

The aims of this course are:

■ to introduce students to the basic concepts and ideas of a statistical computing environment;

■ to train students in programming tools using the R computing environment

■ to provide computational skills which will support other courses on the programme; and

■ to introduce students to fundamental concepts in (scientific) programming in general.

By the end of this course students will be able to:

■ recognise and make appropriate use of different types of data structures;

■ use R to create figures and graphs;

■ identify and implement appropriate control structures to solve a particular programming problem;

■ design and write functions in R and implement simple iterative algorithms;

■ structure complex programming problems into functional units and implement these;

■ carry out extended programming tasks and produce clearly annotated listing of their code;

■ author reports with embedded code using technologies such as Sweave or knitr; and

■ develop and deploy R Shiny apps.

Students must submit at least 75% by weight of the components (including examinations) of the course's summative assessment.