Module overview
This module will provide an introduction to basic statistical programming in R. It consists of lecturers and associated practical sessions for students to gain hands-on experience of statistical programming.
This module will provide an introduction to basic statistical programming in R. It consists of lecturers and associated practical sessions for students to gain hands-on experience of statistical programming.
Having successfully completed this module you will be able to:
18 sessions, in combination of lectures and computer labs, (this may all be delivered online)
Type | Hours |
---|---|
Teaching | 18 |
Independent Study | 57 |
Total study time | 75 |
Garrett Grolemund and Hadley Wickham. R for Data Science. O’Reilly.
This is how we’ll give you feedback as you are learning. It is not a formal test or exam.
Coursework Class ExerciseThis is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Coursework | 100% |
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Coursework | 100% |
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
Method | Percentage contribution |
---|---|
Coursework | 100% |
Repeat type: Internal & External