Curricular information is subject to change.
At the end of the course, students should have attained an intermediate-level knowledge of R. They should be able to use R to:
- Manipulate data sets of any size and structure.
- Create professional quality graphical summaries of data.
- Produce data analysis documents
- Program and implement efficient algorithms.
| Student Effort Type | Hours |
|---|---|
| Computer Aided Lab | 12 |
| Specified Learning Activities | 26 |
| Autonomous Student Learning | 100 |
| Online Learning | 12 |
| Total | 150 |
Not applicable to this module.
| Description | Timing | Component Scale | % of Final Grade | ||
|---|---|---|---|---|---|
| Assignment(Including Essay): There will be one small assignment worth 2% due in week 3 and two main 2 assignments, each worth 19% due in week 6 and 10. | Week 3, Week 6, Week 10 | Alternative linear conversion grade scale 40% | No | 40 |
No |
| Assignment(Including Essay): The project will involve using the R programming tools covered in the course. | Week 15 | Alternative linear conversion grade scale 40% | No | 50 |
No |
| Quizzes/Short Exercises: There will be 4 small tests, each worth 2.5%, which will be available on Brightspace. | Week 4, Week 6, Week 9, Week 12 | Alternative linear conversion grade scale 40% | No | 10 |
No |
| Resit In | Terminal Exam |
|---|---|
| Spring | No |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback
Not yet recorded.
| Name | Role |
|---|---|
| Faezeh Fadaei | Tutor |
| Kate Finucane | Tutor |
| Lapo Santi | Tutor |
| Autumn | Laboratory | Offering 1 | Week(s) - Autumn: Weeks 2-12 | Thurs 09:00 - 09:50 |
| Autumn | Laboratory | Offering 2 | Week(s) - Autumn: Weeks 2-12 | Thurs 11:00 - 11:50 |
| Autumn | Laboratory | Offering 4 | Week(s) - Autumn: Weeks 2-12 | Mon 09:00 - 09:50 |