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Curricular information is subject to change
At the end of the course students should be able to use R to:
- Load in and manipulate data sets of any size and structure
- Find help and use functions which they have not met before
- Create professional quality graphical summaries of data
- Perform simple statistical analyses
Student Effort Type | Hours |
---|---|
Lectures | 12 |
Computer Aided Lab | 12 |
Specified Learning Activities | 26 |
Autonomous Student Learning | 100 |
Total | 150 |
Students must have had previous experience of using computers, including web searching and creating spreadsheets. Some familiarity with statistiics (mean and variance, correlation, linear regression) is expected.
Learning Recommendations:Some familiarity with Microsoft Office (or equivalent), programming concepts such as loops and functions.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Multiple Choice Questionnaire: Multiple choice exams during the semester | Varies over the Trimester | n/a | Standard conversion grade scale 40% | No | 10 |
Continuous Assessment: Computer labs | Throughout the Trimester | n/a | Standard conversion grade scale 40% | No | 40 |
Project: Coursework project | Coursework (End of Trimester) | n/a | Standard conversion grade scale 40% | No | 50 |
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 |
---|---|
Professor Nial Friel | Lecturer / Co-Lecturer |
Professor Brendan Murphy | Lecturer / Co-Lecturer |
John O'Sullivan | Lecturer / Co-Lecturer |