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Curricular information is subject to change
Learning Outcomes:
1. Organise and manipulate data on a computer;
2. Design a biological / environmental experiment, taking due account of independence, allocation of replicates and controls;
3. Fit and validate a statistical model to biological data;
4. Test a null-hypothesis using a fitted statistical model;
5. Accurately communicate data using graphs, tables and written text;
6. Answer research questions and draw strong defensible conclusions using statistical data analysis.
Skills:
The module will contribute towards the development of the following skills:
• Effective presentation and writing of technical information
• Transparency and collaboration on data analysis projects (open science)
• Spreadsheet (Excel), R statistical language and general computer skills
Student Effort Type | Hours |
---|---|
Lectures | 5 |
Practical | 19 |
Autonomous Student Learning | 93 |
Online Learning | 8 |
Total | 125 |
Not applicable to this module.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Practical Skills Assessment: Online test on data analysis in R | n/a | Alternative linear conversion grade scale 40% | No | 20 |
|
Quizzes/Short Exercises: In-class exercises | n/a | Pass/Fail Grade Scale | No | 30 |
|
Exam (Open Book): 2 hour open book exam on data analysis and experimental design. | n/a | Graded | No | 50 |
Resit In | Terminal Exam |
---|---|
Summer | No |
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
• Online automated feedback
Not yet recorded.
Name | Role |
---|---|
Dr Paul Brooks | Lecturer / Co-Lecturer |
Dr John Finarelli | Lecturer / Co-Lecturer |
Dr Adam Kane | Lecturer / Co-Lecturer |
Dr Marcin Penk | Lecturer / Co-Lecturer |
Jonathan Willans | Tutor |
Ultan Ò'Donnell | Tutor |