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Curricular information is subject to change
On completion of this module, students should be able to
Understand the importance of data management and biostatistics
Understand core considerations of data management, including data security, source data, etc.;
Understand core principles of experimental design - sampling, randomization, types of design etc…
Understand common statistical methodologies applied to data generated from clinical trials
Be able to carry out basic statistical analysis of clinical trial datasets
Create a data management plan for a clinical research project
| Student Effort Type | Hours |
|---|---|
| Lectures | 54 |
| Computer Aided Lab | 18 |
| Specified Learning Activities | 48 |
| Autonomous Student Learning | 80 |
| Total | 200 |
Not applicable to this module.
| Description | Timing | Component Scale | % of Final Grade | ||
|---|---|---|---|---|---|
| Continuous Assessment: Continuous Assessment | Throughout the Trimester | n/a | Graded | No | 60 |
| Examination: EXAM | 2 hour End of Trimester Exam | No | Graded | No | 40 |
| Resit In | Terminal Exam |
|---|---|
| Spring | Yes - 2 Hour |
• Feedback individually to students, post-assessment
Not yet recorded.
| Name | Role |
|---|---|
| Dr Marie Galligan | Lecturer / Co-Lecturer |
| Dr Deborah Wallace | Lecturer / Co-Lecturer |