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Curricular information is subject to change
On completion of this module, students should be able to:
1. Process experimental data and solve numerical problems in biochemistry.
2. Demonstrate skills using data analysis programmes, in particular GraphPad Prism and Excel.
3. Demonstrate application of relevant statistical methods and use statistical analysis to interpret experimental data.
4. Apply appropriate data analysis strategies to research problems and experimental approaches in biochemistry and molecular biology.
Student Effort Type | Hours |
---|---|
Lectures | 8 |
Tutorial | 6 |
Specified Learning Activities | 20 |
Autonomous Student Learning | 66 |
Total | 100 |
knowledge of biochemical and molecular biology techniques
prior exposure to analysis and interpretation of experimental data
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Not yet recorded. |
Resit In | Terminal Exam |
---|---|
Spring | No |
• Feedback individually to students, on an activity or draft prior to summative assessment
• Feedback individually to students, post-assessment
1. Prior to Assignment 1, students select data set and complete formative assignment activities. The formative student submissions will be discussed in dedicated class tutorial sessions. 2. For Assignment 2, students will work on their data analysis problems during a tutorial session, during which questions will be answered and feedback will be given by lecturers and teaching assistants (demonstrators) . 3. The individual assignments will be graded and feedback provided to individual students via VLE. 4. Upon request, students receive individual feedback on the final exam.
Name | Role |
---|---|
Dr Seema Nathwani | Lecturer / Co-Lecturer |
Dr Jens Rauch | Lecturer / Co-Lecturer |