Module overview
Aims and Objectives
Learning Outcomes
Transferable and Generic Skills
Having successfully completed this module you will be able to:
- Analyse problems in a systematic manner and develop algorithms to solve them computationally
- Use existing software libraries in your own code
- Design, run, debug and test computer programs
Knowledge and Understanding
Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:
- Good programming style
- Fundamental statistical concepts, including probability distribution functions, cumulative distribution functions, hypothesis testing, parameter estimation and model fitting
- Basic programming constructs, including sequence, selection and iteration, the use of identifiers, variables and expressions, and a range of data types
Subject Specific Practical Skills
Having successfully completed this module you will be able to:
- Write code to analyse and present experimental/observational data
Subject Specific Intellectual and Research Skills
Having successfully completed this module you will be able to:
- Interpret experimental/observational results correctly
Syllabus
Learning and Teaching
Teaching and learning methods
Type | Hours |
---|---|
Completion of assessment task | 110 |
Wider reading or practice | 40 |
Total study time | 150 |
Resources & Reading list
General Resources
Software requirements. Enthought may be OK for this module,but Anaconda is strongly preferred
Textbooks
Staff requirements (including teaching assistants and demonstrators).
Barlow, Roger. Statistics: A Guide to the Use of Statistical Methods in the Physical Sciences. John Wiley & Sons.
Teaching space, layout and equipment required.
Assessment
Assessment strategy
Attendance of all practical sessions is mandatory; no mark will normally be returned for any student attending fewer than half of the sessions. Students repeating this module externally will be assessed solely via Assignment 2, which will therefore contribute 100% to the final mark for these students.Summative
This is how we’ll formally assess what you have learned in this module.
Method | Percentage contribution |
---|---|
Programming project | 20% |
Data analysis project | 60% |
Continuous Assessment | 20% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
Method | Percentage contribution |
---|---|
Data analysis project | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
Method | Percentage contribution |
---|---|
Coursework | 100% |
Repeat Information
Repeat type: Internal