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Curricular information is subject to change
You will gain some understanding and knowledge of the techniques and tools which are available. The emphasis will be on understanding the principles behind he different algorithms. This course is not a course on Statistical computing, but you will understand and appreciate how to aply these methods in practice.
Student Effort Type | Hours |
---|---|
Lectures | 18 |
Computer Aided Lab | 6 |
Specified Learning Activities | 40 |
Autonomous Student Learning | 55 |
Total | 119 |
Basic course in statistics including probability, inference, hypothesis testing
Learning Recommendations:Knowledge of Stochastic Processes, Bayesian Inference
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Examination: End of trimester written exam | 2 hour End of Trimester Exam | No | Standard conversion grade scale 40% | No | 60 |
Assignment: Assignments | Varies over the Trimester | n/a | Standard conversion grade scale 40% | No | 40 |
Resit In | Terminal Exam |
---|---|
Spring | Yes - 2 Hour |
• Group/class feedback, post-assessment
Not yet recorded.
Name | Role |
---|---|
Dr Michael Salter-Townshend | Lecturer / Co-Lecturer |