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Curricular information is subject to change
Be proficient both manually and in R in all of the areas outlined as part of the module content.
Indicative Module Content:Probability distributions, discrete and continuous, regression, R modelling, sampling and inference, confidence intervals, hypothesis tests, power, sample size calculations.
Student Effort Type | Hours |
---|---|
Lectures | 48 |
Autonomous Student Learning | 52 |
Total | 100 |
Not applicable to this module.
Resit In | Terminal Exam |
---|---|
Spring | Yes - 2 Hour |
• Feedback individually to students, post-assessment
Assignments graded and returned. Overall module grade available at end.
Name | Role |
---|---|
Ms Courtney Clarke | Tutor |
Lucien Francois | Tutor |
Mr Lucien Francois | Tutor |
Thais Pacheco Menezes | Tutor |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Fri 12:00 - 13:50 |
Lecture | Offering 1 | Week(s) - 1 | Wed 13:00 - 14:50 |
Lecture | Offering 1 | Week(s) - Autumn: Weeks 2-12 | Wed 13:00 - 14:50 |