| Unit name | Advanced Statistics |
|---|---|
| Unit code | BRMSM0058 |
| Credit points | 20 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
| Unit director | Dr. Tom Palmer |
| Open unit status | Not open |
| Units you must take before you take this one (pre-requisite units) |
None |
| Units you must take alongside this one (co-requisite units) |
None |
| Units you may not take alongside this one |
None |
| School/department | Bristol Medical School |
| Faculty | Faculty of Health Sciences |
Why is this Unit important
The advanced statistical techniques taught in this unit will allow you to deal with the real-world complexity of health data. It will build on your knowledge of regression models acquired in previous units, allowing you to deal with structured data (e.g. where observations are measured at multiple time-points or where measurements are recorded in groups) and advancing your knowledge of survival models. In previous units you learn about different types of bias and then this unit equips you with the statistical modelling tools to eliminate or reduce that bias. For instance, missing data is prevalent in epidemiological studies, and in this unit you will learn how to appropriately deal with missing data to reduce the potential bias.
How does this unit fit into your programme of study
This unit extends your knowledge of statistical techniques learnt in earlier units on the course. For example, in the Regression Models unit (BRMSM0056, teaching block 1) you will learn about generalised linear models, which is built upon in this unit with extensions including multi-level models for structured data. If the more basic models were fitted to the structured data this could produce biased estimates and incorrect statistical inference.
An overview of content
The topics covered are as follows:
How will students, personally, be different as a result of the unit
This unit teaches you advanced statistical methods and how to present the results of analyses using these methods. The methods covered will allow you to deal with different types of bias, and different types of structure in health data.
Learning outcomes
On successful completion of the unit, you should be able to:
The learning of advanced statistical approaches is most effective when it is practice-based. Teaching on this course will consist of lectures to introduce theoretical concepts and modelling approaches, and accompanying practicals to gain experience applying these models in R and appropriately interpreting output.
Directed and self-directed learning will include activities such as reading, accessing web-based supplementary materials, critical analysis, and completion of assessments.
Tasks which help you learn and prepare you for summative tasks (formative):
Your learning will be supported by using informal questioning, quizzes, and group exercises in lectures and practicals. These assessments are for learning and will not contribute to the final unit mark (ILOs 1-3).
The main formative assessment will be a data analysis and interpretation exercise of a dataset from a clustered or longitudinal study design. You will be given a dataset and a research question, and asked to formulate an analysis plan, carry out the analysis, and write a report. The report will include an introduction to the research question, a description of the analysis carried out, appropriate presentation of relevant results, a discussion, and references. (ILOs 1-3)
Tasks which count towards your unit mark (summative):
The summative assessment will be in the form of a data analysis and interpretation exercise from any study design covered in teaching block 1 or in this unit. You will be given a dataset and a research question, and asked to formulate an analysis plan, carry out the analysis and write a report. The report will include an introduction to the research question, a description of the analysis carried out, appropriate presentation of relevant results, a discussion, and references (ILOs 1-3).
When assessment does not go to plan
If you do not pass the unit, you will normally be given the opportunity to take a reassessment as per the Regulations and Code of Practice for Taught Programmes. Decisions on the award of reassessment will normally be taken after all taught units of the year have been completed. Reassessment will normally be in a similar format to the original assessment that has been failed.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. BRMSM0058).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the University Workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. For appropriate assessments, if you have self-certificated your absence, you will normally be required to complete it the next time it runs (for assessments at the end of TB1 and TB2 this is usually in the next re-assessment period).
The Board of Examiners will take into account any exceptional circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
