Visualising & Analysing Biomedical Datasets with R

Code: MED650, Offered By: Research Study Skills

Open To - Staff / Students University Wide

Semester Taught - Academic Year

Full Description

This unit will teach students how to visualise biomedical data using histograms, scattergrams, line plots, and more sophisticated methods including heatmaps, and how to turn these into publication-quality images. Students will learn how to interpret data and how to apply appropriate statistical tests, including all standard tests used in biomedical studies. The module will use the open source (free) software R which runs on all platforms and is fast becoming the standard statistical software in science. The module will be highly interactive with a detailed course manual (effectively a custom textbook on R in biomedical science) for directed self-study.

Researcher Development Framework Categories:

A1) Knowledge base
A2) Cognitive abilities
A3) Creativity

Teaching Methods

The course is taught online by a detailed 180 page PDF manual and 24 online video podcasts giving step by step instruction on how to setup and use R.

Assessments

The exercises in the course manual will provide continuous formative assessment for the students. 

Aims Objectives

To understand and be able to use biomedical data to produce graphical visualisation and appropriate statistical tests within a common standard statistical software environment (R).

Learning Outcomes

Be able to plot histograms, scatterplots, box & whisker plots, heatmaps etc. and turn these into publication quality PDF files. Be able to design a data format and prepare data appropriately in a spreadsheet/database. Be able to load data from spreadsheets into statistical analysis software. Be able to describe the distributions and interactions of data items by interpreting visualisations such as histograms and scatterplots. Be able to select and perform appropriate statistical tests on biomedical data. Be able to write appropriate text description of the statistical tests and results that could be included in the Methods and Results section of a thesis or research paper. Be able to carry out elementary programming in R to automate data processing and visualisation (optional).

Module Dates

This module is now run via online learning in Blackboard.

Other Information

PLEASE NOTE - This module is run via Blackboard.  Once you have registered you will be given access to the resources on Blackboard.  There is no set date for this module, so please ignore any reference to the module date of 30th August 2022.




Staff Contact

Prof Simon Cross  

Sessions

Tue, Aug 30th 2022, 09:35

Venue: NA - Online Module, Room: NA - Online Module

Tutor: Professor Simon Cross

Additional Information

This module is run via Blackboard. 


Once you have registered you will be given access to the recourses on Blackboard. There is no set date for this module, so please ignore any reference to the module date of 30th August 2022.

54 Places Available
Closing Date: August 29th, 2022

If none of the above sessions are suitable, you can add an expression of interest to your basket and you will be notified when any new sessions become available.

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