The MRC Biostatistics Unit run a number of successful courses in statistics on a range of topics at different levels, for statistical, clinical and other audiences. These courses take place in Cambridge at the Cambridge Institute of Public Health, and are mostly either 1 day or 2 days.
Limited spaces are available, so be sure to register in order to secure a place. Participants will be asked to bring their own laptops to the practicals.
Information about upcoming courses is given below. However, due to the recent government announcements we will keep this page updated as to if and when courses will continue to run.
2020 COURSE DATES
Advanced Bayesian Modelling with BUGS
Wednesday 24th June – Thursday 25th June 2020 – to register: click here
Course aims: This course is designed for statisticians who want to improve their command of the BUGS modelling software. We will assume a previous knowledge of BUGS to the level of our companion course “Introduction to Bayesian analysis using BUGS”. Participants will learn how the BUGS language can be used to build models that represent the complexities of real data
For further course details, please see: Advanced Bayesian Modelling with BUGS
Introduction to ‘R’: free software for statistical analysis
Monday 12 October 2020 – to register: click here
Course Times: 09:30-17:00
Course aims: R is a free, popular language and environment that allows powerful and fast manipulation of data, offering many statistical and graphical options. This course aims to introduce R as a tool for statistics and graphics, with the main aim being to become comfortable with the R environment. It will focus on entering and manipulating data in R and producing simple graphs. A few functions for basic statistics will be briefly introduced, but statistical functions will not be covered in detail.
For further course details, please see: An Introduction to ‘R’
Introduction to Bayesian Statistics using BUGS
Tuesday 20 October – Wednesday 21 October 2020 : to register: click here
Course Times 09:30- 17:00
Course aims: This course is intended to provide an introduction to Bayesian analysis and MCMC methods, and a fairly detailed tutorial on the use of OpenBUGS/WinBUGS/JAGS.
For further course details, please see: Introduction to Bayesian statistics using BUGS
Introduction to Statistical Concepts and Reasoning
Monday 19 October 2020 – to register: click here
Course Time: 09:30 – 17:30
Course aims: This course will introduce participants to fundamental statistical concepts and develop their ‘statistical thinking’, the ability to critically interpret and appraise statistical aspects commonly found in published medical research. The course will not cover the underlying statistical methodology (i.e. few if any formulae) nor practical application of specific statistical techniques (i.e. will not be covering any specific statistical software). The course is focused on understanding and interpretation.
For further course details, please see: An Introduction to Statistical Concepts and Reasoning
Tuesday 24 November – Wednesday 25th November 2020
to register: click here
Research Symposium on Mendelian Randomization Methodology – 26 November 2020
to register: click here
Course aims: Studies based on Mendelian randomization are increasingly being used to distinguish causal relationships from observational associations in epidemiology and to prioritize potential targets for pharmaceutical intervention. This course intends to explain both simple and more complex statistical methods for causal inference in Mendelian randomization studies, and the instrumental variable assumptions on which they are based. The course includes computing practicals (R will be supported).
For further course details, please see: Mendelian Randomization
A Research Symposium on Mendelian Randomization Methodology will be taking place on the morning of Thursday 26 November 2020 that is open to course attendees and non-course attendees. To find out more and to register, click here
For further information about the BSU Short Courses please contact the BSU Course Administrator:
Tel: 01223 330366