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Practical Statistics for Epidemiology using R

This course is now full. Please email email the course team to be put on to a waiting list. The next courses will run in April 2023.

 

Date: 12 - 16 September 2022 

Location: this course will run in-person at Brasenose College, University of Oxford. 

Overnight accommodation for course attendees is available at Brasenose College. Please contact the course team for booking information.

Maximum capacity: 20

Course directors: Sarah Lewington, Jennifer Carter, Stephanie Ross, Hubert Lam

The field of epidemiology centres around the study of the patterns, causes and effects of diverse health problems in the population. It is the quantitative science underpinning public health and requires a fundamental understanding of how to interpret and present statistical results.

This course is designed by experienced statisticians and epidemiologists from Oxford Population Health, renowned for its large-scale and innovative observational studies and trials, such as the Million Women Study and the RECOVERY Trial on COVID-19 treatments.

Who is this course for?

Practical Statistics for Epidemiology using R is intended for those who have been exposed to the field of epidemiology. Prior knowledge of epidemiological measures of association such as prevalence, odds, risks, rates and their ratios is required. This is the companion and follow-on course from our Introduction to Epidemiology short course. It is aimed at researchers who use epidemiological data and work alongside statisticians. No prior experience with statistics or statistical software is required, although some experience in a numerate discipline may help participants understand the topics presented. 

Course content

During the week-long course, participants will be introduced to:

  • processing and visualising epidemiological data using the statistical programme R
  • interpreting hypothesis tests, p values, and statistical power
  • use of statistical models for population surveys, case-control studies, and prospective studies
  • statistical techniques to assess and address bias and confounding
  • appropriate presentation of epidemiological results
  • statistical methods for meta-analysis
  • interpreting and critiquing statistical evidence from epidemiological studies.

All course content employs the freely-available statistical programme R. The teaching on this course is a combination of lectures, hands-on practicals with data from the World Health Organization, online quizzes and pre-recorded videos.

Lunch will be provided. 

Outcomes

By the end of this course, attendees will be able to:

  • understand how key epidemiological data are statistically analysed and presented
  • conduct and interpret meta-analyses on epidemiological data
  • interpret and critique statistical results from epidemiological studies.

If you have questions about this short course, please email the course team. 

Course Fees

£250   Oxford student

£500   Oxford staff/external student

£750   External academic/government or non-profit organisations employee

£1000 External industry.