Introduction to R for Epidemiological Analysis
Posted 13 days 18 hours ago by UK Health Security Agency
Learn about the basics concepts of R for epidemiology.
In this course, you will learn about the basic concepts and practical elements of using R and it serves as an introduction to R for epidemiological analysis. With the help of your educators, you’ll develop data management skills that will enable you to load, clean and manage datasets, as well as reshape and merge them. With these skills, you’ll create clean, accurate, and relevant data for surveillance and research analysis. You’ll be taught methods and approaches to visualise your data successfully, using graphs and maps. This course aims to equip you with the skills to use R confidently and independently in your work.
This 6-day course has been developed by the UK Public Health Rapid Support Team (UK-PHRST) in collaboration with afrimapr is being delivered in partnership with the Nigeria Centres for Disease Control (Nigeria CDC), UK Health Security Agency International Health Regulations (IHR) team in Nigeria.
On every step of the course, you can meet other learners, share your ideas and join in with active discussions either in person or in the comments.
This course is accredited by the UK Public Health Rapid Support Team (UK-PHRST). UK-PHRST is a partnership between UK Health Security Agency and the London School of Hygiene and Tropical Medicine.
Co-delivered with the Nigeria Centre for Disease Control and Prevention
The Nigeria Centre for Disease Control is the national public health institute for Nigeria. It is a federal government agency under the Federal Ministry of Health.
This is an introductory course for epidemiologists, surveillance analysts, statisticians, data scientists and similar professionals who work in surveillance, outbreak response or research areas with little to no previous experience in R.
This is an introductory course for epidemiologists, surveillance analysts, statisticians, data scientists and similar professionals who work in surveillance, outbreak response or research areas with little to no previous experience in R.
- Set up and run R
- Install and load up R packages
- Clean and manage messy datasets
- Summarise the cleaned analysis dataset
- Produce data visualisations e.g. epi-curves and maps