R for Public Health 2024

R4PH24 : 23 - 28 Sept 2024

The R4PH batch of 2024

Dr Sushila Nayar School of Public Health at the Mahatma Gandhi Institute of Medical Sciences at Sevagram is pleased to announce the 2024 edition of R in Public Health workshop. This workshop will introduce you to use this extremely powerful, free, open source platform to help you with our data and bio-statistical needs.

About

R is a comprehensive language and environment designed specifically for statistical computing and graphics. It is widely used for various statistical analyses, offering an extensive range of tools and techniques. These include, but are not limited to, linear and nonlinear modeling, classical statistical tests, time-series analysis, classification, and clustering.

One of R’s key strengths lies in its extensibility. Researchers and developers can easily enhance its capabilities by creating and integrating new packages. This flexibility makes R the platform of choice for those involved in cutting-edge research in statistical methodology. With its strong support for the development and implementation of new techniques, R plays a crucial role in advancing the field of statistics.

R is also valued for its robust graphical capabilities. It allows users to produce high-quality visualizations, which are essential for data analysis and presentation. Whether for academic publications or professional reports, R can generate publication-quality tables and figures that meet the exacting standards of scholarly communication.

Moreover, R’s status as an Open Source platform provides a cost-effective route for individuals and organizations to participate in and contribute to the broader statistical community. This openness not only fosters innovation but also encourages collaboration, making R a central tool in the global statistical ecosystem.

Workshop Objectives

  • Provide an introduction to R for beginners with no programming experience.
  • Guide participants in data wrangling and summarisation.
  • Teach data visualization techniques to create effective charts, graphs, and tables.
  • Explore the use of R for conducting biostatistical tests and analyses.
  • Equip participants with the skills to continue learning and mastering advanced techniques beyond the workshop, tackling the steep learning curve that R may present.

Who should apply

  • The course is directed towards post-graduate students in their 2nd or 3rd year and junior faculty in Community Medicine or other public health fields.
  • Applicants should have a basic understanding of biostatistical methods, including parametric, non-parametric, and regression techniques.
  • Participants must have access to a modern computer capable of running R and RStudio, whether it’s a Windows PC, Mac, or Linux system.