R for Epi Workshop

Overview

May 9, 2019

This course is an introduction to the R language and RStudio environment for statistical computing and graphics, with an emphasis on public health applications. R is a powerful, free, open-source, and community-supported statistical programming language that connects well with growing data science principles. Because it is free and powerful, it is an ideal language for those working with public health data in budget-conscious environments or organizations that would be limited by cost-prohibitive SAS or STATA licenses. R scripts can also supplement or replace repetitive and error-prone workflows in Excel, and because it is open-source and community-supported, experts in the field can release cutting-edge research tools and peer-reviewed functions for your use.

In this full-day, hands on workshop we first use public health datasets in three interactive, lecture-based modules: (1) learning base R, (2) data manipulation and summary statistics, (3) data visualization. We then close the day with brief demonstrations of advanced R capabilities relevant for public health (e.g. mapping, report building) and leave dedicated time to field questions with participants about their own projects. All code and training materials from the workshop will be shared with participants for future use. Registration fees include workshop lunch, 1-hour of post-workshop support in implementing R projects in participants' settings, and opportunities for deeper consulting afterwards.

 

This workshop is co-sponsored by the Department of Epidemiology at the UNC Gillings School of Global Public Health.

 

Who should take this course?

This workshop is appropriate for local and state public health professionals, healthcare workers (in the public, private, and non-profit sectors), and academic researchers (including current UNC students, faculty and alumni). The recommended prerequisites are a basic working knowledge of:

  • computer literacy and tabular data - basic analysis in excel at least, if not data within some database.

  • programming concepts - including variables, control structures like if-then statements or loops. Experience in another language (e.g. SAS, Stata, SPSS, or similar statistics programming language) may be useful, but is not required. No experience in R is required.

  • statistics - including measures of central tendency (e.g. mean), variance and standard errors, etc.

  • public health concepts - including risks, rates, effects and concepts of variation/disparities by group or spatial area.

    • Where

    • RENCI
      100 Europa Drive
      Suite 540
      Chapel Hill, North Carolina 27517

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