Effective visual communication is a core task for all data scientists including statisticians, epidemiologists, machine learning experts, bioinformaticians, etc.
By using the right graphical principles, we can better understand data, highlight core insights and influence decisions toward appropriate actions. Without it, we can fool ourselves and others and pave the way to wrong conclusions and actions. While numerous solutions exist to analyze data, these often require many manual steps to convert them into visually convincing and meaningful reports. How do we put this in practice in an accurate, transparent and reproducible way?
In this webinar we will introduce an open collaborative effort, currently undertaken by Roche and Novartis, to develop solutions for effective visual communication with a focus on reporting medical and clinical data. The aim of the collaboration is to develop a user-friendly, fit for purpose, open source package to simplify the use of good graphical principles for effective visual communication of typical analyses of interventional and observational data encountered in clinical drug development. We will introduce the initial visR package design which easily integrates into a typical tidyverse workflow. The package provides guidance and meaningful default parameters covering all aspects from the design, implementation and review of statistical graphics.
Only 1,000 live attendees are allowed in the Webinar on a first come first serve basis. There will be approximately 45 minutes of presentation, usually followed by a question and answer session.
We've started a Github repository with all webinar materials. Speakers for this webinar and all future webinars will add their materials to the repository. https://github.com/rstudio/webinars
If you can't attend, don't worry. We record (almost) every webinar and post all materials on our website within 48 hours. See past webinars at https://resources.rstudio.com/webinars
RStudio provides the premiere open source and enterprise-ready professional software for R, including RStudio Desktop, RStudio Server, RStudio Connect, RStudio Package Manager Shiny Server, and shinyapps.io. The tidyverse, shiny, ggplot, ggvis, dplyr, knitr, R Markdown, and packrat are R packages from RStudio that every data scientist will want to enhance the value, reproducibility, and appearance of their work.