Introduction, R, RStudio, Github and More
Introduction to the Course
This course will describe the concepts underlying the field of study identified as big data analytics along with its application in healthcare. The theoretical underpinnings of these concepts will be presented along with applications in healthcare, including knowledge discovery, precision medicine/nursing, and the development of targeted interventions to improve health outcomes. Commonly used methods in big data analytics will be reviewed, and the challenges related to gathering, analyzing, visualizing, and interpreting big data will be discussed. Hands-on computer laboratory experience with these techniques relevant to an identified area will be included.
What is data science
Open discussion
Introductory Slides
- Lecture 1 Slides - right click and save if you wish
- Introduction to Reproducible Research - right click to save PDF or click to view
Software Tools and Resources
Rhttps://cran.r-project.org/RStudiohttps://www.rstudio.com/Githubhttps://github.com/- rstudio.cloud https://rstudio.cloud/
- Datacamp https://www.datacamp.com/
Resources
See links and information on this website under Resources for R, RStudio, Git and Github at https://melindahiggins2000.github.io/N741bigdata/help.html.
Setting up R and RStudio
See Pre R Workshop Setup Instructions This online “Book” has information on R, installing R and RStudio, and places to get help.
Youtube Video on Installing R, RStudio and Compiling your first Rmarkdown report.
Working with R/RStudio with GIT/Github
A key online book that is HUGELY helpful is “Happy Git and Github for the UseR” by Jenny Bryan, see http://happygitwithr.com/.
Rmarkdown reports
In addition to the YouTube video demonstration above, also learn more at:
Karl Broman’s website Knitr in a Knutshell tutorial
Copyright © Melinda Higgins, Ph.D.. All contents under (CC) BY-NC-SA license,
unless otherwise noted.