- Introductions
- Topics overview
- Getting R up and running
[Photo by Belinda Fewings on Unsplash]
Welcome!
About Us
Ava Hoffman (she/her)
Senior Staff Scientist, Fred Hutchinson Cancer Center
Associate, Department of Biostatistics, JHSPH
PhD in Ecology
Email: ahoffma2@fredhutch.org Web: https://avahoffman.com
About Us
Carrie Wright (she/her)
Senior Staff Scientist, Fred Hutchinson Cancer Center
Associate, Department of Biostatistics, JHSPH
PhD in Biomedical Sciences
Email: cwright2@fredhutch.org Web: https://carriewright11.github.io
The Learning Curve
Learning a programming language can be very intense and sometimes overwhelming.
We recommend fully diving in and making lots of mistakes through trial and error.
We want you to succeed – We will get through this together!
What is R?
R is a language and environment for statistical computing and graphics developed in 1991
R is both open source and open development (aka, free!)
Powerful and flexible - especially for data wrangling and visualization
Extensive add-on software (packages)
Strong community – https://rladies.org/
[source: http://www.r-project.org/, https://en.wikipedia.org/wiki/R_(programming_language)]
Workshop Website
https://hutchdatascience.org/SeattleStatSummer_R/
Learning Objectives
- Understanding basic programming syntax
- Reading data into R
- Summarizing and grouping data
- Filtering data
- Recoding data
- Making plots with your data
Installing R
Install the latest R version
More detailed instructions on the website.
RStudio is an integrated development environment (IDE) that makes it easier to work with R.
More on that soon!
Getting files from downloads
This course will involve moving files around on your computer and downloading files.
If you are new to this - check out these videos.
If you have a PC: https://youtu.be/we6vwB7DsNU
If you have a Mac: https://www.youtube.com/watch?v=Ao9e0cDzMrE
You can find these on the resource page of the website.
Useful (+ mostly Free) Resources
Found on our website under the Resources tab: https://hutchdatascience.org/SeattleStatSummer_R/resources.html
- videos from our Intro to R Course
- cheatsheets from that course
Useful (+ mostly Free) Resources
Want more?
Tidyverse Skills for Data Science Book: https://jhudatascience.org/tidyversecourse/ (more about the tidyverse, some modeling, and machine learning)
Tidyverse Skills for Data Science Course: https://www.coursera.org/specializations/tidyverse-data-science-r
(same content with quizzes, can get certificate with $)R for Data Science: http://r4ds.had.co.nz/
(great general information)R basics by Rafael A. Irizarry: https://rafalab.github.io/dsbook/r-basics.html (great general information)
Open Case Studies: https://www.opencasestudies.org/
(resource for specific public health cases with statistical implementation and interpretation)Dataquest: https://www.dataquest.io/
(general interactive resource)
Useful (+ mostly Free) Resources
Need help?
Various “Cheat Sheets”: https://www.rstudio.com/resources/cheatsheets/
R reference card: http://cran.r-project.org/doc/contrib/Short-refcard.pdf
R jargon: https://link.springer.com/content/pdf/bbm%3A978-1-4419-1318-0%2F1.pdf
R vs Stata: https://link.springer.com/content/pdf/bbm%3A978-1-4419-1318-0%2F1.pdf
R terminology: https://cran.r-project.org/doc/manuals/r-release/R-lang.pdf
Summary
- R is a powerful data visualization and analysis software language.
- Lots of resources can be found on the website.