Resources

Here are additional resources to help you on your R journey - either before, during, or after the class! Click each section to expand.

Help Getting Started

• Guide to using Slack
• R reference card
• R introductory guide
• R jargon
• R terminology
• What is the Tidyverse/what packages are in it?
• Where do package names come from?
• Lawlor et al. 2022: Ten simple rules for teaching yourself R

Class Cheatsheets

• Day 1 - RStudio & Reproducibility Cheatsheet
• Day 2 - Basic R & Data Input/Output Cheatsheet
• Day 3 - Data Subsetting Cheatsheet
• Day 4 - Data Summarization & Data Classes Cheatsheet
• Day 5 - Data Cleaning Cheatsheet
• Day 6 - Data Manipulation & Data Visualization esquisse Cheatsheet
• Day 7 - Data Visualization ggplot2 & Factors Cheatsheet
• Day 8 - Statistics Cheatsheet
• Day 9 - Functions Cheatsheet
• Additional RStudio “Cheatsheets”
• Really great stringr Cheatsheet

Troubleshooting Guides

• Guide on when to use quotes or backticks
• Guide on what functions require pulling values out first

Keyboard Shortcuts

• RStudio shortcuts can be found here

• Shortcut for the %in% operator can be found here

Extra help

Need help with data import?

• Video on data import
• Video for PC users who want to see how to move files around (especially from downloads)
• Video for Mac users who want to see how to move files around (especially from downloads)
• Extra information about file paths

Need extra guidance on wrangling?

• Guide on janitor
• Guide on cleaning complicated names

Need help with joins?

• full-join() animation
• inner_join() animation
• left-join() animation
• right-join() animation

Need help with plots?

• ggplot2 gallery - See what is possible with ggplot2 to create graphs in R
• ggplot2 theme cheatsheet
• Visualization best practices
• Guide on when to use which plot
• Guide to building up a ggplot2 figure

Need help with stats?

• Guide on when to use what stats test
• Modeling 101
• Common statistical tests are linear models (why understanding linear models will get you far!)
• Interpreting GLM output (e.g., deviance)
• Guide on why set.seed can be useful

Want help creating tables?

• Guide on making nice tables from stats tests in R
• Guide on making custom styled tables in R with the kableExtra package
• Guide on using DT table to make interactive tables

Courses & Conferences

Online Courses and Resources

• Tidyverse Skills for Data Science Book (a great next step to learn more about the tidyverse, some modeling, and machine learning)
• Tidyverse Skills for Data Science Course (same content with quizzes, can get certificate with $)
• Open Case Studies
  (resource for specific public health cases with statistical implementation and interpretation - a great next step for learning more about stats and wrangling!)
• R for Data Science (great general information)
• R for Applied Epidemiology (Similar general introductory course)
  
• R basics chapter of Introduction to Data Science by Rafael A. Irizarry(great general information)
• Dataquest (general interactive resource)
• Quick R Guide (nice free general resource)
• Introduction to Reproducibility
• Advanced Reproducibility

Classes at JHU

• PH.140.621, PH.140.622, PH.140.623, PH.140.62 - Statistical Methods in Public Health I, II, III, and IV - The class is mostly taught in STATA, but you can also join a group of students working in R. The class covers many topics in statistical analysis for public health data.
• PH.140.778 - Statistical Computing, Algorithm, and Software Development - A more advanced course for working with data in R.
  • Content for similar topics as this course can also be found on Leanpub.

R Conferences

• The RStudio/Posit conference has lots of useful workshops!
• useR! — International R User Conference information can be found here.

R for Stata, SPSS, and SAS files

• The Haven package
  (This package is super useful for reading and writing files so that they are compatible across Stata, SPSS, SAS, and R)
• R vs Stata
  (See page 505)
• R <-> SAS Cheatsheet
• SAS to R Converter
  
• Guide to learning R as a SAS user
• You might also find large language models like ChatGPT useful for code conversion. Be sure to check the output because AI makes mistakes!

Comparison of Python and R

• A helpful article about the difference between these two languages.

Videos of Previous Online Lectures

From Summer Institute 2023

Day	Link to Video
Introduction	https://youtu.be/aIJrFKQYnP8
RStudio	https://youtu.be/cxHVf5rTK1c
Reproducibility	https://youtu.be/af9B9-_df1o
Basic R	https://youtu.be/5io-iZDutH8
Data Input	https://youtu.be/sllVVRD5YE4
Subsetting Data	https://youtu.be/dWdK3bnAGm8
Data Classes	https://youtu.be/Q4ubnU35TUs
Data Summarization	https://youtu.be/xsI30yCGgTQ
Data Cleaning	https://youtu.be/qL6_yfiR9Jk
Data Manipulation	https://youtu.be/fQ7lDp8Svw0
Intro to Data Visualization	https://youtu.be/D5RdNwadtR0
Data Visualization	https://youtu.be/fKj1iBxLwyk
Factors	https://youtu.be/yqU5zHVh-qA
Statistics	https://youtu.be/T9Oh0miYhZ0
Data Output	https://youtu.be/x2OuR4JhPLY
Functions	https://youtu.be/jWv5RSXq5mo

From Summer Institute 2022

Day	Link to Video
RStudio and Reproducibility	https://www.youtube.com/watch?v=eCsD0f0q6rY&t=9s
Basic R	https://www.youtube.com/watch?v=2YRgDG3qsho
Data IO	https://www.youtube.com/watch?v=ejnBAdA2N1c
Subsetting Data	https://www.youtube.com/watch?v=GFa6dXAezJg
Data Summarization	https://www.youtube.com/watch?v=kj_69maSANk
Data Classes	https://www.youtube.com/watch?v=zoVciFJieLY&t=21s
Data Cleaning	https://www.youtube.com/watch?v=GhK8xMUBNwg
Data Manipulation	https://www.youtube.com/watch?v=qP73AWUjfAU
Intro to Data Visualization	https://www.youtube.com/watch?v=OCVo6vWrKL4
Data Visualization	https://www.youtube.com/watch?v=9UPlZqOfT_s
Factors	https://www.youtube.com/watch?v=0fE756trEEE
Statistics	https://www.youtube.com/watch?v=jZ5sskAdAJU&t=4s
Functions	https://www.youtube.com/watch?v=dx-85RzN1G0

From Winter Institute 2022

Day	Link to Video
RStudio	https://youtu.be/zpAQrglIJb0
Basic R	https://youtu.be/_8ZG0G1nNlA
Reproducibility	https://youtu.be/ChFTiZ7Clo4
Data IO	https://youtu.be/bnYN7AfYGNM
Subsetting Data	https://youtu.be/kPU3dl25ox8
Data Summarization	https://youtu.be/C_a8bGGdrIA
Data Classes	https://youtu.be/ZCe30kIJ0Xc
Data Cleaning	https://youtu.be/siFL49CCsJg
Data Manipulation	https://youtu.be/7M81XUIY5SE
Intro to Data Visualization	https://youtu.be/Md46muvSrYE
Data Visualization	https://youtu.be/YjDT3ZUSiR4
Factors	https://youtu.be/Co4l0YhuYSk
Statistics	https://youtu.be/3nSIN1mu8uw
Functions	https://youtu.be/XUKJtUYU1Ic

From Summer Institute 2021

Day	Link to Video
RStudio	https://youtu.be/zpAQrglIJb0
Basic R	https://youtu.be/md30mwFJ2_Q
Data IO	https://youtu.be/6xNyETqIqZU
Subsetting Data	https://youtu.be/YeBSc2YXr4U
Data Summarization Part 1 + 2	https://youtu.be/yL3BGDWtVC4
Data Classes	https://youtu.be/zBCvbikMTAc
Data Cleaning	https://youtu.be/TaREvr5evwk
Data Manipulation	https://youtu.be/-039V99I-PE
Reproducibility	https://youtu.be/ui9dJLqtdCs
Statistics	https://youtu.be/EJwlBoBHoz4
Data Visualization	https://youtu.be/ngQX9khx7UQ
Functions	https://youtu.be/epIujSKgNi4

From Winter Institute 2020

Day	Link to Video
RStudio and Data Classes	https://youtu.be/vyIsDnsq5jY
Subsetting Data	https://youtu.be/mT8lSagYbjM
Data Summarization Part 1	https://youtu.be/SZYpzt9zy0g
Data Classes	https://youtu.be/82zSA1N0mnA
Data Cleaning	https://youtu.be/G3V2YPaQN34
Data Manipulation	https://youtu.be/43MPdw5bf4o
Statistics 1	https://youtu.be/Jr4ljyzrr4U
Statistics 2	https://youtu.be/ub2BSbK9lMM

From Summer Institute 2017

Day	Link to Video
Day 1	https://youtu.be/Xi-wsACc7p0
Day 2	https://youtu.be/u1FQt9Hr8iw
Day 3	https://youtu.be/woc7AGJTzZw
Day 4	https://youtu.be/RZ7eVIMPIes
Day 5	https://youtu.be/e8cFV8wluC0