In the following weeks, we will continue to release a series of posts to introduce resources on statistical computing, data visualization and to help you catch up with the ever-changing industry trends.
We therefore present to you the Data Resources Mini Series – Not Just Buzzwords.
(Source: https://xkcd.com/1838/)
# secret recipes of learning R before we start
# Always read the R official documents first.
# Stack Overflow and Google are your friends.
# Do a project. Choose a complex one.
# Be a teacher. Explain something to someone else.
# Learn something even harder than you actually need but in related areas. Then return to your problems.
Wait, did I say “come to the Library workshops” in the secret recipes? If you did not make to the R workshops, here are the workshop notes.
Alright. Let’s take a look at some tutorials and blogs for learning R with general purposes. We have something for everyone from absolute beginners to more experienced users.
Next time we will share books and blogs on data visualization. Stay tuned!
01
the starting point
An introduction to R, CRAN project
Everything you need to know to get you started.
02
knowing enough to get by
Cheat Sheets of using R for various purposes from the Base R all the way to deep learning with R.
Quick-R
A quick access to R, especially if you are from Stata, SAS, SPSS etc.
03
using R in projects
R for Data Science, Garrett Grolemund and Hadley Wickham
Don’t miss the exercises.
Advanced R, Hadley Wickham
R programming.
04
Coursera online classes
Data Science Specialization, John Hopkins University
R programming + data analysis + research workflow.
Statistics with R Specialization, Duke University
Some people find the JHU courses too R heavy. This specialization focuses on teaching statistics while people learn to use R through projects.
05
blogs
R news and tutorials for numerous topics.
R graphs and codes by chart types. Previously had a focus on visualization with ggplot2 but not limited to that.
Previously…
*Source of cover image: https://smbc-comics.com/?id=2613
presented by Yun Dai
(yun.dai@nyu.edu)
edited by Scotty Sun