Step 1
Take some courses: If you are eligible for IQSS courses (you need to be a Harvard affiliate), then take some of the R / Python courses at IQSS:
https://dss.iq.harvard.edu/
We also have an account registered through bachtech@mclean.harvard.edu for DataCamp. You should do the following courses:
Introduction to R
Intermediate R
Data Analysis in R: the data.table way
Importing and Cleaning Data in R: Case Studies
Importing Data in R (Parts 1 & 2)
Cleaning Data in R
Writing Functions in R
For additional courses, you can browse by language and topics (such as programming, data manipulation and importing and cleaning data) – https://www.datacamp.com/tracks/skill
The Institute for Quantitative Social Science (IQSS) at Harvard also offers free R workshops that are open to all Harvard affiliates (https://www.iq.harvard.edu/event/introduction-r; check out the Events page for other, more advanced courses like regression and plotting in R). If you prefer not to attend, you can also download the workshop slides and R code (http://tutorials.iq.harvard.edu/). They also offer open office hours (https://www.iq.harvard.edu/calendar) where you can bring a dataset and someone will sit down and help you analyze it. If you choose to do this, make sure to email them first at help@iq.harvard.edu.
Step 2
Read the Andy Field book: Statistics in R. Really just the first 5 chapters.
Step 3
Get your hands dirty
We will be compiling well commented code + data into a central place. This will be code + data that is from TestMyBrain, doing the actual kinds of analysis we already do. You should play with this code and data, modify it, and see if you can change some of the behavior of the functions (in your own directory of course – don’t change the actual model)
Step 4
Pay it forward
When you write your code, comment it clearly and profusely, like you are explaining it to someone who doesn’t live in your head or even in your field. Then copy it – with clear naming and any associated files in the same directory — to the “R_repo” folder in Dropbox. That way, other people can use it to build their own data analysis scripts.
Additional Resources and Documents
Please paste any URLs/documents below along with highlights of the resource you found particularly useful
https://cran.r-project.org/doc/contrib/Paradis-rdebuts_en.pdf
Explains syntax, manipulation, graphics and basic statistical commands.
http://ggplot2.tidyverse.org/index.html
Documentation for ggplot2 – a great graphics package for R.