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This page collects resources for our team to use and learn from. We onboard new students nearly every semester, they learn to code in R, Python, etc. and can find useful learning guides for that here (thanks to Prof. Kalinowski of Quinnnipiac's Economics and Data Science program).

Additionally, we are intentionally as open and transparent as possible.  So we'll add links her to our data sources and other resources we think might be of interest to readers.

The site is structured with "basics" and then topical. The first two books are considered the initial books we all need to follow. They aren't "basic" in any other sense and you will return to them even when you become a more advanced programmer.

The next books are topical guides for graphing, time series, etc.  Currently they are mostly in R.

This has been our go-to website/book for learning R.  We recommend people start by following the book 100% for the first 3 chapters. It's fun and easy, but take your time and don't skip, and by the time you finish, you'll be able to do all sorts of basic graphs.  The next big hurdle is making it through Chapter 5 which covers basic data manipulation. After that, you can skip around a bit and learn as needed, combine with Goolge or ChatGPT questions. Here's the URL:

Image by Cris DiNoto

This is a new book for the team.  We started in R but are now expanding to Python.  This is the top recommendation for starting data analysis in Python. Here's the URL:

Image by Hitesh Choudhary

This book is helpful in understanding and expanding your ability to make graphs in R. The URL:

Image by Giulia May

This book was helpful to me (Chris Ball) for understanding mathematical manipulations in R. The URL:

Image by Roman Mager

This book was helpful to me (Chris Ball) for understanding some basic statistics (more mathematical statistics) in R. The URL: 

Image by Edge2Edge Media

This book was helpful to me (Chris Ball) for understanding some basic time series in R. It's called "forecasting" but that's basically an application using time series. So I think of this as a good intro time series in R book. The URL:

Image by petr sidorov
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