Introduction to Data Exploration and Analysis with R

Introduction to Data Exploration and Analysis with R

There are a lot of resources online to learn R. Some of them are extremely well-written and well-structured, but approach things from a different perspective than I find useful. Some of them are expansive and touch on a massive number of topics, but either don’t go as thoroughly into these topics as might be helpful, or have an interesting writing style or are otherwise hard to follow.

I’ve got a very specific idea of how R should be taught, at least to those interested in using it for data science and other analytical applications. And so in 2018 I began working on a reader - conceived at the time as a series of lecture notes, to support a 3-credit undergrad course - that could be used to learn R that way. However, as I started giving out copies of the reader to friends for feedback, I noticed that a lot of them found the book useful to learn R on their own, and would rather learn that way than in a lecture environment. As such, I started shifting the content into more of a standalone book, attempting to teach R for use in analysis work in both scientific and business contexts.

The book is currently going through a second round of edits, and may be found in its current state at this link. If you find the book helpful (or if you’ve got suggestions on how it could be improved), please drop me a line - I love hearing from people who have stumbled across it!

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Michael Mahoney
Analyst, Supply Chain and Logistics (Forecasting Analytics)