Daniel Kunin from Brown University created a totally stunning and interactive site named Seeing Theory. It provides a visual introduction to many concepts in statistics and probability. Definitely worth checking out and sharing with others.
Tip: it does not work well on mobile.
Matthias Vallentin, a computer science PhD student at UC Berkeley, has published a Probability and Statistics Cookbook. The book can be freely downloaded in PDF format via the website. Also, the latex source is available on Github. Matthias states that others are free to fork the source and make changes.
The book is not a textbook. It is more of a cheatsheet. It contains many of the common probability and statistics techniques and the associated formula. I would consider this book to be an excellent resource to have around.
Previously I mentioned that online statistics learning resources are not abundant.
Well, here is a new online book for learning statistics. It is geared towards programmers, and it looks to be a great fit for people wanting to learn data science. Here is a small excerpt from the Preface:
It emphasizes the use of statistics to explore large datasets.
I have only had time to quickly browse the book, but it looks quite good.
Think Stats: Probability and Statistics for Programmers
(The book has a Creative Commons license, so it is free and OK to download)