BEST FOR: People who have taken a class or two in statistics and are still wondering what it's all about. This is a big picture book on the philosophy of statistics with some historical context.

BEST FOR: Non-statisticians who want simple rules to follow when trying to understand a chart or a statistical analysis.

BEST FOR: People who are generally curious about how statistical thinking applies in specific situations but want to avoid too much math.

BEST FOR: People who want a deep dive into the details of when and why people use specific statistical techniques without a lot of math.

BEST FOR: People want to get their hands dirty but don't know where to start. Teaches you how to work with data using the R programming language without bogging you down with a lot of theory

BEST FOR: Programmers, computer scientists and Python users. This book teaches you statistics concepts by showing you how to code them from first principles.

The one downside is you don't learn state of the art statistics packages.

BEST FOR: People who want to learn some statistics theory but haven't done much calculus or linear algebra. It's a solid introduction to probability theory but not much practical statistics.

BEST FOR: People with a good understanding of calculus and some exposure to probability. It's at the advanced undergraduate level and has a generally conversational style.

BEST FOR: People with a solid math background including linear algebra and a few calculus courses. We use this in my graduate program. It's a solid textbook that covers most of the basics.

BEST FOR: Mathematicians and people with a very strong mathematical background. I don't know this one as well, but I recently purchased it and have been enjoying it. A few mathematicians have told me that this was the perfect book for them.