I found this book to be a godsend. I never took statistics and always wanted to better understand the deep conceptual ideas in the field. I had so many frustrating experiences with books that came highly recommend to me, and turned out to be not what I wanted at all. They spend chapters and chapters beating around the bush, conversationally talking about general ideas around data management and measurement bias and research design and different ways of charting data sets.
I cannot tell you how frustrating this was for me. I wanted just the meat: the core mathematical concepts on which statistical models and inferences are built. Don't tell me a folksy story about gathering soil samples, show me the tools and what they can do, both their power and their limitations. I can think for myself about how to apply those concepts.
I loved this book for being exceptionally clear and terse. I was hooked from the first sentence: "Probability is a mathematical language for quantifying uncertainty." That one sentence makes the concept clear in a way that the entire chapter on probability from "Statistics in a Nutshell" (http://www.amazon.com/Statistics-Nutshell-Sarah-Boslaugh/dp/...) did not.
I'm not someone who thrives on theorems and proofs, I thrive on concepts. And I found this book dense with clear explanations of the key concepts.