Rating: 

Written in a very friendly style. Not written like a
textbook.

I disagree that this book will let you master statistics. It
will most likely make you competent at reasonably simple stuff. I think
some of the detail presented is sloppy in a couple of places. There are a
few more mistakes in the book than I would have expected for such a large
team involved. It is very much more than a single person writing a
book.

Critisms:

• Over the years I have seen a number of problems when people choose
  to work with units of "percent". I think the only good solution is to
  discourage people from using percent in any description or analysis.




• The term "normal distribution" has far too much baggage to be useful
  to anyone. I think every statistics book should endeavor to get people to
  avoid the term. Perhaps one incentive to get people to stay away from
  this term is to point out that distributions of undefined variance
  exist.




• There also exist many problems where the domain of the independent
  variable is finite, and the use of a Gaussian in those circumstances can
  lead to problems.




• Starting the book off with charting is as good a place to start as
  any. Axis origins are discussed, axis transformations aren't.




• Frequency is used in many places where a count might be better.
  For example, frequency is often a "rate" of doing something (in my world),
  which means that a sample histogram is the same as a population histogram
  (except for noise in the sample).




• Some uses of the word variance seem to be describing standard
  deviation.




• I think the goodness of fit testing on the croupiers needs to be
  expanded.




• Some people will think that correlation requires a straight line
  relation between variables, not any functional relation between
  variables.




• The bivariate example chosen is not a good choice for explaining
  regression, or at least the simple kind of regression done for this
  example. This example really calls for showing the difference between
  Y(X) regression, X(Y) regression and orthogonal regression.

Not that I am short, but I hope Julie never gets a
date. :-)

That notwithstanding, if a person was only going to have a
single statistics book, this would probably be a very good choice.

http://elug.ca/reviews/head_first_statistics.shtml