I am personally disappointed with this book for the following reasons:



1) Most math books have the answers in the back for nearly all of the odd programs; this book does not. In fact, there's little rhyme or reason for the answers listed in the back. In short, most odd problem answers are not listed yet some of the even answers are given. Go figure..



2) I don't care for the chapter and section layouts. In my calculus text, everything is more developed. In some of the better texts, definitions are given before the explanations are given, which in turn precedes the examples given. This book does not of that. There is not a comprehensive list of definitions at the end of the chapter, the in-chapter definitions are weak, and they fail to fully develop the material before jumping into examples, etc.



But, it is a textbook and it costs > $100, so by publisher standards, it is a home run.

I am personally disappointed with this book for the following reasons:

1) Most math books have the answers in the back for nearly all of the odd programs; this book does not. In fact, there's little rhyme or reason for the answers listed in the back. In short, most odd problem answers are not listed yet some of the even answers are given. Go figure..

2) I don't care for the chapter and section layouts. In my calculus text, everything is more developed. In some of the better texts, definitions are given before the explanations are given, which in turn precedes the examples given. This book does not of that. There is not a comprehensive list of definitions at the end of the chapter, the in-chapter definitions are weak, and they fail to fully develop the material before jumping into examples, etc.

But, it is a textbook and it costs > $100, so by publisher standards, it is a home run.

I took an AP statistics course in high school that went into much better detail than this book ever did. With this book I could not have made it out with the understanding I currently have of statistics without having taken that class years ago. Our instructor was pretty much incompetent, so it was a true test of how well the textbook got the job done. I watched my classmates really struggle with this book. The problem is that the concepts of different test statistics and what they actually mean are too oversimplified. The book does a great job of teaching how through an extensive amount of examples, but not why, and not enough instances or explanations of what should be done when problems deviate from the given example. It is really important in statistics to know how to handle different kinds of data and which tests to apply to them, but the book in my opinion did a poor job of distinguishing and explaining the different types of tests, as well as how the results should be analyzed. I would definitely recommend looking elsewhere for a good statistics textbook. When it comes to mathematics, theory (knowing why a problem is solved the way it is and why it works) is just as important as being able to correctly solve the problem.

This textbook was required for my statistics class at the University of Wisconsin. I found the book easier to follow with better examples than my lecture was. Often I cannot learn anything right from the book, but this book made it easy with complete examples and simple descriptions of variables and theory. The book was so good, in fact, I rarely made it to class because I learned it better from the book!

The book is reasonably good at explaining simple concepts.

However, the lack of detail does not allow for real life application in a biological field: the concepts are oversimplified and the examples given do not reflect the difficulty of actual basic statistics work in the life sciences.

If you want to buy this book, the questions you should ask yourself are:

1. Are you buying this book just to pass a basic statistics course?

2. Are you buying this book to expand your point of view and understanding of real life applications?

The book is reasonably good at explaining simple concepts.

However, the lack of detail does not allow for real life application in a biological field: the concepts are oversimplified and the examples given do not reflect the difficulty of actual basic statistics work in the life sciences.

If you want to buy this book, the questions you should ask yourself are:

1. Are you buying this book just to pass a basic statistics course?

2. Are you buying this book to expand your point of view and understanding of real life applications?

In a word - wow. This is an outstanding textbook for undergraduate biology students. The number of practical, real life examples exceeds anything else I have seen in a statistics book, permitting the student to follow theory immediately with concrete practice. Examples are drawn from all axes of biology as well - physiology, biogeochemistry, pharmacology, microbiology, animal behaviour and more. I have been disappointed with previous textbooks which fall down in the following ways: 1) too much emphasis on the mathematics of calculation, or 2) lack of practical introductory treatment of moderately advanced topics which are nonetheless necessary to practitioners. This book for me strikes a very good balance between understanding the underpinnings without getting lost in equations, and getting your hands dirty with data in order to learn by example. Coverage is as wide as necessary today: introduction to logistic regression, and a clear treatment of interaction in two-way ANOVA. I do note that multiple regression is not touched. The sole drawback: sticker shock. It will be difficult for students to pay for a book that costs about $100 US. But at least you get what you pay for in this case.

In a word - wow. This is an outstanding textbook for undergraduate biology students. The number of practical, real life examples exceeds anything else I have seen in a statistics book, permitting the student to follow theory immediately with concrete practice. Examples are drawn from all axes of biology as well - physiology, biogeochemistry, pharmacology, microbiology, animal behaviour and more. I have been disappointed with previous textbooks which fall down in the following ways: 1) too much emphasis on the mathematics of calculation, or 2) lack of practical introductory treatment of moderately advanced topics which are nonetheless necessary to practitioners. This book for me strikes a very good balance between understanding the underpinnings without getting lost in equations, and getting your hands dirty with data in order to learn by example. Coverage is as wide as necessary today: introduction to logistic regression, and a clear treatment of interaction in two-way ANOVA. I do note that multiple regression is not touched. The sole drawback: sticker shock. It will be difficult for students to pay for a book that costs about $100 US. But at least you get what you pay for in this case.

I wish I knew where my book was...