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Rating: 
Summary: Now that I have read it
Review: Although three years have past since the third edition there is very little difference in the fourth edition. There is a new second author but the first 7 chapters are virtually identical. The biggest change appears to be the expansion of Chapter 8 from 6 sections to 16 with p-values introduced and explained in various contexts and type I and type II errors introduced one chapter earlier. The introduction of hypothesis testing along with estimation occurs in Chapter 8. This may be helpful to instructors if they tend to strictly follow the order in the text. Chapter 9 is somewhat shorter. These two chapters are now organized by one and two sample problems rather than by estimation and testing. It is not clear to me that this is a better way to organize and introduce the material. In the end, the text is only 15 pages longer than the third edition and there are no new chapters. There seem to be fewer exercises overall. Although there are noticeable differences in Chapters 8 an 9, there is very little difference in the other chapters. Most of the exercises are the same (with a few deleted from the new edition). The authors claim to put more emphasis on the use of computers to solve problems. But this is not easily discernable. I only noticed some brief mention of SPSS version 9 in the ANOVA chapter.
Rating:
Summary: Now that I have read it
Review: Although three years have past since the third edition there is very little difference in the fourth edition. There is a new second author but the first 7 chapters are virtually identical. The biggest change appears to be the expansion of Chapter 8 from 6 sections to 16 with p-values introduced and explained in various contexts and type I and type II errors introduced one chapter earlier. The introduction of hypothesis testing along with estimation occurs in Chapter 8. This may be helpful to instructors if they tend to strictly follow the order in the text. Chapter 9 is somewhat shorter. These two chapters are now organized by one and two sample problems rather than by estimation and testing. It is not clear to me that this is a better way to organize and introduce the material. In the end, the text is only 15 pages longer than the third edition and there are no new chapters. There seem to be fewer exercises overall. Although there are noticeable differences in Chapters 8 an 9, there is very little difference in the other chapters. Most of the exercises are the same (with a few deleted from the new edition). The authors claim to put more emphasis on the use of computers to solve problems. But this is not easily discernable. I only noticed some brief mention of SPSS version 9 in the ANOVA chapter.
Rating: 
Summary: Horrible at explaining concepts and formulas
Review: As a statistics tutor, I have had to spend countless hours explaining to students the content of this book due to its lack of ability to make concepts clear. This book assumes that the reader has a background in statistics and does not need detailed explanations. I have had to use my personal statistics book (Elementary Statistics by Mario F. Triola) to properly teach the students statistics. This book is frustrating to say the least.
Rating:
Summary: Fair overview, but not always clear.
Review: Kuzma's book provides a good non-mathematical treatment of introductory biostatistics for health science majors. The book is at the right level for my undergraduate students in the Health Science Department at Cal State Long Beach. Kuzma's experience at Loma Linda Hospital has given him a good sense of the appropriate topics and level for these students. I have supplemented the book with my own materials on bootstrap methods and have also considered including topics on epidemiology and problems requiring meta analyses. The downside to the book is that Kuzma is not a professional statistician and hence there are occasional technical errors and poor exposition of techniques. Even given these shortcomings, it is the best currently available book at this level. At a slightly higher graduate level, I would recommend Altman's book "Practical Statistics for Medical Research".
Rating:
Summary: good introduction for health science majors
Review: Kuzma's book provides a good non-mathematical treatment of introductory biostatistics for health science majors. The book is at the right level for my undergraduate students in the Health Science Department at Cal State Long Beach. Kuzma's experience at Loma Linda Hospital has given him a good sense of the appropriate topics and level for these students. I have supplemented the book with my own materials on bootstrap methods and have also considered including topics on epidemiology and problems requiring meta analyses. The downside to the book is that Kuzma is not a professional statistician and hence there are occasional technical errors and poor exposition of techniques. Even given these shortcomings, it is the best currently available book at this level. At a slightly higher graduate level, I would recommend Altman's book "Practical Statistics for Medical Research".
Rating:
Summary: Fair overview, but not always clear.
Review: The book is well organized from start to finish, and builds well on the topics as they are presented. Unfortunately, it often makes assumptions about the reader's knowledge of the topic, usually around formula usage that is confusing and difficult. As a primer for statistics, this one falls a little short.
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