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This classic text takes an applied and computer-oriented approach to its topical coverage. The book is intended for one or two semester courses in biostatistics at the undergraduate or graduate level offered by departments of biostatistics, statistics, mathematics, nursing and other allied health disciplines, and is also used in some departments of forestry and animal husbandry. Nearly all the examples and exercises make use of real data from actual research projects and reports from health sciences literature. Where appropriate, Minitab, SPSS and SAS commands and printouts are included as part of the examples and solutions to exercises.
- Sales Rank: #10757864 in Books
- Published on: 2005-03-21
- Original language: English
- Number of items: 1
- Dimensions: 9.41" h x 1.91" w x 7.81" l, 4.11 pounds
- Binding: Hardcover
- 782 pages
From the Publisher
Like its predecessors, this edition stresses intuitive understanding of principles rather than learning by mathematical proof. Provides broad coverage of statistical procedures used in all the health science disciplines. This version contains a greater emphasis on computer applications, and most of the statistical techniques include the MINITAB commands by which they can be applied.
From the Back Cover
Develop the statistical tools needed in the allied health fields �
Anyone entering the allied health field needs to have a working understanding of how data can be turned into useful information. Now in its ninth edition, Wayne W. Daniel’s Biostatistics: A Foundation for Analysis in the Health Sciences provides a comprehensive introduction to biostatistics as it is used in the biological sciences.
Designed for the undergraduate and graduate student across a range of fields, from the health disciplines to forestry and animal husbandry, the text takes an applied and computer-oriented approach to its topical coverage. Its chapters take you from the basic concepts of probability through hypothesis testing, linear regression and correlation, the analysis of variance, chi-square distribution, nonparametric and distribution-free statistics, and more.
This new edition adds much new and expanded material, including such features as:
- Integration of new applications from several biological science fields throughout the pages
- Highlighting of main ideas with bulleted objectives at the start of each chapter
- Summary boxes of formulae and statistical rules for easy reference and review
- Support for multiple programs such as SPSS, SAS, and STATA, in addition to Minitab
- Screen captures and technology boxes with step-by-step help
- Real-world practice through examples and exercises using data from actual research projects and reports
About the Author
Wayne W. Daniel� is on the faculty of Georgia State University, Atlanta, Georgia.
Most helpful customer reviews
24 of 24 people found the following review helpful.
Not as impressive as I first thought
By A. Shankar
Daniel obviously knows his statistics; but, I wouldnt think that is too helpful for individuals reading or studying from his textbook.
The reasons are numerous, and all these reasons would reduce anyone's chances of solely using this book, or even using it at all.
The textbook is well organized, however Daniel's writing often is pedantic, repetitive (not in the helpful way) and ambiguous at best.
The examples and solutions occassionaly have serious errors in them which affect the overall outcome of the test (A second consideration is that the book is in it's 8th edition!!! therefore such errors are unacceptable for a person such as myself).
An example can be found on page 239 (example 7.3.2). The pooled variance, as calculated by Daniel is approximately off by 100 simply because he didnt give attention to dividing the numerator with the proper pooled D.F of the samples. The chapter ironically was on hypothesis tests, something extremely important to any line of empirically oriented statistics.
In Chapter 8; which is probably the most important chapter in Bistatistics (ANOVAs) he does not mention the relationship between MSW and sample SD. Also, his usage of Summation in formulas often are unnecessarily overcomplicated. Such is not even seen in professional journals.
I did like this textbook regardless of its many shortcomings, its not because I liked the author's style of writing. Its more or less the fact that my lecturer (I assume) used this book heavily in his lectures and so I used it as a supplementary text.
I would suggest, Chap T. Le's Introductory Biostatistics. However he goes too much into nonparametric methods and proportions and doesnt cocentration (to the degree I wanted) on continous data.
More robust and probably cost effect books are :Introductory Statistics for the Life Sciences by Samuels. But the Best book I have ever seen on the subject is "Introductory Biostatistics for the health sciences" By Chernick and Friis. The book is well priced and no portion of this book, I have seen as being useless.
12 of 12 people found the following review helpful.
Excellent Text for 2nd Statistics Class
By W. Mary
I'm taking my first biostatistics class in medical school, but the text I am using in class (Rosner) has lost me. I subsequently borrowed Daniel's book from the library (only because it has 7th editions), and I am glad that I picked it! Daniel is a good writer. The book is well organized and laid out. Important concepts are emphased and explained with minimum mathematics involved. The well thought out examples are worth working through as well for clarification of the applications of important concepts. However, as a beginner in statistics, I was lost in the midst of mathematics on certain concepts (given that I have a relatively strong mathematics background) without really understanding the meaning of some very basic terms, like percentile, confidence intervals.
What I do is to read another reference book that explains the very basic concepts in plain English first before reading this text. I am currently using Munro's Statistical Methods for Health Care Research. While both of them cover the same set of concepts, Daniel gives me the mathematical and more advanced explainations compare to Munro.
4 of 5 people found the following review helpful.
Solid introductory reference
By A Customer
The title is very appropriate - this text provides a solid foundation in biostats. I used it for an intro course in grad school, and working through the text was very worthwhile. Previously cloudy concepts are now more clear, and I have a great reference for future use. More in-depth biostats deserves a consultation with a statistician, not a longer text. I agree with other reviewers that there are occasional mistakes (which need to be fixed - this is not even the first edition), but overall I would still highly recommend it.
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