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ISBN : 0131008463
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Zar’s Biostatistical Analysis, Fifth Edition, is the ideal book for readers seeking practical coverage of statistical analysis methods used by researchers to collect, summarize, analyze and draw conclusions from biological research. The latest edition of this best-selling textbook is both comprehensive and easy to read. It is suitable as an introduction for beginners and as a comprehensive reference book for biological researchers and other advanced users.
Introduction; Populations and Samples; Measures of Central Tendency; Measures of Dispersion and Variability; Probabilities; The Normal Distribution; One-Sample Hypotheses; Two-Sample Hypotheses; Paired-Sample Hypotheses; Multisample Hypotheses: The Analysis of Variance; Multiple Comparisons; Two-Factor Analysis of Variance; Data Transformations; Multiway Factorial Analysis of Variance; Nested (Hierarchical) Analysis of Variance; Multivariate Analysis of Variance; Simple Linear Regression; Comparing Simple Linear Regression Equations; Simple Linear Correlation; Multiple Regression and Correlation; Polynomial Regression; Testing for Goodness of Fit; Contingency Tables; More on Dichotomous Variables; Testing for Randomness; Circular Distributions: Descriptive Statistics; Circular Distributions: Hypothesis Testing
For all readers interested in biostatistics.
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- Hardcover: 960 pages
- Publisher: Pearson; 5 edition (February 25, 2009)
- Language: English
- ISBN-10: 0131008463
- ISBN-13: 978-0131008465
- Product Dimensions: 1.3 x 8 x 9.8 inches
- Shipping Weight: 3.4 pounds (View shipping rates and policies)
Free Biostatistical Analysis
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This book is popular because it is well written and authoritative. It is written for biologists, medical students and researchers who do not have any prior knowledge of probability or statistics and may have little mathematical training as well. It serves as an introductory text providing many homework exercises. It can also be used as a reference. It is very thorough and covers most of the important topics required for biological problems. The needed probability is introduced when necessary.
There is the usual emphasis on hypothesis testing and regression. Correlation and analysis of variance are also very well covered. Important issues of sample size determination are covered and many solutions are provided in easy to use box descriptions.
As the author points out in the preface, in order to make this text a good reference it is extensive (663 pages of text followed by appendices and a large number of tables). It also includes a wealth of useful reference articles and books. Consequently, there is too much material for a one semester course. The author provides instructors with guidelines for sections to cover in an introductory course.
Notable topics covered in this text that is rarely found in introductory biostatistics books include multivariate methods especially the multivariate analysis of variance (MANOVA)and inference for circular data.
Recent developments in meta analysis, Bayesian statistics and bootstrap methods are not covered. In fact, these topics are not covered at all. Also, the important topic of missing data is omitted. Outliers are only covered briefly and just a few references are given but the major references, the texts by Hawkins and the treatise of Barnett and Lewis are neglected.
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