547 pages, b/w illustrations, tables
Designed to cover techniques for analysis of data in the animal sciences, this popular textbook provides an overview of the basic principles of statistics enabling the subsequent applications to be carried out with familiarity and understanding. Each chapter begins by introducing a problem with practical questions, followed by a brief theoretical background. Most topics are followed up with numerical examples to illustrate the methods described using data-sets from animal sciences and related fields. The same examples are then solved using the SAS software package.
Key features of this third edition:
- Updated throughout, and covers a wealth of new distributions and new material on non-normal dependent variables
- Improved clarity of text and examples
- Includes both basic techniques and more complex procedures to provide an essential resource whatever your level
- Contains exercises and many worked examples in SAS.
Written primarily for students and researchers in animal sciences, the text is also useful for those studying agricultural, biological, and veterinary sciences.
Reviews of the second edition:
"This book is an excellent text and should be on every animal scientist's bookshelf. It is easy to read and well formatted throughout with numerous easy to follow examples from various disciplines in animal science."
– Terry A Gipson, Small Ruminant Research, 57, 2005
"This is likely to prove a useful text for the serious researcher. Its practical guidance on performing the analyses in SAS makes it a handbook for routine situations."
– Nick Fieller, Laboratory Animals, 39, 2005
1: Presenting and Summarizing Data
3: Random Variables and their Distributions
4: Population and Sample
5: Estimation of Parameters
6: Hypothesis Testing
7: Simple Linear Regression
9: Multiple Linear Regression
10: Curvilinear Regression
11: Fixed Effects One-way Analysis of Variance
12: Random Effects One-way Analysis of Variance
13: Mixed Models
14: Concepts of Experimental Design
16: Change-over Designs
17: Factorial Experiments
18: Hierarchical or Nested Design
19: Split-plot Design
20: Analysis of Covariance
21: Repeated Measures
22: Analysis of Numerical Treatment Levels
23: Discrete, Categorical and other Non-normal Dependent Variables
Solutions of Exercises
Appendix A: Vectors and Matrices
Appendix B: Statistical Tables
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Miroslav Kaps is at the University of Zagreb, Croatia. William R. Lamberson is at the University of Missouri.