Written to meet the needs of both students and applied researchers, Design of Experiments for Agriculture and the Natural Sciences, Second Edition serves as an introductory guide to experimental design and analysis. Like the popular original, this thorough text provides an understanding of the logical underpinnings of design and analysis by selecting and discussing only those carefully chosen designs that offer the greatest utility. However, it improves on the first edition by adhering to a step-by-step process that greatly improves accessibility and understanding. Real problems from different areas of agriculture and science are presented throughout to show how practical issues of design and analysis are best handled.
Completely revised to greatly enhance readability, this new edition includes:
Intended for those in the agriculture, environmental, and natural science fields as well as statisticians, this text requires no previous exposure to analysis of variance, although some familiarity with basic statistical fundamentals is assumed. In keeping with the book's practical orientation, numerous workable problems are presented throughout to reinforce the reader's ability to creatively apply the principles and concepts in any given situation.
THE NATURE OF AGRICULTURAL RESEARCH
Fundamental Concepts
Research by Practitioners
KEY ASSUMPTIONS OF EXPERIMENTAL DESIGNS
Introduction
Assumptions of the Analysis of Variance (ANOVA) and Their Violations
Measures to Detect Failures of the Assumptions
Data Transformation
DESIGNS FOR REDUCING ERROR
Introduction
Approaches to Eliminating Uncontrolled Variations
Error Elimination by Several Groupings of Units
SINGLE-FACTOR EXPERIMENTAL DESIGNS
Introduction
Complete Block Designs
Incomplete Block Designs
TWO-FACTOR EXPERIMENTAL DESIGNS
Factorial Experiments
Main Effects and Interactions in a Two-Factor Experiment
Interpretation of Interactions
Factorials in Complete Block Designs
Split-Plot or Nested Designs
Strip-Plot Design
THREE (OR MORE)-FACTOR EXPERIMENTAL DESIGNS
Introduction
Split-Split-Plot Design
Strip-Split-Plot Design
Factorial Experiments in Fractional Replication
TREATMENT MEANS COMPARISONS
Introduction
Comparisons of Paired Means
Comparisons of Grouped Means
SAMPLE DESIGNS OVER TIME
Terminology and Concepts
Analysis of Experiments over Years
Analysis of Experiments over Seasons
REGRESSION AND CORRELATION ANALYSIS
Bivariate Relationships
Regression Analysis
Correlational Analysis
Curvilinear Regression Analysis
Multiple Regression and Correlation
COVARIANCE ANALYSIS
Introduction
Covariance Analysis Procedures
Estimating Missing Data
Appendix A: Chi-Square Distribution
Appendix B: The Arc SineTransformation
Appendix C: Selected Latin Squares
Appendix D: Random Digits
Appendix E: Points for the Distribution of F
Appendix F: Basic Plans for Balanced and Partially Balanced Lattice Designs
Appendix G: Fractional Factorial Design Plans
Appendix H: Significant Studentized Ranges for 5% and 1% Level New Multiple Range Test
Appendix I: Student t Distribution
Appendix J: Coefficients and the Sum of Squares of Sets of Orthogonal Polynomials When There Are Equal Interval Treatments
Appendix K: Minitab
Index
"… guides readers to think through their problems, to design experiments to answer their questions, to analyze the data accruing from those experiments, and to draw sensible inferences. … the exercises at the end of the chapter give readers the opportunity to test their understanding. … a handy companion for agronomists and environmental scientists who need to experiment with treatments they can control."
-R. Webster, Journal of Environmental Quality, Vol. 36, Issue 1, January-February 2007
"…One strength of the text is that there are many actual agricultural and biological examples and data analysis problems. … This text would be beneficial to those whose backgrounds are in agriculture and biology, those who would like to see basic computational details, and those who prefer the classical test statistic/critical value approach to hypothesis testing."
-Biometrics, December 2006