1st Edition
Handbook of Statistics for Teaching and Research in Plant and Crop Science
More than a textbook—it’s also a valuable reference book for researchers and crop science professionals!
The Handbook of Statistics for Teaching and Research in Plant and Crop Science presents the fundamental concepts of important statistical methods and experimental designs to the students and researchers who need to apply them to their own specific problems. This comprehensive handbook takes what can be the difficult and confusing topics of statistics and experimental design and explains them in easily understandable terms, making them accessible to nearly every reader. More than a student textbook, it is an essential reference for researchers and professionals in a multitude of fields.
Designed as a two-semester statistical textbook, the first section of the Handbook of Statistics for Teaching and Research in Plant and Crop Science focuses on statistical concepts, providing a foundation of useful knowledge on which you can base your own research. The second section concentrates on experimental designs in plant and crop sciences. The material is presented in a way that helps readers with a minimum of mathematical background to understand important theories and concepts. Derivations of formulas are avoided, and mathematical symbols are used only when essential. To illustrate the computational procedures, data is drawn from actual experiments. At the end of each chapter, examples and exercises are given to provide clear insight into real-life problems. A comprehensive appendix of clearly presented statistical tables is included.
Part One of Handbook of Statistics for Teaching and Research in Plant and Crop Science focuses on statistical methods, principles, and procedures, exploring:
- methods of display of statistical information, such as tables, diagrams, graphs, etc.
- symbols and their use in denoting variables
- descriptions of types of statistical data
- methods of computation from raw and graphed data
- the importance of studying variables and dispersion in research
- the use of normal probability integral tables and their application to practical problems
- descriptions of different types of experiments, such as determinate and nondeterminate
- the significance of expected value in research
- special techniques in descriptive statistics
- explanations of population, sample, and statistical inference
- the significance of null hypothesis in research
- methods of correlation studies
- assumptions and principles in regression analysis
Part Two concentrates on experimental design, principles and procedures, exploring: - basic principles of experimental design
- the fundamental concepts of linear models and analysis of variance
- method and layout of Completely Randomized Design (CRD)
- the advantages and disadvantages of Randomized Complete Block Design (RCBD)
- methods and procedures for comparison of several treatment means
- the important features of Latin Square Design
- factorial experiments
- split plot design
- completely confounded design
- analysis of covariance
- the Chi Square Test of Significance
- the transformation of experimental data
- quality control
- and so much more!
- Foreword (C. Ramasamy)
- Preface
- Acknowledgments
- Introduction
- PART I: STATISTICAL METHODS
- Chapter 1. Tables, Graphs, and Diagrams
- Tables
- Graphs and Diagrams
- Exercises
- Chapter 2. Review of Basic Mathematical Concepts Fundamental to Statistics
- Variables
- Summations
- Logarithms
- Squares and Square Roots
- Quantities
- Permutations and Combinations
- Exercises
- Chapter 3. Nature of Statistical Data
- Raw Data
- Classification of Data
- Exercises
- Chapter 4. Measures of Central Tendency
- Mean
- Median
- Mode
- Exercises
- Chapter 5. Measures of Dispersion
- Variables
- Most Common Measures of Dispersion
- Exercises
- Chapter 6. Normal Distribution
- Properties of Normal Distribution
- Properties of Standard Normal Distribution
- Probability Integral
- Practical Application Examples
- Exercises
- Chapter 7. Probability
- Experiments
- Basic Concepts of Probability
- Exercises
- Chapter 8. Set Theory
- Sample Spaces
- Venn Diagrams
- Expected Value
- Exercises
- Chapter 9. Special Techniques in Descriptive Statistics
- Frequency Distribution
- Discrete Variables
- Exercises
- Chapter 10. Population, Sample, and Statistical Inference
- Population
- Sample
- Parameters and Statistics
- Sample Size and Sampling Distribution of Mean and Variance
- Some Points
- Standard Error
- Exercises
- Chapter 11. Hypothesis and Test of Significance
- Null Hypothesis
- Test of Hypothesis
- Level of Significance
- Interpolation
- Testing of a Population Mean
- Significance of Asterisks
- Exercises
- Chapter 12. Correlation
- Methods of Studying Correlation
- Coefficient of Determination
- Assumptions in Correlation Analysis
- Rank Correlation
- Exercises
- Chapter 13. Regression
- Function Concept and Regression
- Straight Line Equation
- Definition of Error in Regression Estimates
- Prediction and Measurement of Error in Prediction
- Exercises
- Chapter 14. Chi Square Test of Significance
- Definition
- Corrections for Continuity
- Test of Goodness of Fit
- Poisson Distribution
- Procedure for Fitting Normal Distribution
- Test of Independence (or Testing for Association)
- Pearson’s Coefficient of Contingency
- Heterogeneity Chi-Square Analysis
- Exercises
- PART II: EXPERIMENTAL DESIGN
- Chapter 15. Experimental Design
- Experimental Design
- Experimental Unit
- Accuracy
- Precision
- Bias
- Study of Variability Among Plots
- Treatment
- Experimental Error
- Exercises
- Chapter 16. Analysis of Variance
- Fundamental Concepts
- Computation of Variance
- Find the F Ratio Value
- Degrees of Freedom
- F Distribution
- Summary of the ANOVA Technique
- Exercises
- Chapter 17. Principles of Experimental Design
- Replication
- Randomization
- Local Control
- Analysis of Data
- Exercises
- Chapter 18. Completely Randomized Design
- Description of the Design
- F Ratio and Its Significance
- Using the F Table
- Assumptions
- Least Significant Difference
- Computation Procedure for Completely Randomized Design
- Exercises
- Chapter 19. Randomized Complete Block Design
- Two-Way Classification
- The Specifics of Randomized Complete Block Design
- Linear Model for Randomized Complete Block Design
- Missing Values
- Modifications in the Analysis
- Exercises
- Chapter 20. Group Comparisons
- Comparison
- Orthogonal and Nonorthogonal Contrasts
- Partitioning of Treatment Sum of Squares
- Second Set of Orthogonal Comparisons
- Practical Utility of Contrasts
- Exercises
- Chapter 21. Multiple Comparison Procedures
- Least Significant Difference Test
- Duncan’s New Multiple Range Test
- Dunnett’s Test
- Tukey’s w - Procedure Test
- Newman-Keuhl’s Test or Student-Newman-Keuhls Test
- Scheff’s Test or S Test
- Exercises
- Chapter 22. Latin Square Design
- Linear Model
- Advantages and Disadvantages of Latin Square Design
- Latin Square and Trend Analysis
- Exercises
- Chapter 23. Factorial Experiments
- Levels
- Single-Factor Experiment versus Factorial Experiment
- Two-Factor Experiments
- Meaning of Significant Interaction
- Three-Factor Experiments
- Exercises
- Chapter 24. Split Plot Design
- Reasons for Adopting Split Plot Design
- Procedure for Layout of Split Plot Design
- Comparison of Split Plot Design with RCBD
- Standard Errors in Split Plot Design
- Exercises
- Chapter 25. Split Block (Strip Plot)
- Layout
- Combined Analysis in Strip Plot Design
Exercises - Chapter 26. Completely Confounded Design
- Layout of the Experiment
- Choice of Confounding Interactions
- Statistical Analysis
- Identification of Confounded Interaction
- Conclusion
- Exercises
- Chapter 27. Analysis of Covariance
- Reasons for Covariance Analysis
- Uses of Covariance Analysis
- Principles in ANOCOVA with Reference to Two Treatments
- Comparisons Involving Adjusted Means
- Testing Homogeneity of Regression
- Assumptions in Covariance Analysis
- Exercises
- Chapter 28. Transformation of Experimental Data
- Transformation
- Exercises
- Chapter 29. Quality Control
- Quality Control and Statistical Quality Control
- Causes of Variation
- Stable and Unstable Conditions
- Mean Chart
- Quality Control Chart for Range (R Chart)
- P Chart
- C Chart
- Exercises
- Appendix. Statistical Tables
- Index
- Reference Notes Included
Biography
Usha Palaniswamy
