Handbook of Statistics for Teaching and Research in Plant and Crop Science

• 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