About the Author

Chin Long Chiang is Professor in the Graduate School, University of California, Berkeley. He was a visiting professor at Harvard, Yale, Emory, Pittsburgh, North Carolina, Michigan, Minnesota, Vanderbilt, Texas, Washington at Seattle, Peking University, and University of London. Professor Chiang has served as a consultant to the WHO, the NIH, and other agencies. He is a fellow of the IMS, the ASA, and the RSS of London. He has published five books, three of them have been translated into Chinese and one into Japanese.

This textbook systematically presents fundamental methods of statistical analysis: from probability and statistical distributions, through basic concepts of statistical inference, to a collection of methods of analysis useful for scientific research. It is rich in tables, diagrams, and examples, in addition to theoretical justification of the methods of analysis introduced. Each chapter has a section entitled "Exercises and Problems" to accompany the text. There are altogether about 300 exercises and problems, answers to the selected problems are given. A section entitled "Proof of the Results in This Chapter" in each chapter provides interested readers with material for further study.

Contents:

• Descriptive Statistics
• Probability
• Random Variables
• Probability Distributions
• Statistical Inference — Interval Estimation
• Hypothesis Testing — Fundamental Concepts
• Testing Hypotheses Concerning Population Means and Population Proportions
• The Chi-Square Test
• Linear Regression
• Correlation
• Multiple Regression and Correlation
• One-Way Analysis of Variance
• Two-Way Analysis of Variance — Fixed Effects Model
• Two-Way Analysis of Variance Random-Effects Model and Mixed Model
• Design of Experiment
• Analysis of Covariance
• Non-Parametric Statistics

"It offers a sound presentation of concepts at either the undergraduate or first-year graduate level, including a moderate amount of calculus ... A resulting strength of the text is that students are presented with a deeper understanding of analytic methods."

"The main merit of this book is that the author gives for every model the corresponding method of hypothesis testing: whether the given assumption holds. The abundance of numerical examples, diagrams, tables helps the reader to analyze the problems arisen not only from biology, but from social sciences, too ... Due to the interesting applications the book can be recommended also to lecturers of theoretical statistics to demonstrate the force of the theory."