The Nature of the Book This book is a text for a first course in statistical concepts and methods. It introduces the analysis of data and statistical inference and explains various methods in enough detail so that the student can apply them. Little mathematical background is required; only high school algebra is used. No mathematical proof is given in the body of the text, although algebraic demonstrations are given in appendices at the ends of some chapters. The exposition is based on logic, verbal explanations, figures, and numerical examples. The verbal and conceptual levels are higher than the mathematical leveL The concepts and methods of statistical analysis are illustrated by more than 100 interesting real-life data sets. Some examples are taken from daily life; many deal with the behavioral sciences, some with business, the health sciences, the physical sciences, and engineering. The exercises are of varying degrees of difficulty. This book is suitable for undergraduates in many majors and for grad� uate students in the health sciences, behavioral sciences, and education. It has grown out of our experience over many years of teaching such courses. An earlier text by T. W. Anderson and S. L. Sclove, The Statistical Analysis of Data, had similar objectives and was of a similar nature.

Synopsis

This book provides a non-calculus based introduction to statistics and data analysis for students studying statistics, business, engineering, health sciences, social sciences, and education. It presents a thorough coverage of statistical techniques and includes numerous examples drawn largely from actual research studies. Little mathematical background is required and explanations of important concepts are based on providing intuition with illustrative figures and numerical examples. Part One shows how statistical methods are used in diverse fields in asnwering important questions. Part Two covers descriptive statitics and considers the organization and summarization of data. Parts Three, Four, and Five cover probability, statistical inference, and more advanced statistical techniques, respectively.

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